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General Admission

<p>Do you want to master the essential mathematical skills for data science and machine learning? Do you want to learn how to apply statistics and probability to real-world problems and scenarios? If yes, then this course is for you!</p>
<p>In this course, you will learn the advanced concepts and techniques of statistics and probability that are widely used in data science and machine learning. You will learn how to describe and analyse data using descriptive statistics, distributions, and probability theory. You will also learn how to perform hypothesis testing, regressions, ANOVA, and machine learning algorithms to make predictions and inferences from data. You will gain hands-on experience with practical exercises and projects using Python and R.</p>
<p><strong>Learning Outcomes</strong></p>
<p>By the end of this course, you will be able to:</p>
<ul>
<li>Apply descriptive statistics, distributions, and probability theory to summarise and visualise data</li>
<li>Perform hypothesis testing, regressions, ANOVA, and machine learning algorithms to make predictions and inferences from data</li>
<li>Use Python and R to implement statistical and machine learning methods</li>
<li>Interpret and communicate the results of your analysis using appropriate metrics and visualisations</li>
<li>Solve real-world problems and scenarios using statistics and probability</li>
</ul>
<h3><b>Why choose this Advanced Diploma in Statistics &amp; Probability for Data Science &amp; Machine Learning at QLS Level 7<span> course</span>?</b></h3>
<ol>
<li>Unlimited access to the course for a lifetime.</li>
<li>Opportunity to earn a certificate accredited by the <b>CPD Quality Standards</b> and <b>CIQ </b>after completing this course.</li>
<li>Structured lesson planning in line with industry standards.</li>
<li>Immerse yourself in innovative and captivating course materials and activities.</li>
<li>Assessments designed to evaluate advanced cognitive abilities and skill proficiency.</li>
<li>Flexibility to complete the Course at your own pace, on your own schedule.</li>
<li>Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience.</li>
<li>Unlock career resources for CV improvement, interview readiness, and job success.</li>
</ol>
<h3><b>Who is this Advanced Diploma in Statistics &amp; Probability for Data Science &amp; Machine Learning at QLS Level 7<span> </span></b><b><span>course </span></b><b>for?</b></h3>
<p>This course is for anyone who wants to learn the advanced concepts and techniques of statistics and probability for data science and machine learning. This course is suitable for:</p>
<ul>
<li>Data scientists, machine learning engineers, and analysts who want to enhance their skills and knowledge</li>
<li>Students and researchers who want to learn the mathematical foundations of data science and machine learning</li>
<li>Professionals and managers who want to understand and apply data-driven decision making</li>
<li>Hobbyists and enthusiasts who want to explore and learn from data</li>
<li>Anyone who loves statistics and probability and wants to challenge themselves</li>
</ul>
<h3><b>Career path</b></h3>
<ul>
<li><strong>Data Scientist</strong> (£35,000 - £55,000)</li>
<li><strong>Machine Learning Engineer</strong> (£40,000 - £60,000)</li>
<li><strong>Statistician</strong> (£35,000 - £55,000)</li>
<li><strong>Data Analyst</strong> (£40,000 - £60,000)</li>
<li><strong>Business Intelligence</strong> <strong>Analyst</strong> (£45,000 - £65,000)</li>
<li><strong>Senior Data Analyst</strong> (£50,000 - £70,000)</li>
</ul>
<h3><b>Prerequisites</b></h3>
<p><span>This </span><b>Advanced Diploma in Statistics &amp; Probability for Data Science &amp; Machine Learning at QLS Level 7</b><span> does not require you to have any prior qualifications or experience. You can just enrol and start learning.This </span><b>Advanced Diploma in Statistics &amp; Probability for Data Science &amp; Machine Learning at QLS Level 7</b><span> was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection.</span></p>
<h3><b>Certification</b></h3>
<p><span>After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8.</span></p>
<p><b>Endorsed Certificate of Achievement from the Quality Licence Scheme</b></p>
<p>Learners will be able to achieve an endorsed certificate after completing the course as proof of their achievement. You can order the endorsed certificate for only £135 to be delivered to your home by post. For international students, there is an additional postage charge of £10.</p>
<p><b>Endorsement</b></p>
<p>The Quality Licence Scheme (QLS) has endorsed this course for its high-quality, non-regulated provision and training programmes. The QLS is a UK-based organisation that sets standards for non-regulated training and learning. This endorsement means that the course has been reviewed and approved by the QLS and meets the highest quality standards.</p>
<p>Please Note: Studyhub is a Compliance Central approved resale partner for Quality Licence Scheme Endorsed courses.</p><div>
				<h3>
	<span>Course Curriculum</span>
</h3>

<div>
<table width="100%">				<tbody><tr>
					<td colspan="4">Section 01: Let's get started</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Welcome!</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>What will you learn in this course?</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>How can you get the most out of it?</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Section 02: Descriptive statistics</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Intro</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Mean</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Median</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Mode</td>
					<td> </td>
					<td><span><i></i> 00:04:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Mean or Median?</td>
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Skewness</td>
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Practice: Skewness</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Solution: Skewness</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Range &amp; IQR</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Sample vs. Population</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Variance &amp; Standard deviation</td>
					<td> </td>
					<td><span><i></i> 00:11:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Impact of Scaling &amp; Shifting</td>
					<td> </td>
					<td><span><i></i> 00:19:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Statistical moments</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Section 03: Distributions</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>What is a distribution?</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Normal distribution</td>
					<td> </td>
					<td><span><i></i> 00:09:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Z-Scores</td>
					<td> </td>
					<td><span><i></i> 00:13:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Practice: Normal distribution</td>
					<td> </td>
					<td><span><i></i> 00:04:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Solution: Normal distribution</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Section 04: Probability theory</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Intro</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Probability Basics</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Calculating simple Probabilities</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Practice: Simple Probabilities</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Quick solution: Simple Probabilities</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Detailed solution: Simple Probabilities</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Rule of addition</td>
					<td> </td>
					<td><span><i></i> 00:13:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Practice: Rule of addition</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Quick solution: Rule of addition</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Detailed solution: Rule of addition</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Rule of multiplication</td>
					<td> </td>
					<td><span><i></i> 00:11:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Practice: Rule of multiplication</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Solution: Rule of multiplication</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Bayes Theorem</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Bayes Theorem - Practical example</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Expected value</td>
					<td> </td>
					<td><span><i></i> 00:11:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Practice: Expected value</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Solution: Expected value</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Law of Large Numbers</td>
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Central Limit Theorem - Theory</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Central Limit Theorem - Intuition</td>
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Central Limit Theorem - Challenge</td>
					<td> </td>
					<td><span><i></i> 00:11:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Central Limit Theorem - Exercise</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Central Limit Theorem - Solution</td>
					<td> </td>
					<td><span><i></i> 00:14:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Binomial distribution</td>
					<td> </td>
					<td><span><i></i> 00:16:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Poisson distribution</td>
					<td> </td>
					<td><span><i></i> 00:17:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Real life problems</td>
					<td> </td>
					<td><span><i></i> 00:15:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Section 05: Hypothesis testing</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Intro</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>What is a hypothesis?</td>
					<td> </td>
					<td><span><i></i> 00:19:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Significance level and p-value</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Type I and Type II errors</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Confidence intervals and margin of error</td>
					<td> </td>
					<td><span><i></i> 00:15:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Excursion: Calculating sample size &amp; power</td>
					<td> </td>
					<td><span><i></i> 00:11:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Performing the hypothesis test</td>
					<td> </td>
					<td><span><i></i> 00:20:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Practice: Hypothesis test</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Solution: Hypothesis test</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>T-test and t-distribution</td>
					<td> </td>
					<td><span><i></i> 00:13:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Proportion testing</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Important p-z pairs</td>
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Section 06: Regressions</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Intro</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Linear Regression</td>
					<td> </td>
					<td><span><i></i> 00:11:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Correlation coefficient</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Practice: Correlation</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Solution: Correlation</td>
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Practice: Linear Regression</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Solution: Linear Regression</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Residual, MSE &amp; MAE</td>
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Practice: MSE &amp; MAE</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Solution: MSE &amp; MAE</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Coefficient of determination</td>
					<td> </td>
					<td><span><i></i> 00:12:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Root Mean Square Error</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Practice: RMSE</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Solution: RMSE</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Section 07: Advanced regression &amp; machine learning algorithms</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Multiple Linear Regression</td>
					<td> </td>
					<td><span><i></i> 00:16:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Overfitting</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Polynomial Regression</td>
					<td> </td>
					<td><span><i></i> 00:13:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Logistic Regression</td>
					<td> </td>
					<td><span><i></i> 00:09:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Decision Trees</td>
					<td> </td>
					<td><span><i></i> 00:21:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Regression Trees</td>
					<td> </td>
					<td><span><i></i> 00:14:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Random Forests</td>
					<td> </td>
					<td><span><i></i> 00:13:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Dealing with missing data</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Section 08: ANOVA (Analysis of Variance)</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>ANOVA - Basics &amp; Assumptions</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>One-way ANOVA</td>
					<td> </td>
					<td><span><i></i> 00:12:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>F-Distribution</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Two-way ANOVA - Sum of Squares</td>
					<td> </td>
					<td><span><i></i> 00:16:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Two-way ANOVA - F-ratio &amp; conclusions</td>
					<td> </td>
					<td><span><i></i> 00:11:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Section 09: Wrap up</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Wrap up</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Assignment</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Assignment - Statistics &amp; Probability for Data Science &amp; Machine Learning</td>
					<td> </td>
					<td><span><i></i> 00:00:00</span></td>
				</tr>
								<tr>
					<td colspan="4"> Order your QLS Endorsed Certificate </td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Order your QLS Endorsed Certificate</td>
					<td> </td>
					<td><span><i></i> 00:00:00</span></td>
				</tr>
				</tbody></table></div>

			</div>

Studyhub UK

Data Science

Diploma in Management Studies (DMS)

Diploma in Professional Studies (DPS)

ICDL (International Certification of Digital Literacy)

Advanced Diploma in Statistics & Probability for Data Science & Machine Learning at QLS Level 7

<strong>Gain proficiency in the mastery of Geographic Information Systems (GIS) via ArcGIS Desktop</strong>
        <p>This course teaches you the most important aspects of spatial data analysis using ArcGIS. It is highly beneficial for both those wanting to learn spatial data analysis and/or gain familiarity with the ArcGIS ecosystem

First, we'll start some basic GIS tasks like 'Zooming'. Then, we'll move into more complex processing tasks like 'Geo-Statistics'. We'll also deal with some theoretical concepts related to Spatial Data Analysis, and then we'll focus on implementing some of the most common GIS techniques (all the way showing you how to execute these tasks in ArcGIS Desktop).

The stuff you'll learn from this course will be extremely useful in terms of you being able to implement it on future Spatial Data projects you'll be working on. The course is a hands-on training with real data. It's a step by step course covering both the theory and application of Spatial Data Analysis. This is one of the most comprehensive courses on this topic.  

All the code and supporting files for this course are available at -
https://github.com/PacktPublishing/ArcGIS-Desktop-For-Spatial-Analysis-Go-From-Basic-To-Pro</p>
        <h2>What You Will Learn</h2><p>You will have a thorough knowledge of the ArcGIS Interface and Functionality<br>You will learn about the different toolboxes in ArcGIS and what they can do<br>You can carry out practical spatial data analysis tasks, geoprocessing and mapping using ArcGIS Desktop<br>You learn about advanced topics such as geostatistics and carry them out on actual data<br>You visualize and map spatial data</p>
        <h2>Audience</h2><p>The target audience is the people looking to get started in the field of GIS Analysis use ArcGIS Desktop in academic or professional settings and students should have access to ArcGIS Desktop. You should have prior knowledge of basic spatial data related concepts such as the different data types and coordinate systems.</p>
        <h2>Approach</h2><p>The approach is full of hands-on instructions via video-lectures, interesting and illustrative examples, clear explanations. Each video lecture will teach you a new concept that you can apply to your own data.</p>
        <h2>Key Features</h2><p>The course will teach you to implement some of the most important spatial data analysis techniques in ArcGIS Desktop * You learn to work with real spatial data * Carry our practical map making to display the results of spatial analysis * Learn about advanced topics such as geostatistics and carry them out on actual data</p>
        <h2>Github Repo</h2><p>https://github.com/packtpublishing/arcgis-desktop-for-spatial-analysis-go-from-basic-to-pro</p>
        <h2>About the Author</h2><h3>Minerva Singh</h3><p>Minerva Singh is a PhD graduate from Cambridge University where she specialized in Tropical Ecology. She is also a part-time Data Scientist. As part of her research, she must carry out extensive data analysis, including spatial data analysis. For this purpose, she prefers to use a combination of freeware tools: R, QGIS, and Python. She does most of her spatial data analysis work using R and QGIS. Apart from being free, these are very powerful tools for data visualization, processing, and analysis. She also holds an MPhil degree in Geography and Environment from Oxford University. She has honed her statistical and data analysis skills through several MOOCs, including The Analytics Edge and Statistical. In addition to spatial data analysis, she is also proficient in statistical analysis, machine learning, and data mining.</p>
        <h2>Course Outline</h2><h4>1. Welcome to Spatial Data Analysis and Visualization</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. What is this Course About and Meet the Instructor</p><p style='margin: 0'>Welcome to Spatial Data Analysis and Visualization: What is this Course About and Meet the Instructor</p></td></tr><tr><td style='padding: 15px;'><p>2. Some Spatial Data Analysis Related Concepts</p><p style='margin: 0'>Welcome to Spatial Data Analysis and Visualization: Some Spatial Data Analysis Related Concepts</p></td></tr><tr><td style='padding: 15px;'><p>3. Conclusion to Section 1</p><p style='margin: 0'>Welcome to Spatial Data Analysis and Visualization: Conclusion to Section 1</p></td></tr></tbody></table><br><h4>2. Introduction to ArcGIS Desktop and its Functionality</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. What is ArcGIS Desktop?</p><p style='margin: 0'>Introduction to ArcGIS Desktop and its Functionality: What is ArcGIS Desktop?</p></td></tr><tr><td style='padding: 15px;'><p>2. Accessing and Displaying Spatial Data in ArcGIS</p><p style='margin: 0'>Introduction to ArcGIS Desktop and its Functionality: Accessing and Displaying Spatial Data in ArcGIS</p></td></tr><tr><td style='padding: 15px;'><p>3. Finding and identifying Features and Values in ArcGIS Desktop</p><p style='margin: 0'>Introduction to ArcGIS Desktop and its Functionality: Finding and identifying Features and Values in ArcGIS Desktop</p></td></tr><tr><td style='padding: 15px;'><p>4. Making Selections in ArcGIS</p><p style='margin: 0'>Introduction to ArcGIS Desktop and its Functionality: Making Selections in ArcGIS</p></td></tr><tr><td style='padding: 15px;'><p>5. Zooming and Measuring</p><p style='margin: 0'>Introduction to ArcGIS Desktop and its Functionality: Zooming and Measuring</p></td></tr><tr><td style='padding: 15px;'><p>6. Calculate Shapefile Geometry in ArcGIS</p><p style='margin: 0'>Introduction to ArcGIS Desktop and its Functionality: Calculate Shapefile Geometry in ArcGIS</p></td></tr><tr><td style='padding: 15px;'><p>7. Working With Different Coordinate Systems in ArcGIS</p><p style='margin: 0'>Introduction to ArcGIS Desktop and its Functionality: Working With Different Coordinate Systems in ArcGIS</p></td></tr><tr><td style='padding: 15px;'><p>8. Conclusion to Section 2</p><p style='margin: 0'>Introduction to ArcGIS Desktop and its Functionality: Conclusion to Section 2</p></td></tr></tbody></table><br><h4>3. Working with Raster Data in ArcGIS Desktop</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Displaying Raster Data in ArcGIS</p><p style='margin: 0'>Working with Raster Data in ArcGIS Desktop: Displaying Raster Data in ArcGIS</p></td></tr><tr><td style='padding: 15px;'><p>2. Merge Rasters in ArcGIS</p><p style='margin: 0'>Working with Raster Data in ArcGIS Desktop: Merge Rasters in ArcGIS</p></td></tr><tr><td style='padding: 15px;'><p>3. Band Arithmetic in ArcGIS Desktop</p><p style='margin: 0'>Working with Raster Data in ArcGIS Desktop: Band Arithmetic in ArcGIS Desktop</p></td></tr><tr><td style='padding: 15px;'><p>4. Reclassify a Raster in ArcGIS Desktop</p><p style='margin: 0'>Working with Raster Data in ArcGIS Desktop: Reclassify a Raster in ArcGIS Desktop</p></td></tr><tr><td style='padding: 15px;'><p>5. Resample a Raster in ArcGIS</p><p style='margin: 0'>Working with Raster Data in ArcGIS Desktop: Resample a Raster in ArcGIS</p></td></tr><tr><td style='padding: 15px;'><p>6. Topographic Data Products-Brief Theoretical Introduction</p><p style='margin: 0'>Working with Raster Data in ArcGIS Desktop: Topographic Data Products-Brief Theoretical Introduction</p></td></tr><tr><td style='padding: 15px;'><p>7. Topographic Calculations in ArcGIS Desktop</p><p style='margin: 0'>Working with Raster Data in ArcGIS Desktop: Topographic Calculations in ArcGIS Desktop</p></td></tr><tr><td style='padding: 15px;'><p>8. Clip a Raster to the Extent of a Polygon in ArcGIS Desktop</p><p style='margin: 0'>Working with Raster Data in ArcGIS Desktop: Clip a Raster to the Extent of a Polygon in ArcGIS Desktop</p></td></tr><tr><td style='padding: 15px;'><p>9. Zonal Statistics</p><p style='margin: 0'>Working with Raster Data in ArcGIS Desktop: Zonal Statistics</p></td></tr><tr><td style='padding: 15px;'><p>10. Extract Raster Values to Points</p><p style='margin: 0'>Working with Raster Data in ArcGIS Desktop: Extract Raster Values to Points</p></td></tr><tr><td style='padding: 15px;'><p>11. Geo-referencing a Raster in ArcGIS Desktop</p><p style='margin: 0'>Working with Raster Data in ArcGIS Desktop: Geo-referencing a Raster in ArcGIS Desktop</p></td></tr><tr><td style='padding: 15px;'><p>12. Conclusion to Section 3</p><p style='margin: 0'>Working with Raster Data in ArcGIS Desktop: Conclusion to Section 3</p></td></tr></tbody></table><br><h4>4. Working with Vector Data in ArcGIS Desktop</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Exploratory Data Analysis with Shapefile Attributes in ArcGIS Desktop</p><p style='margin: 0'>Working with Vector Data in ArcGIS Desktop: Exploratory Data Analysis with Shapefile Attributes in ArcGIS Desktop</p></td></tr><tr><td style='padding: 15px;'><p>2. Basic Graphing of Shapefile Attributes in ArcGIS Desktop</p><p style='margin: 0'>Working with Vector Data in ArcGIS Desktop: Basic Graphing of Shapefile Attributes in ArcGIS Desktop</p></td></tr><tr><td style='padding: 15px;'><p>3. Spatial Join with Tabular Data</p><p style='margin: 0'>Working with Vector Data in ArcGIS Desktop: Spatial Join with Tabular Data</p></td></tr><tr><td style='padding: 15px;'><p>4. Spatial Joins in ArcGIS Based on Spatial Location</p><p style='margin: 0'>Working with Vector Data in ArcGIS Desktop: Spatial Joins in ArcGIS Based on Spatial Location</p></td></tr><tr><td style='padding: 15px;'><p>5. Create Choropleth Maps</p><p style='margin: 0'>Working with Vector Data in ArcGIS Desktop: Create Choropleth Maps</p></td></tr><tr><td style='padding: 15px;'><p>6. Split Shapefiles Using ArcGIS</p><p style='margin: 0'>Working with Vector Data in ArcGIS Desktop: Split Shapefiles Using ArcGIS</p></td></tr><tr><td style='padding: 15px;'><p>7. Clip Shapefile in ArcGIS</p><p style='margin: 0'>Working with Vector Data in ArcGIS Desktop: Clip Shapefile in ArcGIS</p></td></tr><tr><td style='padding: 15px;'><p>8. Intersection of Shapefiles in ArcGIS</p><p style='margin: 0'>Working with Vector Data in ArcGIS Desktop: Intersection of Shapefiles in ArcGIS</p></td></tr><tr><td style='padding: 15px;'><p>9. Add Buffer Areas to Shapefiles in ArcGIS Desktop</p><p style='margin: 0'>Working with Vector Data in ArcGIS Desktop: Add Buffer Areas to Shapefiles in ArcGIS Desktop</p></td></tr><tr><td style='padding: 15px;'><p>10. Merge and Append Shapefiles in ArcGIS Desktop</p><p style='margin: 0'>Working with Vector Data in ArcGIS Desktop: Merge and Append Shapefiles in ArcGIS Desktop</p></td></tr><tr><td style='padding: 15px;'><p>11. Dissolve Shapefiles in ArcGIS</p><p style='margin: 0'>Working with Vector Data in ArcGIS Desktop: Dissolve Shapefiles in ArcGIS</p></td></tr><tr><td style='padding: 15px;'><p>12. Conclusion to Section 4</p><p style='margin: 0'>Working with Vector Data in ArcGIS Desktop: Conclusion to Section 4</p></td></tr></tbody></table><br><h4>5. More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Euclidean Distance Raster Generation in ArcGIS Desktop</p><p style='margin: 0'>More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics: Euclidean Distance Raster Generation in ArcGIS Desktop</p></td></tr><tr><td style='padding: 15px;'><p>2. Density Analysis in ArcGIS Desktop</p><p style='margin: 0'>More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics: Density Analysis in ArcGIS Desktop</p></td></tr><tr><td style='padding: 15px;'><p>3. Compute Line Density in ArcGIS</p><p style='margin: 0'>More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics: Compute Line Density in ArcGIS</p></td></tr><tr><td style='padding: 15px;'><p>4. Compute Point Density in ArcGIS</p><p style='margin: 0'>More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics: Compute Point Density in ArcGIS</p></td></tr><tr><td style='padding: 15px;'><p>5. Kernel Density for Linear and Point Features in ArcGIS</p><p style='margin: 0'>More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics: Kernel Density for Linear and Point Features in ArcGIS</p></td></tr><tr><td style='padding: 15px;'><p>6. Interpolation of Point Data-Theory</p><p style='margin: 0'>More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics: Interpolation of Point Data-Theory</p></td></tr><tr><td style='padding: 15px;'><p>7. Interpolation of Point Data-Application</p><p style='margin: 0'>More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics: Interpolation of Point Data-Application</p></td></tr><tr><td style='padding: 15px;'><p>8. Mapping Spatial Clusters in ArcGIS Desktop-Theory</p><p style='margin: 0'>More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics: Mapping Spatial Clusters in ArcGIS Desktop-Theory</p></td></tr><tr><td style='padding: 15px;'><p>9. Mapping Spatial Clusters in ArcGIS Desktop-Application</p><p style='margin: 0'>More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics: Mapping Spatial Clusters in ArcGIS Desktop-Application</p></td></tr><tr><td style='padding: 15px;'><p>10. Geographically Weighted Regression in ArcGIS-Theory</p><p style='margin: 0'>More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics: Geographically Weighted Regression in ArcGIS-Theory</p></td></tr><tr><td style='padding: 15px;'><p>11. Geographically Weighted Regression in ArcGIS-Application</p><p style='margin: 0'>More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics: Geographically Weighted Regression in ArcGIS-Application</p></td></tr><tr><td style='padding: 15px;'><p>12. Model Builder for Automating Geoprocessing</p><p style='margin: 0'>More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics: Model Builder for Automating Geoprocessing</p></td></tr><tr><td style='padding: 15px;'><p>13. Conclusion to Section 5</p><p style='margin: 0'>More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics: Conclusion to Section 5</p></td></tr></tbody></table><br><h4>6. Make Simple Maps in ArcGIS</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Examples of ArcGIS Maps</p><p style='margin: 0'>Make Simple Maps in ArcGIS: Examples of ArcGIS Maps</p></td></tr><tr><td style='padding: 15px;'><p>2. Presenting Spatial Data As a Layer File</p><p style='margin: 0'>Make Simple Maps in ArcGIS: Presenting Spatial Data As a Layer File</p></td></tr><tr><td style='padding: 15px;'><p>3. Using Base Maps provided by ArcGIS to Provide Context to Our Map</p><p style='margin: 0'>Make Simple Maps in ArcGIS: Using Base Maps provided by ArcGIS to Provide Context to Our Map</p></td></tr><tr><td style='padding: 15px;'><p>4. Putting Together a Map</p><p style='margin: 0'>Make Simple Maps in ArcGIS: Putting Together a Map</p></td></tr><tr><td style='padding: 15px;'><p>5. Conclusion to Section 6</p><p style='margin: 0'>Make Simple Maps in ArcGIS: Conclusion to Section 6</p></td></tr></tbody></table>

Programming

Gain proficiency in the mastery of Geographic Information Systems (GIS) via ArcGIS Desktop

ArcGIS Desktop for Spatial Analysis: Go from Basic to Pro

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					<p><span>This comprehensive course on </span><b><span>CompTIA PenTest+ (Ethical Hacking)</span></b> will deepen your understanding on this topic.</p><p><span><span>After successful completion of this course you can acquire the required skills in this sector. This </span><b>CompTIA PenTest+ (Ethical Hacking)</b> comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market.</span></p><p><span><span>So enrol in this course today to fast track your career ladder.</span></span></p>					</div>
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					<p><span>There is no experience or previous qualifications required for enrolment on this </span><b><span>CompTIA PenTest+ (Ethical Hacking)</span></b>. It is available to all students, of all academic backgrounds.</p>					</div>
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			<h2>Requirements</h2>		</div>
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					<p><span>Our </span><b><span>CompTIA PenTest+ (Ethical Hacking)</span></b> is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G.</p><p><span><span>There is no time limit for completing this course, it can be studied in your own time at your own pace.</span></span></p>					</div>
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					</div> <h3>Course Curriculum</h3><div><p>6 sections • 67 lectures • 10:48:00 total length</p></div><div><div><div><div><div><div><div><p>•Introduction: 00:09:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Planning a Pen Test: 00:09:00</p></div><div><div><p>•Rules of Engagement: 00:11:00</p></div><div><div><p>•Resources and Budget: 00:07:00</p></div><div><div><p>•Impact and Constraints: 00:05:00</p></div><div><div><p>•Support Resources: 00:13:00</p></div><div><div><p>•Legal Groundwork: 00:12:00</p></div><div><div><p>•Scope Considerations: 00:11:00</p></div><div><div><p>•Lab Environment Setup: 00:23:00</p></div><div><div><p>•Project Strategy and Risk: 00:09:00</p></div><div><div><p>•Scope Vulnerabilities: 00:14:00</p></div><div><div><p>•Compliance-Based Assessments: 00:05:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Scanning and Enumeration: 00:05:00</p></div><div><div><p>•Scanning Demo: 00:11:00</p></div><div><div><p>•Packet Investigation: 00:08:00</p></div><div><div><p>•Packet Inspection Demo: 00:06:00</p></div><div><div><p>•Application and Open-Source Resources: 00:12:00</p></div><div><div><p>•Vulnerability Scanning: 00:09:00</p></div><div><div><p>•Vulnerability Scanning Demo: 00:17:00</p></div><div><div><p>•Target Considerations: 00:16:00</p></div><div><div><p>•Nmap Timing and Performance Options: 00:07:00</p></div><div><div><p>•Prioritization of Vulnerabilities: 00:09:00</p></div><div><div><p>•Common Attack Techniques: 00:12:00</p></div><div><div><p>•Credential Attacks: 00:15:00</p></div><div><div><p>•Weaknesses in Specialized Systems: 00:18:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Remote Social Engineering: 00:07:00</p></div><div><div><p>•Spear Phishing Demo: 00:10:00</p></div><div><div><p>•In-Person Social Engineering: 00:12:00</p></div><div><div><p>•Network-Based Exploits: 00:07:00</p></div><div><div><p>•FTP Exploit Demo: 00:08:00</p></div><div><div><p>•Man-in-the-middle Exploits: 00:07:00</p></div><div><div><p>•Wireless Exploits: 00:14:00</p></div><div><div><p>•Application Exploits, Part 1: 00:06:00</p></div><div><div><p>•SQL Injection Demo: 00:09:00</p></div><div><div><p>•Application Exploits, Part 2: 00:08:00</p></div><div><div><p>•Application Exploits, Part 3: 00:09:00</p></div><div><div><p>•Cross-Site Scripting Demo: 00:07:00</p></div><div><div><p>•Code Vulnerabilities: 00:17:00</p></div><div><div><p>•Local Host Vulnerabilities: 00:05:00</p></div><div><div><p>•Privilege Escalation (Linux): 00:10:00</p></div><div><div><p>•Privilege Escalation (Windows): 00:06:00</p></div><div><div><p>•Misc. Privilege Escalation: 00:08:00</p></div><div><div><p>•Misc. Local Host Vulnerabilities: 00:08:00</p></div><div><div><p>•Physical Security: 00:11:00</p></div><div><div><p>•Post-Exploitation Techniques: 00:11:00</p></div><div><div><p>•Persistence and Stealth: 00:11:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Nmap Scoping &amp; Output Options: 00:21:00</p></div><div><div><p>•Pen Testing Toolbox: 00:07:00</p></div><div><div><p>•Using Kali Linux: 00:06:00</p></div><div><div><p>•Scanners &amp; Credential Tools: 00:10:00</p></div><div><div><p>•Code-Cracking Tools: 00:05:00</p></div><div><div><p>•Open-Source Research Tools: 00:07:00</p></div><div><div><p>•Wireless and Web Pen Testing Tools: 00:11:00</p></div><div><div><p>•Remote Access Tools: 00:06:00</p></div><div><div><p>•Analyzers and Mobile Pen Testing Tools: 00:03:00</p></div><div><div><p>•Other Pen Testing Tools: 00:05:00</p></div><div><div><p>•Using Scripting in Pen Testing: 00:13:00</p></div><div><div><p>•Bash Scripting Basics: 00:15:00</p></div><div><div><p>•Bash Scripting Techniques: 00:10:00</p></div><div><div><p>•PowerShell Scripts: 00:04:00</p></div><div><div><p>•Ruby Scripts: 00:07:00</p></div><div><div><p>•Python Scripts: 00:06:00</p></div><div><div><p>•Scripting Languages Comparison: 00:11:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Writing Reports: 00:16:00</p></div><div><div><p>•Post-Report Activities: 00:06:00</p></div><div><div><p>•Mitigation Strategies: 00:05:00</p></div><div><div><p>•Communication: 00:10:00</p></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div>

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Certified Ethical Hacker (CEH)

CompTIA A+

CompTIA Security+

Ethical Hacking

CompTIA PenTest+ (Ethical Hacking)

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			<h2>Overview
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					<p><span>This comprehensive course on Recruitment: IT Basics for IT Recruiters</span><b> </b><span>will deepen your understanding on this topic.</span></p><p><span>After successful completion of this course you can acquire the required skills in this sector. This Recruitment: IT Basics for IT Recruiters</span><span> comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market.   </span></p><p><span>So enrol in this course today to fast-track your career ladder.</span></p>					</div>
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			<h2>How will I get my certificate?</h2>		</div>
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					<p><span>You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate.</span></p>					</div>
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			<h2>Who is This course for?</h2>		</div>
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					<p><span>There is no experience or previous qualifications required for enrolment on this Recruitment: IT Basics for IT Recruiters</span><span>. It is available to all students, of all academic backgrounds.</span></p>					</div>
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			<h2>Requirements</h2>		</div>
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					<p><span>Our Recruitment: IT Basics for IT Recruiters</span><span> is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G.</span></p>					</div>
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			<h2>Career Path</h2>		</div>
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					<p><span>Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to-</span></p><ul><li><span>Open doors of opportunities</span></li><li><span>Increase your adaptability</span></li><li><span>Keep you relevant</span></li><li><span>Boost confidence</span></li></ul><p><span>And much more!</span></p>					</div>
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					</div> <h3>Course Curriculum</h3><div><p>9 sections • 62 lectures • 05:10:00 total length</p></div><div><div><div><div><div><div><div><p>•Introduction: 00:02:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Server: 00:08:00</p></div><div><div><p>•What is hardware and software?: 00:04:00</p></div><div><div><p>•Project Life Cycle: 00:06:00</p></div><div><div><p>•Software Development Life Cycle: 00:08:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Methodologies: Scrum, Agile, Kanban, Waterfall, Lean: 00:09:00</p></div><div><div><p>•CMS: 00:04:00</p></div><div><div><p>•API: 00:04:00</p></div><div><div><p>•Stacks: 00:03:00</p></div><div><div><p>•Native &amp; Hybrid Native Apps: 00:02:00</p></div><div><div><p>•CI / CD / Deployment tools: 00:04:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•CTO: 00:13:00</p></div><div><div><p>•IT Architects: 00:08:00</p></div><div><div><p>•Product Owner: 00:12:00</p></div><div><div><p>•Product Manager: 00:06:00</p></div><div><div><p>•PO vs Product Manager: 00:04:00</p></div><div><div><p>•Project Manager: 00:13:00</p></div><div><div><p>•Product Owner vs Project Manager vs Product Manager: 00:07:00</p></div><div><div><p>•Business Analysts: 00:09:00</p></div><div><div><p>•Business Intelligence Analyst: 00:06:00</p></div><div><div><p>•Data Engineer: 00:05:00</p></div><div><div><p>•Data Scientist: 00:07:00</p></div><div><div><p>•Data Engineer vs Data Scientist: 00:07:00</p></div><div><div><p>•Agile Coach: 00:14:00</p></div><div><div><p>•Scrum Master: 00:08:00</p></div><div><div><p>•Agile Coach vs Scrum Master: 00:01:00</p></div><div><div><p>•Frontend Developer: 00:06:00</p></div><div><div><p>•Backend Developer: 00:06:00</p></div><div><div><p>•Fullstack Developer: 00:04:00</p></div><div><div><p>•Developers: Frontend, Backend and Fullstack: 00:02:00</p></div><div><div><p>•iOS Developer: 00:03:00</p></div><div><div><p>•Android Developer: 00:04:00</p></div><div><div><p>•UX Designers: 00:09:00</p></div><div><div><p>•UI Design: 00:08:00</p></div><div><div><p>•UX vs UI Design: what is the difference?: 00:04:00</p></div><div><div><p>•QA Engineers and Testers: 00:09:00</p></div><div><div><p>•System Administrators: 00:07:00</p></div><div><div><p>•DevOps: 00:05:00</p></div><div><div><p>•SEO Specialists: who are they?: 00:10:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Programming Languages and Frameworks. Introduction: 00:01:00</p></div><div><div><p>•Programming languages and frameworks: 00:08:00</p></div><div><div><p>•JavaScript: 00:02:00</p></div><div><div><p>•Java: 00:03:00</p></div><div><div><p>•Python: 00:01:00</p></div><div><div><p>•C: 00:02:00</p></div><div><div><p>•C#: 00:02:00</p></div><div><div><p>•C++: 00:03:00</p></div><div><div><p>•SWIFT: 00:02:00</p></div><div><div><p>•Objective C: 00:01:00</p></div><div><div><p>•HTML: 00:02:00</p></div><div><div><p>•PHP: 00:02:00</p></div><div><div><p>•Ruby: 00:02:00</p></div><div><div><p>•SQL: 00:02:00</p></div><div><div><p>•Go: 00:01:00</p></div><div><div><p>•R: 00:01:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Database: 00:05:00</p></div><div><div><p>•Types of Databases: 00:07:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•The day of an IT Recruiter: 00:05:00</p></div><div><div><p>•Key principles: 00:03:00</p></div><div><div><p>•Sourcing Tips: 00:03:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Thank you for taking part in this course!: 00:01:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Assignment - Recruitment: IT Basics for IT Recruiters: 00:00:00</p></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div>

Online Course Marketing

Recruitment Consultant

IT Skills

Computer Skills

Trainers Course

Recruitment: IT Basics for IT Recruiters

<div id="course-pills-1">Duration<p>3 Days</p><p>18 CPD hours</p>This course is intended for<p>Server administrators<br />Network engineers<br />Systems engineers<br />Consulting systems engineers<br />Technical solutions architects<br />Network administrators<br />Storage administrators<br />Network managers<br />Cisco integrators and partners</p>Overview<p>After taking this course, you should be able to:<br />Describe and implement Fibre Channel, zoning, and N-Port Virtualization (NPV) features on Cisco UCS<br />Describe and implement Fibre Channel over Ethernet (FCoE) on Cisco UCS<br />Describe Cisco UCS policies for service profiles<br />Describe Cisco Adapter Fabric Extender (FEX) and Single Root I/O Virtualization<br />Describe and implement Role-Based Access Control (RBAC) on Cisco UCS<br />Describe and implement external authentication providers on Cisco UCS Manager<br />Describe and implement key management on Cisco UCS Manager<br />Describe Cisco UCS Director<br />Describe and implement Cisco Intersight<br />Describe the scripting options for Cisco UCS Manager<br />Describe and implement monitoring on Cisco UCS Manager</p><p>The Configuring Cisco Unified Computing System (DCCUCS) v1.0 shows you how to deploy, secure, operate, and maintain Cisco Unified Computing System? (Cisco UCSÂ©) B-series blade servers, Cisco UCS C-Series, and S-Series rack servers for use in data centers. You will learn how to implement management and orchestration software for Cisco UCS. You will gain hands-on practice: configuring key features of Cisco UCS, Cisco UCS Director, and Cisco UCS Manager; implementing UCS management software including Cisco UCS Manager and Cisco Intersight?; and more.</p></div><div id="course-pills-2"><h4>Implementing Cisco UCS Storage Area Network (SAN)</h4><ul><li>SAN Introduction</li><li>Cisco UCS Fabric Interconnect Fibre Channels modes</li><li>Named VSANs</li><li>Cisco UCS Fibre Channel and FCoE Storage Connectivity</li></ul><h4>Describing Cisco UCS Policies for Service Profiles</h4><ul><li>Storage Policies and Profiles</li><li>Basic Input Output System (BIOS) Policies</li><li>Boot Policy</li><li>Intelligent Platform Management Interface (IPMI) Policies</li><li>Scrub Policies</li><li>Maintenance Policies</li></ul><h4>Describing Cisco Adapter FEX and Single Root I/O Virtualization</h4><ul><li>Cisco FEX Overview</li><li>Cisco Adapter FEX</li><li>Single Root I/O Virtualization</li></ul><h4>Implementing RBAC on Cisco UCS</h4><ul><li>RBAC in Cisco UCS</li><li>Users, Roles, and Privileges</li><li>Functions of Organizations and Locales</li><li>Effective Rights of a User</li></ul><h4>Implementing External Authentication Providers</h4><ul><li>Options for External Authentication Providers</li></ul><h4>Implementing Key Management on Cisco UCS Manager</h4><ul><li>Public Key Infrastructure</li></ul><h4>Implementing Cisco UCS Director</h4><ul><li>Cisco UCS Director Overview</li><li>Policies, Virtual Data Centers, and Catalogs</li><li>Cisco UCS Director Virtualization Support</li><li>Managing Compute with Cisco UCS Director</li><li>Cisco UCS Manager Orchestration</li><li>Self-Service Portal</li><li>Reporting and Monitoring in Cisco UCS Director</li></ul><h4>Implementing Cisco Intersight</h4><ul><li>Cisco UCS Director Overview</li><li>Important Features of Cisco Intersight</li></ul><h4>Describing the Scripting Options for Cisco UCS Manager</h4><ul><li>Cisco UCS Manager XML API</li><li>Cisco UCS Management Information Tree</li><li>Managed Object Browser</li><li>Cisco UCS PowerTool</li><li>Cisco UCS Python Software Development Kit (SDK)</li></ul><h4>Implementing Key Management on Cisco UCS Manager</h4><ul><li>Public Key Infrastructure</li></ul><h4>Implementing Cisco Intersight</h4><ul><li>Cisco Intersight Overview</li><li>Important Features of Cisco Intersight</li></ul><h4>Describing the Scripting Options for Cisco UCS Manager</h4><ul><li>Cisco UCS Manager XML API</li><li>Cisco UCS Management Information Tree</li><li>Managed Object Browser</li><li>Cisco UCS Manager PowerTool</li><li>Cisco UCS Python SDK</li></ul><h4>Implementing Monitoring on Cisco UCS Manager</h4><ul><li>Logging Sources in Cisco UCS Manager</li><li>Port Monitoring Capabilities of Cisco UCS Manager</li><li>Simple Network Management Protocol (SNMP) Security Ramifications</li><li>Cisco UCS Manager Call Home Feature</li></ul><h4>Lab outline</h4><ul><li>Configure Pod-Specific Device Aliases</li><li>Configure Zoning</li><li>Configure VSANs in Cisco UCS Manager</li><li>Configure Unified Ports on Cisco UCS Fabric Interconnects</li><li>Install and Boot VMware Elastic Sky X Integrated (ESXi) on Cisco UCS from the FCoE Logical Unit Number (LUN) via FCoE</li><li>Configure RBAC</li><li>Configure Cisco UCS Manager to Authenticate Users via Open Lightweight Directory Access Protocol (OpenLDAP)</li><li>Configure a Trusted Point and Key Ring in Cisco UCS Manager</li><li>Configure Cisco UCS with Cisco Intersight</li><li>Configure Cisco UCS Manager Using Scripting</li><li>Implement Syslog and Call Home</li></ul></div><div id="course-pills-3"><h4>Additional course details:</h4><br /><p>Nexus Humans Cisco Configuring Cisco Unified Computing System v1.0 (DCCUCS) training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. </p><p></p> This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. <p></p>Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success.  <p></p>While we feel this is the best course for the Cisco Configuring Cisco Unified Computing System v1.0 (DCCUCS) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you.  <p></p>Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.<p></p></div>

Nexus Human

Cisco Certified Network Associate (CCNA)

Cisco Certified Network Professional certification (CCNP)

Certificate in Information Security Management Principles (CISMP)

Cisco Certified Entry Networking Technician (CCENT)

Cisco Certified Internetwork Expert (CCIE)

IT Networking Fundamentals

Cisco Configuring Cisco Unified Computing System v1.0 (DCCUCS)

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	<h3><b>Description: </b></h3>
<p><span>Gaming has been considered as one of the most popular hobbies in the world. Since the demand for games is not decreasing just yet, game development has continued to grow and develop. If you are interested in gaming, you need to put in your mind that learning the basics will help you in this industry. But adding lessons on how to develop and test games could take you a step ahead which this course will be able to provide. You will also be provided with social gaming guide and financial tips that could take you even further in the gaming industry.</span></p>
<h3><b>Who is the course for?</b></h3>
<ul>
<li><span>Game developers or professionals who want to improve their gaming basics for development</span></li>
<li><span>People who have an interest in becoming part of the game development industry.</span></li>
</ul>
<h3><b>Entry Requirement:</b></h3>
<ul>
<li><span>This course is available to all learners, of all academic backgrounds. </span></li>
<li><span>Learners should be aged 16 or over to undertake the qualification.</span></li>
<li><span>Good understanding of English language, numeracy and ICT are required to attend this course.</span></li>
</ul>
<h3><b>Assessment:  </b></h3>
<ul>
<li><span>At the end of the course, you will be required to sit an online multiple-choice test. Your test will be assessed automatically and immediately so that you will instantly know whether you have been successful.</span></li>
<li><span>Before sitting for your final exam, you will have the opportunity to test your proficiency with a mock exam. </span></li>
</ul>
<h3><b>Certification: </b></h3>
<ul>
<li><span>After you have successfully passed the test, you will be able to obtain an Accredited Certificate of Achievement. You can however also obtain a Course Completion Certificate following the course completion without sitting for the test. Certificates can be obtained either in hard copy at the cost of £39 or in PDF format at the cost of £24. </span></li>
<li><span>PDF certificate's turnaround time is 24 hours, and for the hardcopy certificate, it is 3-9 working days.</span></li>
</ul>
<h3><b>Why choose us?</b></h3>
<ul>
<li><span>Affordable, engaging &amp; high-quality e-learning study materials;</span></li>
<li><span>Tutorial videos/materials from the industry leading experts;</span></li>
<li><span>Study in a user-friendly, advanced online learning platform;</span></li>
<li><span>Efficient exam systems for the assessment and instant result; </span></li>
<li><span>The UK &amp; internationally recognized accredited qualification;</span></li>
<li><span>Access to course content on mobile, tablet or desktop from anywhere anytime;</span></li>
<li><span>The benefit of career advancement opportunities;</span></li>
<li><span>24/7 student support via email.</span></li>
</ul>
<h3><b>Career Path:</b></h3>
<p><span>The Gaming 5 Course Bundle would be beneficial for the following careers:</span></p>
<ul>
<li><span>Animator</span></li>
<li><span>Audio Engineer</span></li>
<li><span>Beta Tester</span></li>
<li><span>Creative Director</span></li>
<li><span>Executive Producer</span></li>
<li><span>Game Developer</span></li>
<li><span>Game Programmer</span></li>
<li><span>Game Tester</span></li>
<li><span>Games Artist</span></li>
<li><span>Product Manager</span></li>
<li><span>QA Tester</span></li>
<li><span>Software Developer.</span></li>
</ul>
		</div><table width="100%">				<tbody><tr>
					<td colspan="4">Gaming Basics</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Introduction</td>
					<td> </td>
					<td><span><i></i> 00:30:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Understanding Consoles</td>
					<td> </td>
					<td><span><i></i> 01:00:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Using Your Computer</td>
					<td> </td>
					<td><span><i></i> 01:00:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Using Your Phone</td>
					<td> </td>
					<td><span><i></i> 01:00:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Using the Internet</td>
					<td> </td>
					<td><span><i></i> 00:30:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Where to Find Free Software</td>
					<td> </td>
					<td><span><i></i> 01:00:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Understanding Accessories Dealing with Drugs</td>
					<td> </td>
					<td><span><i></i> 00:30:00</span></td>
				</tr>
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					<td><i></i></td>
					<td>Wrapping Up</td>
					<td> </td>
					<td><span><i></i> 00:15:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Developing Games</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Introduction To Game Creation</td>
					<td> </td>
					<td><span><i></i> 00:30:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Essential Tools</td>
					<td> </td>
					<td><span><i></i> 01:00:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>2D Game Creation Software</td>
					<td> </td>
					<td><span><i></i> 01:00:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>3D Game Creation Software</td>
					<td> </td>
					<td><span><i></i> 01:00:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>3D Game Creation</td>
					<td> </td>
					<td><span><i></i> 00:30:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Game Modification</td>
					<td> </td>
					<td><span><i></i> 01:00:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>How To Create  a Game on a Social Site</td>
					<td> </td>
					<td><span><i></i> 00:30:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Wrapping Up</td>
					<td> </td>
					<td><span><i></i> 00:15:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Testing Games</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Introduction to Game Testing</td>
					<td> </td>
					<td><span><i></i> 01:00:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Two Rules of Game Testing</td>
					<td> </td>
					<td><span><i></i> 01:00:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>How to Put a Resume Together</td>
					<td> </td>
					<td><span><i></i> 01:00:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>How give  Examples During Job Interview</td>
					<td> </td>
					<td><span><i></i> 00:30:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Contacting Game Developers</td>
					<td> </td>
					<td><span><i></i> 01:00:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Use the Correct Search Keywords</td>
					<td> </td>
					<td><span><i></i> 00:30:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Wrapping Up</td>
					<td> </td>
					<td><span><i></i> 00:15:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Social Gaming Guide</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Introduction</td>
					<td> </td>
					<td><span><i></i> 01:00:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>How to Use the Application Launcher</td>
					<td> </td>
					<td><span><i></i> 00:30:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Farmville on Facebook</td>
					<td> </td>
					<td><span><i></i> 01:00:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Facebook Words with Friends</td>
					<td> </td>
					<td><span><i></i> 01:00:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Facebook Social City</td>
					<td> </td>
					<td><span><i></i> 01:00:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Finding Free Social Games</td>
					<td> </td>
					<td><span><i></i> 01:00:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Being A Hero In Social Site Game</td>
					<td> </td>
					<td><span><i></i> 00:30:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>The Best Social Site Games</td>
					<td> </td>
					<td><span><i></i> 01:00:00</span></td>
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					<td><i></i></td>
					<td>How to separate learning myths from reality</td>
					<td> </td>
					<td><span><i></i> 00:30:00</span></td>
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					<td colspan="4">Financial Tips for Gamer</td>
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					<td><i></i></td>
					<td>Introduction</td>
					<td> </td>
					<td><span><i></i> 01:00:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Basic Concept of Internet Safety</td>
					<td> </td>
					<td><span><i></i> 01:00:00</span></td>
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					<td><i></i></td>
					<td>A Simple Guide for Buying budget Gaming</td>
					<td> </td>
					<td><span><i></i> 01:00:00</span></td>
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					<td><i></i></td>
					<td>Keep Track of what you Spend</td>
					<td> </td>
					<td><span><i></i> 00:30:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Why Being Naive Can Make Your Fortune</td>
					<td> </td>
					<td><span><i></i> 00:30:00</span></td>
				</tr>
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					<td><i></i></td>
					<td>If you Need Help Get It</td>
					<td> </td>
					<td><span><i></i> 01:00:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Be Careful not to Get Hooked</td>
					<td> </td>
					<td><span><i></i> 01:00:00</span></td>
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					<td><i></i></td>
					<td>How to Handle Difficult Conversations at Work</td>
					<td> </td>
					<td><span><i></i> 00:30:00</span></td>
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					<td><i></i></td>
					<td>The Best Way to Finance Games</td>
					<td> </td>
					<td><span><i></i> 00:15:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Additional Supporting Materials</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Game QA &amp; Testing</td>
					<td> </td>
					<td><span><i></i> 00:00:00</span></td>
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					<td><i></i></td>
					<td>Become A Game Tester</td>
					<td> </td>
					<td><span><i></i> 00:00:00</span></td>
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					<td>Game Testing Changers</td>
					<td> </td>
					<td><span><i></i> 00:00:00</span></td>
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					<td><i></i></td>
					<td>2D Game</td>
					<td> </td>
					<td><span><i></i> 00:00:00</span></td>
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					<td>Beginning Game Development with Python and Pygame</td>
					<td> </td>
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					<td>Game Development XNA GameStudio</td>
					<td> </td>
					<td><span><i></i> 00:00:00</span></td>
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					<td colspan="4">Refer A Friend</td>
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								<tr>
					<td><i></i></td>
					<td>Refer A Friend</td>
					<td> </td>
					<td><span><i></i> 00:00:00</span></td>
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					<td colspan="4">Mock Exam</td>
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					<td><i></i></td>
					<td>Mock Exam- Gaming 5 Course Bundle</td>
					<td> </td>
					<td><span><i></i> 00:30:00</span></td>
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					<td colspan="4">Final Exam</td>
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					<td><i></i></td>
					<td>Final Exam- Gaming 5 Course Bundle</td>
					<td> </td>
					<td><span><i></i> 00:30:00</span></td>
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								<tr>
					<td colspan="4">Order Your Certificate and Transcript</td>
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								<tr>
					<td><i></i></td>
					<td>Order Your Certificates and Transcripts</td>
					<td> </td>
					<td><span><i></i> 00:00:00</span></td>
				</tr>
				</tbody></table>

John Academy

Game Design

Gaming

Online Course Creation

Game Development

Video Game

Gaming 5 Course Bundle

<strong>Welcome to this beginner's level course on Microsoft SQL Servers. Understand the concepts of SQL and learn to create a new database and table to perform various operations on it, with live running queries as examples. Work on hands-on exercises and understand database concepts in a real-world scenario.</strong>
        <p>SQL Server is a relational database management system (RDBMS) developed by Microsoft. SQL Server also allows user-defined composite types (UDTs) to be used. The SQL Server services operate within SQL server instances, allowing people to do machine learning and data analytics.

In this course, you will understand the difference between SQL and NoSQL. You will query SQL and learn about built-in SQL functions. You will create and modify databases and tables using the CREATE DATABASE and CREATE TABLE statements. You will create, select, and modify records and create constraints in SQL. You will advance to create indexes, drop tables, and databases in SQL. You will learn about operators (AND, OR, NOT, LIKE, BETWEEN, IN, LIKE), functions, statements, and constraints in SQL. You will look at stored procedures and aliases, and learn to back up databases in SQL. You will use the WHERE clause to query and learn about the SELECT and DISTINCT functions. You will arrange data using the ORDER BY keyword and ASC and DESC keywords.

After completing the course, you will thoroughly understand SQL's features and components. You will create complex databases and maintain existing databases. Finally, you will acquire complex SQL query capabilities and write complex queries.

All resources are available at: https://github.com/PacktPublishing/SQL-Server-Course-for-Beginners-with-100-examples</p>
        <h2>What You Will Learn</h2><p>Create databases and tables from the start<br>Learn to handle MySQL queries<br>Learn to query SQL to manipulate records in tables<br>Explore functions, statements, and constraints in SQL<br>Create and maintain complex databases and table structures<br>Write complex query statements for maximum data optimization</p>
        <h2>Audience</h2><p>This course delivers a substantial learning experience for database creators, web developers, application developers, and programmers who must operate with SQL and database structures. Database analysts and administrators who are looking to advance/refresh their knowledge skillsets can benefit from this course. The course has no additional prerequisites besides basic computer use knowledge.</p>
        <h2>Approach</h2><p>Well-structured and high-quality video lectures provide step-by-step explanations in a tutorial-like environment, making it easily understandable for beginners about a new database, tables, and their features with live running queries as examples. The course also provides carefully created quizzes to refresh and hone your SQL skillsets.</p>
        <h2>Key Features</h2><p>Understand the SQL query process and the role of databases in real-world applications * Create new databases and tables and perform operations to manipulate records using SQL queries * Master SQL querying and write complex query statements to enhance your understanding of MySQL</p>
        <h2>Github Repo</h2><p>https://github.com/PacktPublishing/SQL-Server-Course-for-Beginners-with-100-examples</p>
        <h2>About the Author</h2><h3>Amit Diwan</h3><p>Studyopedia was founded by Amit Diwan in 2018 after working for Tutorialspoint , IIT, IASRI, Sitepoint, DU, and C# Corner. Studyopedia sells courses on Udemy, Tutorialspoint, Geeksforgeeks, and Skillshare, providing video courses to master various technologies and programming languages, databases, frameworks, Python, data science, machine learning, Java, Android, C/C++, HTML5, Bootstrap, JavaScript, jQuery, PHP, CSS, WordPress, Drupal, Joomla, Magento, osCommerce, OpenCart, PrestaShop, and other disciplines. Studyopedia delivers high-quality video courses to millions of students and professionals enrolled through their website on multiple programming languages and technologies.</p>
        <h2>Course Outline</h2><h4>1. SQL Introduction</h4><p>This section focuses on a cursory introduction to SQL, the benefits of using SQL, and also the features of SQL.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction</p><p style='margin: 0'>Learn what SQL is and how it is based on RDBMS. We will discuss the features and Microsoft SQL Server and SQL Server Management Studio.</p></td></tr><tr><td style='padding: 15px;'><p>2. SQL Versus NoSQL</p><p style='margin: 0'>Learn the difference between SQL and NoSQL. We have considered the example of MySQL (SQL-based) and MongoDB (NoSQL-based) to understand the concept.</p></td></tr></tbody></table><br><h4>2. SQL Installation and Setup</h4><p>This section focuses on the installation and setup process of SQL server over Windows 10 and 11 and also to fix installation errors.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Install SQL Server on Windows 10</p><p style='margin: 0'>Learn how to download and install Microsoft SQL Server on Windows 10. We will also install SQL Server Management Studio (SSMS).</p></td></tr><tr><td style='padding: 15px;'><p>2. Install SQL Server on Windows 11</p><p style='margin: 0'>Learn how to download and install Microsoft SQL Server on Windows 11. We will also install SQL Server Management Studio (SSMS).</p></td></tr><tr><td style='padding: 15px;'><p>3. Fix SQL Server Installation Error</p><p style='margin: 0'>While installing SQL Server, you may get the following error: Learn how to fix the following error while installing Microsoft SQL Server 2019: A required file could not be downloaded. This could mean the version of the installer is no longer supported.</p></td></tr></tbody></table><br><h4>3. Create and Insert</h4><p>This section focuses over creating a database and table and adding records or populating the table and database.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Create a Database</p><p style='margin: 0'>Learn how to create a new database in SQL Server. The CREATE DATABASE statement is used to create a new SQL server database.</p></td></tr><tr><td style='padding: 15px;'><p>2. Create a Table</p><p style='margin: 0'>Learn how to create a new table with SQL Server. The CREATE TABLE statement is used to create a new table in SQL Server.</p></td></tr><tr><td style='padding: 15px;'><p>3. Insert Records</p><p style='margin: 0'>Use the INSERT INTO Statement in SQL to learn how to insert records in a table.</p></td></tr></tbody></table><br><h4>4. Select Records in SQL</h4><p>This section delves over records in SQL, how to select them, how to select distinct elements, and use the where clause to segregate records.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. SELECT Statement in SQL</p><p style='margin: 0'>Learn how to select records in SQL using the SELECT statement. We will also see how to choose multiple columns in a single query.</p></td></tr><tr><td style='padding: 15px;'><p>2. SELECT DISTINCT Statement in SQL</p><p style='margin: 0'>Learn how to select and return only distinct values from a table using the SQL SELECT DISTINCT statement.</p></td></tr><tr><td style='padding: 15px;'><p>3. WHERE Clause in SQL</p><p style='margin: 0'>Learn how to work with the WHERE clause in SQL. WHERE clause filters records based on condition(s).</p></td></tr></tbody></table><br><h4>5. Order Records in SQL</h4><p>This section focuses on the order records function of SQL using the ORDER BY keyword.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. ORDER BY Keyword in SQL</p><p style='margin: 0'>Learn how to order records in SQL using the ORDER BY keyword. The default sorts in ascending order. We will see examples of both ASC and DESC keywords as well.</p></td></tr></tbody></table><br><h4>6. Operators in SQL</h4><p>This section focuses on the arithmetic and logical operators used in SQL, including AND, OR, NOT, IN, BETWEEN, and LIKE.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. AND Operator</p><p style='margin: 0'>Learn how to work with the AND operator in SQL to display records only if both conditions are TRUE. These two conditions should be separated by the AND operator.</p></td></tr><tr><td style='padding: 15px;'><p>2. OR Operator</p><p style='margin: 0'>Learn how to work with the OR operator in SQL to display records only if one condition is TRUE. The OR operator should separate these two conditions.</p></td></tr><tr><td style='padding: 15px;'><p>3. NOT Operator</p><p style='margin: 0'>Learn how to work with the NOT operator in SQL to display records only if the condition isn't met, that is, FALSE.</p></td></tr><tr><td style='padding: 15px;'><p>4. IN Operator</p><p style='margin: 0'>Learn how to implement the IN operator in SQL. We will check whether a specific value matches.</p></td></tr><tr><td style='padding: 15px;'><p>5. BETWEEN Operator</p><p style='margin: 0'>Learn how to implement the BETWEEN operator in SQL. We will find values in a range.</p></td></tr><tr><td style='padding: 15px;'><p>6. LIKE Operator</p><p style='margin: 0'>Learn how to implement the LIKE operator in SQL. We will find values based on a specific pattern using percentages and underscore.</p></td></tr></tbody></table><br><h4>7. Built-In Functions in SQL</h4><p>This section focuses on the built-in functions in SQL and helps us understand maximum, minimum, sum, average, and count functions in detail.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. MAX() Function</p><p style='margin: 0'>Learn how to implement the MAX() function in SQL. We will find the maximum of column values.</p></td></tr><tr><td style='padding: 15px;'><p>2. MIN() Function</p><p style='margin: 0'>Learn how to implement the MIN() function in SQL. We will find the minimum of column values.</p></td></tr><tr><td style='padding: 15px;'><p>3. SUM() Function</p><p style='margin: 0'>Learn how to implement the SUM() function in SQL. We will find the sum of column values.</p></td></tr><tr><td style='padding: 15px;'><p>4. AVG() Function</p><p style='margin: 0'>Learn how to implement the AVG() function in SQL. We will find the average of column values.</p></td></tr><tr><td style='padding: 15px;'><p>5. COUNT() Function</p><p style='margin: 0'>Learn how to implement the COUNT() function in SQL. We will find the count of the number of rows.</p></td></tr></tbody></table><br><h4>8. Constraints in SQL</h4><p>This section focuses on constraints in SQL and the different types of constraints that can be used to manipulate data.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. NOT NULL Constraint</p><p style='margin: 0'>Learn how to work with the NOT NULL constraint in SQL to enforce a column with values, that is, not null. Remember, as columns can have NULL by default, we use the NOT NULL constraint to enforce a column NOT to accept values.</p></td></tr><tr><td style='padding: 15px;'><p>2. UNIQUE Constraint</p><p style='margin: 0'>Learn how to work with the UNIQUE constraint in SQL to uniquely identify each record in a database table. It enforces the uniqueness of column values.</p></td></tr><tr><td style='padding: 15px;'><p>3. PRIMARY KEY Constraint</p><p style='margin: 0'>Learn how to work with the PRIMARY KEY constraint in SQL. A PRIMARY KEY uniquely identifies each record. Not a Primary Key column can never have NULL values.</p></td></tr><tr><td style='padding: 15px;'><p>4. FOREIGN KEY Constraint</p><p style='margin: 0'>Learn how to work with the FOREIGN KEY constraint in SQL. A FOREIGN KEY is a field in one table that refers to the PRIMARY KEY in another. A child table is a table with a foreign key.</p></td></tr><tr><td style='padding: 15px;'><p>5. CHECK Constraint</p><p style='margin: 0'>Learn how to work with the CHECK constraint in SQL to allow only specific values for a column. You can limit the value range set in a column, for example, Age > 18, Marks > 75, and so on.</p></td></tr></tbody></table><br><h4>9. Alter and Update in SQL</h4><p>This section focuses on the ALTER TABLE and UPDATE TABLE functions in SQL that allow us to manipulate records in a table.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. ALTER TABLE Statement</p><p style='margin: 0'>Learn how to work with the ALTER TABLE in SQL to add or delete columns in the existing table. To add a column to an existing table, use the ALTER TABLE with ADD command. To delete a column from an existing table, use the ALTER TABLE with DROP COLUMN.</p></td></tr><tr><td style='padding: 15px;'><p>2. UPDATE Statement</p><p style='margin: 0'>Learn how to work with the UPDATE statement in SQL to update existing records in a table. Use the WHERE clause with the UPDATE statement to avoid updating all records in the table.</p></td></tr><tr><td style='padding: 15px;'><p>3. Aliases</p><p style='margin: 0'>Learn how to work with Aliases in SQL to give a temporary name to a table or column. The AS keyword creates an alias, making column names more readable. Remember that the alias's existence expires when that query's duration ends.</p></td></tr></tbody></table><br><h4>10. Advanced SQL</h4><p>This advanced section delves deep into stored procedures, indexes, and other advanced statements. We will also look at backing up a database and removing tables from a database.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Stored Procedures in SQL</p><p style='margin: 0'>Use the CREATE PROCEDURE statement to learn how to work with stored procedures in SQL. If you want to reuse a query again and again, then create a procedure and save the query in it. Call the procedure whenever you need that same query. Therefore, stored procedures work like a function.</p></td></tr><tr><td style='padding: 15px;'><p>2. Indexes in SQL</p><p style='margin: 0'>Learn how to work with the CREATE INDEX statement in SQL to create indexes in a table. Indexes retrieve data quickly from the database. We will also see how to delete indexes using the DROP INDEX statement.</p></td></tr><tr><td style='padding: 15px;'><p>3. SELECT INTO Statement in SQL</p><p style='margin: 0'>Learn how to work with the SELECT INTO statement in SQL to create a backup copy of your table to a new table. The new table will have the same type and columns as in the first.</p></td></tr><tr><td style='padding: 15px;'><p>4. SELECT TOP Clause in SQL</p><p style='margin: 0'>Learn how to implement the SELECT TOP statement in SQL. We will work with the SELECT TOP PERCENT statement as well.</p></td></tr><tr><td style='padding: 15px;'><p>5. Back Up a Database in SQL</p><p style='margin: 0'>Learn how to back up a database in SQL. We will back up the database in a local directory with the extension .bak.</p></td></tr><tr><td style='padding: 15px;'><p>6. SQL Views</p><p style='margin: 0'>Learn how to work with Views in SQL. A view is a virtual table created from the actual table, displaying the current result set. We will use the CREATE VIEW and DROP VIEW statements to develop and delete views.</p></td></tr><tr><td style='padding: 15px;'><p>7. Drop a Table in SQL</p><p style='margin: 0'>Learn how to drop a table in SQL. Dropping will delete all the records of the table. It will also obliterate the existence of the table.</p></td></tr></tbody></table>

Database Programming

SQL Server

MySQL

Welcome to this beginner's level course on Microsoft SQL Servers. Understand the concepts of SQL and learn to create a new database and table to perform various operations on it, with live running queries as examples. Work on hands-on exercises and understand database concepts in a real-world scenario.

SQL Server Course for Beginners with 100+ examples

<strong>Pre-process and Analyze Satellite Remote Sensing Data with Free Software</strong>
        <p>Enroll in my latest course on how to learn all about Basic Satellite Remote Sensing or perhaps you have prior experiences in GIS or tools like R and QGIS? You don't want to spend 100s and 1000s of dollars on buying commercial software for imagery analysis? The next step for you is to gain proficiency in satellite remote sensing data analysis.

This course is hands-on training with real remote sensing data with open source tools! This course provides a foundation to carry out practical, real-life remote sensing analysis tasks in popular and free software frameworks with real spatial data. By taking this course, you are taking an important step forward in your GIS journey to become an expert in geospatial analysis. Why Should You Take My Course? The author is an Oxford University MPhil (Geography and Environment), graduate. She also completed a Ph.D. at Cambridge University (Tropical Ecology and Conservation). She has several years of experience in analyzing real-life spatial remote sensing data from different sources and producing publications for international peer-reviewed journals. 

In this course, actual satellite remote sensing data such as Landsat from USGS and radar data from JAXA will be used to give practical hands-on experience of working with remote sensing and understanding what kind of questions remote sensing can help us answer. This course will ensure you learn and put remote sensing data analysis into practice today and increase your proficiency in geospatial analysis. Remote sensing software tools are very expensive, and their cost can run into thousands of dollars. Instead of shelling out so much money or procuring pirated copies (which puts you at risk of prosecution), you will learn to carry out some of the most important and common remote sensing analysis tasks using a number of popular, open-source GIS tools such as R, QGIS, GRASS, and ESA-SNAP.  All of which are in great demand in the geospatial sector and improving your skills in these is a plus for you. You will also learn about the different sources of remote sensing data there are and how to obtain these free of charge and process them using free software.

All the code and supporting files for this course are available at -
https://github.com/PacktPublishing/Satellite-Remote-Sensing-Data-Bootcamp-with-Opensource-Tools</p>
        <h2>What You Will Learn</h2><p>Download different types of satellite remote sensing data for free<br>Have a thorough knowledge of remote sensing- theoretical concepts and applications<br>Implement pre-processing techniques using R and QGIS<br>Carry out the unsupervised classification of satellite remote sensing data<br>Carry out the supervised classification of satellite remote sensing data<br>Implement machine learning algorithms on satellite remote sensing data in R<br>Carry out habitat suitability mapping using remote sensing and machine learning<br>Use other freely available software tools such as Google Earth Engine and SNAP for RS data analysis</p>
        <h2>Audience</h2><p>This course is for people with prior experience of working spatial data such as GIS analysts, Ecologists, Forestry and Conservation Practioners, Geographers, and Geologists.</p>
        <h2>Approach</h2><p>This is an introductory course, i.e. we will focus on learning the most important and widely encountered remote sensing data processing and analyzing tasks in R, QGIS, GRASS and ESA-SNAP.</p>
        <h2>Key Features</h2><p>A good starter course to explain the fundamentals & properly understand the applications of remote sensing * Short lectures and practicals which are good to ensure the attention of the audience is still there.</p>
        <h2>Github Repo</h2><p>https://github.com/packtpublishing/satellite-remote-sensing-data-bootcamp-with-opensource-tools</p>
        <h2>About the Author</h2><h3>Minerva Singh</h3><p>Minerva Singh is a PhD graduate from Cambridge University where she specialized in Tropical Ecology. She is also a part-time Data Scientist. As part of her research, she must carry out extensive data analysis, including spatial data analysis. For this purpose, she prefers to use a combination of freeware tools: R, QGIS, and Python. She does most of her spatial data analysis work using R and QGIS. Apart from being free, these are very powerful tools for data visualization, processing, and analysis. She also holds an MPhil degree in Geography and Environment from Oxford University. She has honed her statistical and data analysis skills through several MOOCs, including The Analytics Edge and Statistical. In addition to spatial data analysis, she is also proficient in statistical analysis, machine learning, and data mining.</p>
        <h2>Course Outline</h2><h4>1. Introduction to Satellite Remote Sensing Data Analysis</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction to the Course and Instructor</p><p style='margin: 0'>Introduction to Satellite Remote Sensing Data Analysis: Introduction to the Course and Instructor</p></td></tr><tr><td style='padding: 15px;'><p>2. What is Remote Sensing?</p><p style='margin: 0'>Introduction to Satellite Remote Sensing Data Analysis: What is Remote Sensing?</p></td></tr><tr><td style='padding: 15px;'><p>3. Different Types of Remote Sensing Data</p><p style='margin: 0'>Introduction to Satellite Remote Sensing Data Analysis: Different Types of Remote Sensing Data</p></td></tr><tr><td style='padding: 15px;'><p>4. Different Tools for Working with Remote Sensing-Start with R and QGIS</p><p style='margin: 0'>Introduction to Satellite Remote Sensing Data Analysis: Different Tools for Working with Remote Sensing-Start with R and QGIS</p></td></tr><tr><td style='padding: 15px;'><p>5. Get Started with SNAP Toolbox-Brief Introduction</p><p style='margin: 0'>Introduction to Satellite Remote Sensing Data Analysis: Get Started with SNAP Toolbox-Brief Introduction</p></td></tr><tr><td style='padding: 15px;'><p>6. Get Started with GRASS GIS-Brief Introduction</p><p style='margin: 0'>Introduction to Satellite Remote Sensing Data Analysis: Get Started with GRASS GIS-Brief Introduction</p></td></tr><tr><td style='padding: 15px;'><p>7. Conclusions to Section 1</p><p style='margin: 0'>Introduction to Satellite Remote Sensing Data Analysis: Conclusions to Section 1</p></td></tr></tbody></table><br><h4>2. Introduction to Optical Remote Sensing Data</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Principles Behind Collection of Optical Remote Sensing Data</p><p style='margin: 0'>Introduction to Optical Remote Sensing Data: Principles Behind Collection of Optical Remote Sensing Data</p></td></tr><tr><td style='padding: 15px;'><p>2. Different Types of Optical Remote Sensing Data</p><p style='margin: 0'>Introduction to Optical Remote Sensing Data: Different Types of Optical Remote Sensing Data</p></td></tr><tr><td style='padding: 15px;'><p>3. Downloading and Viewing Landsat Data</p><p style='margin: 0'>Introduction to Optical Remote Sensing Data: Downloading and Viewing Landsat Data</p></td></tr><tr><td style='padding: 15px;'><p>4. Different Landsat Sensors</p><p style='margin: 0'>Introduction to Optical Remote Sensing Data: Different Landsat Sensors</p></td></tr><tr><td style='padding: 15px;'><p>5. Downloading and Viewing Optical Data via QGIS</p><p style='margin: 0'>Introduction to Optical Remote Sensing Data: Downloading and Viewing Optical Data via QGIS</p></td></tr><tr><td style='padding: 15px;'><p>6. Conclusions to Section 2</p><p style='margin: 0'>Introduction to Optical Remote Sensing Data: Conclusions to Section 2</p></td></tr></tbody></table><br><h4>3. Pre-Processing Optical Data</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Why is Pre-Processing Needed for Optical Data?</p><p style='margin: 0'>Pre-Processing Optical Data: Why is Pre-Processing Needed for Optical Data?</p></td></tr><tr><td style='padding: 15px;'><p>2. Implementing Atmospheric Correction on Landsat Data in R</p><p style='margin: 0'>Pre-Processing Optical Data: Implementing Atmospheric Correction on Landsat Data in R</p></td></tr><tr><td style='padding: 15px;'><p>3. QGIS For Pre-Processing Landsat Data: Semi-Automatic Classification Plugin</p><p style='margin: 0'>Pre-Processing Optical Data: QGIS For Pre-Processing Landsat Data: Semi-Automatic Classification Plugin</p></td></tr><tr><td style='padding: 15px;'><p>4. Atmospherically Corrected Outputs from QGIS</p><p style='margin: 0'>Pre-Processing Optical Data: Atmospherically Corrected Outputs from QGIS</p></td></tr><tr><td style='padding: 15px;'><p>5. What Can Pre-Processed Satellite Data Be Used For?</p><p style='margin: 0'>Pre-Processing Optical Data: What Can Pre-Processed Satellite Data Be Used For?</p></td></tr><tr><td style='padding: 15px;'><p>6. Conclusions to Section 3</p><p style='margin: 0'>Pre-Processing Optical Data: Conclusions to Section 3</p></td></tr></tbody></table><br><h4>4. The Many Uses of Optical Data</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Stacking and Unstacking Bands in QGIS</p><p style='margin: 0'>The Many Uses of Optical Data: Stacking and Unstacking Bands in QGIS</p></td></tr><tr><td style='padding: 15px;'><p>2. Band Maths in R and QGIS</p><p style='margin: 0'>The Many Uses of Optical Data: Band Maths in R and QGIS</p></td></tr><tr><td style='padding: 15px;'><p>3. Texture Indices-Theory</p><p style='margin: 0'>The Many Uses of Optical Data: Texture Indices-Theory</p></td></tr><tr><td style='padding: 15px;'><p>4. Texture Indices-GRASS GIS</p><p style='margin: 0'>The Many Uses of Optical Data: Texture Indices-GRASS GIS</p></td></tr><tr><td style='padding: 15px;'><p>5. Texture Indices-ESA SNAP</p><p style='margin: 0'>The Many Uses of Optical Data: Texture Indices-ESA SNAP</p></td></tr><tr><td style='padding: 15px;'><p>6. Tasseled Cap Transformations-theory</p><p style='margin: 0'>The Many Uses of Optical Data: Tasseled Cap Transformations-theory</p></td></tr><tr><td style='padding: 15px;'><p>7. Tasseled Cap Transformations-GRASS GIS</p><p style='margin: 0'>The Many Uses of Optical Data: Tasseled Cap Transformations-GRASS GIS</p></td></tr><tr><td style='padding: 15px;'><p>8. Vegetation Indices in GRASS GIS</p><p style='margin: 0'>The Many Uses of Optical Data: Vegetation Indices in GRASS GIS</p></td></tr><tr><td style='padding: 15px;'><p>9. Vegetation Indices using RStoolbox</p><p style='margin: 0'>The Many Uses of Optical Data: Vegetation Indices using RStoolbox</p></td></tr><tr><td style='padding: 15px;'><p>10. Dimension Reduction-theory</p><p style='margin: 0'>The Many Uses of Optical Data: Dimension Reduction-theory</p></td></tr><tr><td style='padding: 15px;'><p>11. Dimension Reduction-QGIS</p><p style='margin: 0'>The Many Uses of Optical Data: Dimension Reduction-QGIS</p></td></tr><tr><td style='padding: 15px;'><p>12. Dimension Reduction-GRASS GIS</p><p style='margin: 0'>The Many Uses of Optical Data: Dimension Reduction-GRASS GIS</p></td></tr><tr><td style='padding: 15px;'><p>13. Conclusion to Section 4</p><p style='margin: 0'>The Many Uses of Optical Data: Conclusion to Section 4</p></td></tr></tbody></table><br><h4>5. Classification of Remote Sensing Satellite Data</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Theory of Unsupervised Classification</p><p style='margin: 0'>Classification of Remote Sensing Satellite Data: Theory of Unsupervised Classification</p></td></tr><tr><td style='padding: 15px;'><p>2. Unsupervised Classification-ESA SNAP</p><p style='margin: 0'>Classification of Remote Sensing Satellite Data: Unsupervised Classification-ESA SNAP</p></td></tr><tr><td style='padding: 15px;'><p>3. Theory of Supervised Classification</p><p style='margin: 0'>Classification of Remote Sensing Satellite Data: Theory of Supervised Classification</p></td></tr><tr><td style='padding: 15px;'><p>4. Supervised Classification in QGIS: Preliminary Steps</p><p style='margin: 0'>Classification of Remote Sensing Satellite Data: Supervised Classification in QGIS: Preliminary Steps</p></td></tr><tr><td style='padding: 15px;'><p>5. Classification and Post Classification Accuracy in QGIS</p><p style='margin: 0'>Classification of Remote Sensing Satellite Data: Classification and Post Classification Accuracy in QGIS</p></td></tr><tr><td style='padding: 15px;'><p>6. Machine Learning Theory</p><p style='margin: 0'>Classification of Remote Sensing Satellite Data: Machine Learning Theory</p></td></tr><tr><td style='padding: 15px;'><p>7. Create Training Data in QGIS</p><p style='margin: 0'>Classification of Remote Sensing Satellite Data: Create Training Data in QGIS</p></td></tr><tr><td style='padding: 15px;'><p>8. Apply Machine Learning Techniques on Satellite Data</p><p style='margin: 0'>Classification of Remote Sensing Satellite Data: Apply Machine Learning Techniques on Satellite Data</p></td></tr><tr><td style='padding: 15px;'><p>9. Conclusion to Section 5</p><p style='margin: 0'>Classification of Remote Sensing Satellite Data: Conclusion to Section 5</p></td></tr></tbody></table><br><h4>6. Introduction to Active Remote Sensing Data: Synthetic Aperture Radar</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Why Use Active Remote Sensing Data?</p><p style='margin: 0'>Introduction to Active Remote Sensing Data: Synthetic Aperture Radar: Why Use Active Remote Sensing Data?</p></td></tr><tr><td style='padding: 15px;'><p>2. Obtain ALOS PALSAR Data</p><p style='margin: 0'>Introduction to Active Remote Sensing Data: Synthetic Aperture Radar: Obtain ALOS PALSAR Data</p></td></tr><tr><td style='padding: 15px;'><p>3. Pre-processing of ALOS PALSAR data</p><p style='margin: 0'>Introduction to Active Remote Sensing Data: Synthetic Aperture Radar: Pre-processing of ALOS PALSAR data</p></td></tr><tr><td style='padding: 15px;'><p>4. Filtering for Speckles</p><p style='margin: 0'>Introduction to Active Remote Sensing Data: Synthetic Aperture Radar: Filtering for Speckles</p></td></tr><tr><td style='padding: 15px;'><p>5. Obtain back-scatter values from ALOS PALSAR data</p><p style='margin: 0'>Introduction to Active Remote Sensing Data: Synthetic Aperture Radar: Obtain back-scatter values from ALOS PALSAR data</p></td></tr></tbody></table>

Web Development

Pre-process and Analyze Satellite Remote Sensing Data with Free Software

Satellite Remote Sensing Data Bootcamp With Opensource Tools

<strong>Learn JavaScript from Scratch: JavaScript for Everyone is a hands-on course that teaches the ins and outs of modern JavaScript. It is the perfect course for anyone who wants to learn the programming language from scratch and wants to develop engaging, interactive websites that leverage all the latest features JavaScript comes with.</strong>
        <p>Despite the deluge of new coding languages over the years, JavaScript continues to dominate the web. The language is a staple in most of the front-ends; if not vanilla JavaScript, you won't be surprised to find one of its derivatives on the next website you visit. This ubiquity makes JavaScript a sought-after skill. This course is designed to teach you that skill from scratch.

You'll begin by learning how to set up your coding playground and then gain some familiarity with the JavaScript syntax. Once you've gotten your hands dirty, you'll discover how to store data in variables, comment out your code, and do more with your variables by learning about operators.

Next, you'll learn about data structures and conditional statements, further shoring up your JavaScript skills. By learning about the Document Object Model (The DOM), you will be able to change the elements of a webpage and add interactivity to it. You'll also learn to work with strings and arrays, and then, to make your code concise, learn how to write your own functions. Toward the end of the course, you'll work on a final project wherein you'll get to use all these skills together.

By completing this course, not only will you have a solid understanding of modern JavaScript language, you'll also be able to use it to create engaging, interactive webpages.</p>
        <h2>What You Will Learn</h2><p>Learn about different variable types, including let and const<br>Discover how to do more with your variables using operators<br>Gain an in-depth understanding of data structures in JavaScript<br>Learn in detail the structure of the Document Object Model (The DOM)<br>Using the knowledge of the DOM, learn to modify elements of an HTML page<br>Discover how to manipulate strings and how to work with numbers<br>Learn how to store and work with multiple elements through arrays<br>Make your code concise by learning how to write your own functions</p>
        <h2>Audience</h2><p>If you're someone who has never coded in JavaScript but always wanted to, this course is for you. Since you'll be making interactive webpages, a rudimentary knowledge of HTML CSS would be beneficial (though it's not a hard requirement).</p>
        <h2>Approach</h2><p>Whether or not you have any code editing software installed on your system, you'll be writing JavaScript code from the very first lecture. The course focuses on teaching you the key concepts of modern JavaScript through hands-on practice. In the end, you'll work on an interactive project where you'll be making use of all the concepts you learned in the course so far.</p>
        <h2>Key Features</h2><p>Learn JavaScript fundamentals, especially if you've never written JavaScript code before * Learn all the modern JavaScript concepts such as template literals, let, const, and more * Put everything you learned to test by building an interactive project at the end of the course</p>
        
        <h2>About the Author</h2><h3>Kalob Taulien</h3><p>Kalob Taulien is a professional web developer who has been developing websites and working with start-ups since 1999. Since many years, he has been writing codes in Python and Django. He is in the core Wagtail CMS team and one of the core leaders in Wagtail-based education. The passion to learn and to share his knowledge by teaching and helping others is something that drives him constantly. His ability to turn complex programming concepts into easy-to-understand bits of knowledge has been called his 'superpower'. Throughout the years, he has built numerous websites. He even provides one-on-one coaching and start-up consulting to new organizations.</p>
        <h2>Course Outline</h2><h4>1. Introduction</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction</p><p style='margin: 0'>This video introduces the course.</p></td></tr></tbody></table><br><h4>2. Getting Started</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Getting Your Hands Dirty</p><p style='margin: 0'>In this video, you'll start writing code in JavaScript.</p></td></tr><tr><td style='padding: 15px;'><p>2. What is JavaScript?</p><p style='margin: 0'>In this video, you'll learn what exactly JavaScript is and where it is used.</p></td></tr><tr><td style='padding: 15px;'><p>3. You Need a Text Editor</p><p style='margin: 0'>In this video, you'll get set up with a text editor.</p></td></tr><tr><td style='padding: 15px;'><p>4. JavaScript Syntax</p><p style='margin: 0'>In this video, you'll get an overview of JavaScript syntax.</p></td></tr></tbody></table><br><h4>3. Coding with JavaScript</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Console Logging</p><p style='margin: 0'>In this video, you'll learn what console logging is and why you need to use it.</p></td></tr><tr><td style='padding: 15px;'><p>2. Debugging External Files</p><p style='margin: 0'>In this video, you'll learn how to debug external files.</p></td></tr><tr><td style='padding: 15px;'><p>3. Storing Data in Variables</p><p style='margin: 0'>In this video, you'll learn how to store data in variables.</p></td></tr><tr><td style='padding: 15px;'><p>4. Let and Const Variable Types</p><p style='margin: 0'>In this video, you'll learn all about let and const.</p></td></tr><tr><td style='padding: 15px;'><p>5. Coding Comments</p><p style='margin: 0'>In this video, you'll learn how and why you should write code comments.</p></td></tr><tr><td style='padding: 15px;'><p>6. JavaScript Operators</p><p style='margin: 0'>In this video, you'll learn the different types of operators in JavaScript.</p></td></tr><tr><td style='padding: 15px;'><p>7. Data Structures</p><p style='margin: 0'>In this video, you'll learn the importance of data structures.</p></td></tr><tr><td style='padding: 15px;'><p>8. Conditional Statements</p><p style='margin: 0'>In this video, you'll learn what conditional statements are.</p></td></tr><tr><td style='padding: 15px;'><p>9. The Document Object Model (DOM)</p><p style='margin: 0'>In this video, you'll get an overview of the DOM.</p></td></tr><tr><td style='padding: 15px;'><p>10. Selecting Elements by Their IDs</p><p style='margin: 0'>In this video, you'll learn how to select elements by their IDS and what it does in the DOM.</p></td></tr><tr><td style='padding: 15px;'><p>11. JavaScript Objects</p><p style='margin: 0'>In this video, you'll learn what objects are in JavaScript and why they are useful.</p></td></tr><tr><td style='padding: 15px;'><p>12. String Methods</p><p style='margin: 0'>In this video, you'll learn how to work with string methods.</p></td></tr><tr><td style='padding: 15px;'><p>13. Demystifying Data Types</p><p style='margin: 0'>In this video, you'll learn how to identify the different data types in a code.</p></td></tr><tr><td style='padding: 15px;'><p>14. Casting Data Types</p><p style='margin: 0'>In this video, you'll learn how to convert data types from one type to another.</p></td></tr><tr><td style='padding: 15px;'><p>15. String Concatenation</p><p style='margin: 0'>In this video, you'll learn to mix and merge variable types together.</p></td></tr><tr><td style='padding: 15px;'><p>16. JavaScript Numbers</p><p style='margin: 0'>In this video, you'll learn how to work with numbers in JavaScript.</p></td></tr><tr><td style='padding: 15px;'><p>17. JavaScript Arrays</p><p style='margin: 0'>In this video, you'll learn to work with lists/arrays in JavaScript.</p></td></tr><tr><td style='padding: 15px;'><p>18. Array Iteration</p><p style='margin: 0'>In this video, you'll learn to loop over arrays.</p></td></tr><tr><td style='padding: 15px;'><p>19. Selecting Multiple DOM Nodes</p><p style='margin: 0'>In this video, you'll learn what happens when you select multiple DOM nodes.</p></td></tr><tr><td style='padding: 15px;'><p>20. Functions: the DRY (Don't Repeat Yourself) Principle</p><p style='margin: 0'>In this video, you'll learn the effectiveness of the DRY principle.</p></td></tr><tr><td style='padding: 15px;'><p>21. Functions: Reusing Code</p><p style='margin: 0'>This video builds upon the DRY principle and you'll learn how to write larger pieces of code.</p></td></tr><tr><td style='padding: 15px;'><p>22. Functions: the Rest Operator</p><p style='margin: 0'>In this video, you'll learn about the Rest operator, which is relatively new in JavaScript.</p></td></tr><tr><td style='padding: 15px;'><p>23. Objects with Functions</p><p style='margin: 0'>In this video, you'll learn how to create objects with the help of functions.</p></td></tr><tr><td style='padding: 15px;'><p>24. Final Project</p><p style='margin: 0'>In this video, you'll get a brief of the project you will work on.</p></td></tr></tbody></table><br><h4>4. Section Summary</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Summary</p><p style='margin: 0'>This video gives a summary of the course covered so far.</p></td></tr></tbody></table><br><h4>5. JavaScript 201 - Getting Started</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. introduction</p><p style='margin: 0'>This video gives an introduction to the next sections.</p></td></tr><tr><td style='padding: 15px;'><p>2. Styling Your Code</p><p style='margin: 0'>In this video, you'll learn how to make your code look clean.</p></td></tr><tr><td style='padding: 15px;'><p>3. Waiting for the Page to Load</p><p style='margin: 0'>In this video, you'll learn how to make sure that everything in your page is loaded using JavaScript.</p></td></tr><tr><td style='padding: 15px;'><p>4. When the Page is Refreshed</p><p style='margin: 0'>In this video, you'll learn what to do when you hit the refresh button on a webpage.</p></td></tr></tbody></table><br><h4>6. Intermediate JavaScript</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Strict Comparisons</p><p style='margin: 0'>In this video, you'll learn how to use comparisons in JavaScript.</p></td></tr><tr><td style='padding: 15px;'><p>2. JavaScript Scope</p><p style='margin: 0'>In this video, you'll learn about scope in JavaScript.</p></td></tr><tr><td style='padding: 15px;'><p>3. JavaScript Hoisting</p><p style='margin: 0'>In this video, you'll learn a unique feature in JavaScript.</p></td></tr><tr><td style='padding: 15px;'><p>4. JavaScript Closures</p><p style='margin: 0'>In this video, you'll learn what closures are in JavaScript.</p></td></tr><tr><td style='padding: 15px;'><p>5. Callback Functions</p><p style='margin: 0'>In this video, you'll learn about callback functions.</p></td></tr><tr><td style='padding: 15px;'><p>6. Strict Mode</p><p style='margin: 0'>In this video, you'll learn what strict mode is and how it is useful.</p></td></tr><tr><td style='padding: 15px;'><p>7. Timeout and Intervals</p><p style='margin: 0'>In this video, you'll get introduced to timeout and intervals in JavaScript.</p></td></tr><tr><td style='padding: 15px;'><p>8. While Loops</p><p style='margin: 0'>In this video, you'll learn to work with while loops in JavaScript.</p></td></tr><tr><td style='padding: 15px;'><p>9. Date Formatting</p><p style='margin: 0'>In this video, you'll learn the importance of date formatting in JavaScript.</p></td></tr><tr><td style='padding: 15px;'><p>10. Destructuring Arrays and Objects</p><p style='margin: 0'>In this video, you'll learn a modern JavaScript technique.</p></td></tr><tr><td style='padding: 15px;'><p>11. Deleting Object Properties</p><p style='margin: 0'>In this video, you'll learn what it means to delete object properties.</p></td></tr><tr><td style='padding: 15px;'><p>12. JavaScript Math</p><p style='margin: 0'>In this video, you'll learn about the math module in JavaScript.</p></td></tr></tbody></table><br><h4>7. Mini-Project</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Random Numbers</p><p style='margin: 0'>In this video, you'll learn about 'math.random' in the math module.</p></td></tr><tr><td style='padding: 15px;'><p>2. Random Number Guessing Game</p><p style='margin: 0'>This video teaches you to develop a short game on guessing a random number.</p></td></tr></tbody></table><br><h4>8. Professional JavaScript</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Try, Catch, and Finally</p><p style='margin: 0'>In this video, you'll learn how to use try, catch, and finally in JavaScript.</p></td></tr><tr><td style='padding: 15px;'><p>2. The 'This' Keyword</p><p style='margin: 0'>In this video, you'll learn what 'this' represents.</p></td></tr><tr><td style='padding: 15px;'><p>3. Arrow Functions</p><p style='margin: 0'>In this video, you'll learn about arrow functions.</p></td></tr><tr><td style='padding: 15px;'><p>4. JavaScript Classes</p><p style='margin: 0'>In this video, you'll learn about classes.</p></td></tr><tr><td style='padding: 15px;'><p>5. Class Constructors</p><p style='margin: 0'>In this video, you'll learn an important feature in JavaScript.</p></td></tr><tr><td style='padding: 15px;'><p>6. JavaScript Object Notation</p><p style='margin: 0'>In this video, you'll get a brief introduction to JSON.</p></td></tr><tr><td style='padding: 15px;'><p>7. Ajax</p><p style='margin: 0'>In this video, you'll learn about asynchronous JavaScript and XML.</p></td></tr><tr><td style='padding: 15px;'><p>8. Fetch API</p><p style='margin: 0'>In this video, you'll learn to work with the fetch API to handle ajax requests.</p></td></tr></tbody></table><br><h4>9. Final Project</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Your Project</p><p style='margin: 0'>In this video, you'll get a brief of the project that you'll create.</p></td></tr><tr><td style='padding: 15px;'><p>2. Summary</p><p style='margin: 0'>This video gives a summary of the last 2 sections.</p></td></tr></tbody></table>

JavaScript

Learn JavaScript from Scratch: JavaScript for Everyone is a hands-on course that teaches the ins and outs of modern JavaScript. It is the perfect course for anyone who wants to learn the programming language from scratch and wants to develop engaging, interactive websites that leverage all the latest features JavaScript comes with.

Learn JavaScript from Scratch: JavaScript for Everyone

<div id="course-pills-1">Duration<p>4 Days</p><p>24 CPD hours</p>This course is intended for<p></p><p>This course is designed for data scientists with existing knowledge of Python and machine learning frameworks like Scikit-Learn, PyTorch, and Tensorflow, who want to build and operate machine learning solutions in the cloud.</p><p></p>Overview<p>Learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. This course teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring in Microsoft Azure.</p><p></p><p>Learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. This course teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring with Azure Machine Learning and MLflow.</p><p></p>Prerequisites<p></p><li>Creating cloud resources in Microsoft Azure.</li>  <li>Using Python to explore and visualize data.</li>  <li>Training and validating machine learning models using common frameworks like Scikit-Learn, PyTorch, and TensorFlow.</li>  <li>Working with containers</li>  <li>AI-900T00: Microsoft Azure AI Fundamentals is recommended, or the equivalent experience.</li><p></p></div><div id="course-pills-2"><h3>1 - Design a data ingestion strategy for machine learning projects</h3> <ul> <li>Identify your data source and format</li> <li>Choose how to serve data to machine learning workflows</li> <li>Design a data ingestion solution</li> </ul> <h3>2 - Design a machine learning model training solution</h3> <ul> <li>Identify machine learning tasks</li> <li>Choose a service to train a machine learning model</li> <li>Decide between compute options</li> </ul> <h3>3 - Design a model deployment solution</h3> <ul> <li>Understand how model will be consumed</li> <li>Decide on real-time or batch deployment</li> </ul> <h3>4 - Design a machine learning operations solution</h3> <ul> <li>Explore an MLOps architecture</li> <li>Design for monitoring</li> <li>Design for retraining</li> </ul> <h3>5 - Explore Azure Machine Learning workspace resources and assets</h3> <ul> <li>Create an Azure Machine Learning workspace</li> <li>Identify Azure Machine Learning resources</li> <li>Identify Azure Machine Learning assets</li> <li>Train models in the workspace</li> </ul> <h3>6 - Explore developer tools for workspace interaction</h3> <ul> <li>Explore the studio</li> <li>Explore the Python SDK</li> <li>Explore the CLI</li> </ul> <h3>7 - Make data available in Azure Machine Learning</h3> <ul> <li>Understand URIs</li> <li>Create a datastore</li> <li>Create a data asset</li> </ul> <h3>8 - Work with compute targets in Azure Machine Learning</h3> <ul> <li>Choose the appropriate compute target</li> <li>Create and use a compute instance</li> <li>Create and use a compute cluster</li> </ul> <h3>9 - Work with environments in Azure Machine Learning</h3> <ul> <li>Understand environments</li> <li>Explore and use curated environments</li> <li>Create and use custom environments</li> </ul> <h3>10 - Find the best classification model with Automated Machine Learning</h3> <ul> <li>Preprocess data and configure featurization</li> <li>Run an Automated Machine Learning experiment</li> <li>Evaluate and compare models</li> </ul> <h3>11 - Track model training in Jupyter notebooks with MLflow</h3> <ul> <li>Configure MLflow for model tracking in notebooks</li> <li>Train and track models in notebooks</li> </ul> <h3>12 - Run a training script as a command job in Azure Machine Learning</h3> <ul> <li>Convert a notebook to a script</li> <li>Run a script as a command job</li> <li>Use parameters in a command job</li> </ul> <h3>13 - Track model training with MLflow in jobs</h3> <ul> <li>Track metrics with MLflow</li> <li>View metrics and evaluate models</li> </ul> <h3>14 - Perform hyperparameter tuning with Azure Machine Learning</h3> <ul> <li>Define a search space</li> <li>Configure a sampling method</li> <li>Configure early termination</li> <li>Use a sweep job for hyperparameter tuning</li> </ul> <h3>15 - Run pipelines in Azure Machine Learning</h3> <ul> <li>Create components</li> <li>Create a pipeline</li> <li>Run a pipeline job</li> </ul> <h3>16 - Register an MLflow model in Azure Machine Learning</h3> <ul> <li>Log models with MLflow</li> <li>Understand the MLflow model format</li> <li>Register an MLflow model</li> </ul> <h3>17 - Create and explore the Responsible AI dashboard for a model in Azure Machine Learning</h3> <ul> <li>Understand Responsible AI</li> <li>Create the Responsible AI dashboard</li> <li>Evaluate the Responsible AI dashboard</li> </ul> <h3>18 - Deploy a model to a managed online endpoint</h3> <ul> <li>Explore managed online endpoints</li> <li>Deploy your MLflow model to a managed online endpoint</li> <li>Deploy a model to a managed online endpoint</li> <li>Test managed online endpoints</li> </ul> <h3>19 - Deploy a model to a batch endpoint</h3> <ul> <li>Understand and create batch endpoints</li> <li>Deploy your MLflow model to a batch endpoint</li> <li>Deploy a custom model to a batch endpoint</li> <li>Invoke and troubleshoot batch endpoints</li> </ul></div>

Data Engineering

Microsoft AZ-900

Microsoft Azure

Microsoft AZ-303

Microsoft AZ-700

Azure Machine Learning

DP-100T01 Designing and Implementing a Data Science Solution on Azure

"Start your career as a Certified Python Programmer and earn up to £70,000 per Year."
Are you looking to make your mark in the ever-evolving world of Data Analyst? The demand for Python programmers has never been higher. Just in the UK, job postings for Analysts / Python programmers surged by an astounding 70% in 2022. This exponential growth trend signifies the soaring need for skilled Python programmers. Amid this vibrant job market, our Python Programmer online Training is your golden ticket to a prosperous career in programming or Data Analysis. Regardless of your level - beginner or expert - we ensure a comprehensive learning experience that will enhance your current skills and prepare you for the dynamic tech industry.
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Courses we will provide once you enrol in the program:
Course 01: Computer Science With Python
Course 02: Ultimate Python Training for Beginners
Course 03: Python Intermediate Training
Course 04: Python Advanced Training
Course 05: Deep Learning & Neural Networks Python - Keras
Course 06: Complete Python Machine Learning & Data Science Fundamentals
Course 06: Introduction to Data Analysis
Course 07: Business and Data Analytics for Beginners
Course 08: Data Analytics with Tableau
Course 09: Quick Data Science Approach from Scratch
Course 10: Learn MySQL from Scratch for Data Science and Analytics
Course 11: SQL for Data Science, Data Analytics and Data Visualization
Course 12: Statistics & Probability for Data Science & Machine Learning
Course 13: Basic Google Data Studio
Course 14: Machine Learning with Python Course
Course 15: Python Programming Bible | Networking, GUI, Email, XML, CGI
Course 16: Web Scraping and Mapping Dam Levels in Python and Leaflet
Course 17: Coding Essentials - Javascript, ASP. Net, C#
Course 19: Master JavaScript with Data Visualization
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HF Online provides consultancy, professional and educational services to many of the companies in the UK. During our intense exclusive training program, you will not just gain and complete the industry valuable certification but will gain industry experience as well, which is imperative to get your 1st job in the sector.
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Begin your exciting journey with us by enrolling in the Python Certification Training program. Complete your registration and make a secure online payment. Remember, we offer a 14-day money-back guarantee if you're not completely satisfied.
After you enrol in the Program, you will get lifetime access to 19 Premium Courses related to Python Programming. These courses will teach you the knowledge and skills required to become a successful Python Prgrammer. Our customer service team will help you and keep in contact with you every step of the way. So you won't have to worry about a thing!
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Once enrolled, you will be paired with a dedicated career mentor. Schedule your first one-on-one session to discuss your career aspirations, skills, experience, and any areas for potential growth. This conversation will shape your learning and development path.
Step 3 - Certification upon Course Completion
After learning from the courses, you must obtain certificates for each course. There will be exams for every course, and you have to pass them to get your certificate. To pass successfully, you must get 90% marks. Once you pass the exams, you will receive hardcopy certificates. These certificates will prove that you're an expert in the subject.
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We understand the power of casting a wide net. We'll strategically submit your CV to various platforms and networks, expanding your reach and connecting you with valuable opportunities that align with your career goals. We will also make connections with many high-profile individuals and companies through your LinkedIn profile.
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With your CV ready, we'll move on to interview preparation. Gain exclusive access to our database of potential interview questions. Through simulated interviews with your mentor, you'll practice your responses and receive valuable feedback to further refine your skills.
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Post-interview, we'll provide a debriefing session to reflect on your performance and identify areas of improvement for future interviews if necessary. Remember, our commitment extends until you land your dream job.
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Once you've secured your dream job in Python Programming, it's time to celebrate! However, our support doesn't end there. We'll provide you with ongoing career advice to ensure you continue to thrive in your new role.
We're excited to accompany you on this journey to success. Enrol today, and let's get started! Your path to a successful career in Python Programming begins with us.
 CPD 
100 CPD hours / points  Accredited by CPD Quality Standards
 Who is this course for? 
This Python Certification Course is suitable for:
Beginners with no prior programming experience who are looking to enter the world of coding.
Intermediate programmers who wish to expand their skills and explore Python's extensive usage.
IT professionals seeking to diversify their skill sets and stay relevant in today's tech-driven market.
Data analysts and scientists who want to leverage Python's powerful libraries for their data processing needs.
Students and recent graduates looking to enhance their employability in the thriving tech industry.
Entrepreneurs who wish to understand and utilise Python to automate tasks and analyse data for their businesses.
Anyone with a keen interest in Python programming and a desire to delve into its applications in diverse fields like web development, data science, machine learning, and more.
 Requirements 
No experience required. Just enrol & start learning python.
 Career path 
Upon completion of our Program, the potential career paths include:
Python Developer: £30,000 - £90,000 annually
Data Scientist: £40,000 - £100,000 annually
Machine Learning Engineer: £50,000 - £110,000 annually
Data Analyst: £35,000 - £85,000 annually
Software Engineer: £35,000 - £95,000 annually
Back-end Developer: £40,000 - £95,000 annually
Web Developer: £30,000 -£85,000 annually
 Certificates 
CPD Accredited e-Certificate
 Digital certificate - Included 
CPD Accredited Framed (Hardcopy) Certificate
 Hard copy certificate - Included 
Enrolment Letter
 Digital certificate - Included 
QLS Endorsed Hard Copy Certificate
 Hard copy certificate - Included 
Student ID Card
 Digital certificate - Included 

Academy for Health and Fitness

Programming Fundamentals

Career Development

Become an IT professional with our Python Certification - IT Job Ready Program! Gain comprehensive skills in Python programming, data analysis, and automation. We offer a money-back guarantee if you don't secure a job within six months of completion. Enroll now and jumpstart your tech career!


Ready to land your dream job in tech? Our Python Certification - IT Job Ready Program equips you with essential Python programming, data analysis, and automation skills. Plus, we offer a money-back guarantee if you don't get hired within six months of completing the course. Don't miss out – enroll today and take the first step towards a successful IT career! 💻📊 #PythonCertification #TechTraining #CareerReady #MoneyBackGuarantee

Python Certification - IT Job Ready Program with Money Back Guarantee

<strong>Learn Python Programming the Easy Way, Complete with Examples, Quizzes, Exercises and more. Learn Python 2 and Python 3.</strong>
        <p>This course will teach you Python in a practical manner, complete with examples, quizzes, exercises, and more. You will learn when to use Python 2 and Python 3; both versions are covered in the course and you will learn to program in both. You'll learn how to take tedious and repetitious tasks and turn them into programs that will save you time and simplify your life on Linux, UNIX, or MAC systems. You will learn how to prepare your computer for programming in Python; how to work with various data types including strings, lists, tuples, dictionaries, Booleans; how to perform mathematical operations using Python, and more.</p>
        <h2>What You Will Learn</h2><p>When to use Python 2 and when to use Python 3.<br>How to install Python on Windows, Mac, and Linux.<br>How to prepare your computer for programming in Python.<br>The various ways to run a Python program on Windows, Mac, and Linux.<br>Suggested text editors and Integrated Development Environments to use when coding in Python.<br>How to work with various data types including strings, lists, tuples, dictionaries, Booleans, and more.<br>What variables are and when to use them.<br>How to perform mathematical operations using Python.<br>How to capture input from a user.<br>Ways to control the flow of your programs.<br>The importance of white space in Python.<br>How to organize your Python programs: learn what goes where.<br>What modules are, when you should use them, and how to create your own.<br>How to define and use functions.<br>Important built-in Python functions that you ll use often.<br>How to read from and write to files.<br>The difference between binary and text files.<br>Various ways of getting help, including finding Python documentation.<br></p>
        <h2>Audience</h2><p>This course targets anyone interested in Python programming, Python scripting, or computer programming in general; those who want to become a highly paid Python developer; and those who want to open up doors in their IT career by learning one of the world's most popular and in-demand programming languages.</p>
        <h2>Approach</h2><p>A complete course packed with step-by-step instructions, practice exercises with solutions, and quizzes. This course is clearly divided into small parts to help you understand each part individually and learn at your own pace. Once you've completed this course you'll know how to write programs that will run on the Linux, Mac, and Windows operating systems. You can even take what you've learned and apply it to web applications. </p>
        <h2>Key Features</h2><p>How to install Python on Windows, Mac, and Linux. * A practical tutorial designed for Python beginners. * </p>
        <h2>Github Repo</h2><p>https://github.com/packtpublishing/python-for-beginners-learn-python-programming-python-3-</p>
        <h2>About the Author</h2><h3>Jason Cannon</h3><p>Jason Cannon is a professional system administrator, consultant, and author. He started his career as a Unix and Linux System engineer in 1999. Since that time, he has utilized his Linux skills at companies such as Xerox, UPS, Hewlett-Packard, and Amazon.com. Additionally, he has acted as a technical consultant and independent contractor for small businesses and Fortune 500 companies.

Jason has professional experience with CentOS, RedHat Enterprise Linux, SUSE Linux Enterprise Server, and Ubuntu. He has used several Linux distributions on personal projects including Debian, Slackware, CrunchBang, and others. In addition to Linux, Jason has experience supporting proprietary Unix operating systems including AIX, HP-UX, and Solaris. He enjoys teaching others how to use and exploit the power of the Linux operating system.</p>
        <h2>Course Outline</h2><h4>1. Course Overview and Downloads</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Course Overview</p><p style='margin: 0'>Course Overview and Downloads: Course Overview</p></td></tr></tbody></table><br><h4>2. Python Setup</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Python 2 vs Python 3</p><p style='margin: 0'>Python Setup: Python 2 vs Python 3</p></td></tr><tr><td style='padding: 15px;'><p>2. Installing Python on Windows</p><p style='margin: 0'>Python Setup: Installing Python on Windows</p></td></tr><tr><td style='padding: 15px;'><p>3. Installing Python on Mac</p><p style='margin: 0'>Python Setup: Installing Python on Mac</p></td></tr><tr><td style='padding: 15px;'><p>4. Installing Python on Linux</p><p style='margin: 0'>Python Setup: Installing Python on Linux</p></td></tr><tr><td style='padding: 15px;'><p>5. Writing Python Programs</p><p style='margin: 0'>Python Setup: Writing Python Programs</p></td></tr><tr><td style='padding: 15px;'><p>6. Running Python Programs</p><p style='margin: 0'>Python Setup: Running Python Programs</p></td></tr></tbody></table><br><h4>3. Strings and Variables</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Section Overview</p><p style='margin: 0'>Strings and Variables: Section Overview</p></td></tr><tr><td style='padding: 15px;'><p>2. Variables and Strings</p><p style='margin: 0'>Strings and Variables: Variables and Strings</p></td></tr><tr><td style='padding: 15px;'><p>3. Functions and Printing</p><p style='margin: 0'>Strings and Variables: Functions and Printing</p></td></tr><tr><td style='padding: 15px;'><p>4. String Methods</p><p style='margin: 0'>Strings and Variables: String Methods</p></td></tr><tr><td style='padding: 15px;'><p>5. String Concatenation</p><p style='margin: 0'>Strings and Variables: String Concatenation</p></td></tr><tr><td style='padding: 15px;'><p>6. Formatting Strings</p><p style='margin: 0'>Strings and Variables: Formatting Strings</p></td></tr><tr><td style='padding: 15px;'><p>7. Section Summary</p><p style='margin: 0'>Strings and Variables: Section Summary</p></td></tr><tr><td style='padding: 15px;'><p>8. Solutions to the Practice Exercises - #1 - Video</p><p style='margin: 0'>Strings and Variables: Solutions to the Practice Exercises - #1 - Video</p></td></tr><tr><td style='padding: 15px;'><p>9. Solutions to the Practice Exercises - #2 - Video</p><p style='margin: 0'>Strings and Variables: Solutions to the Practice Exercises - #2 - Video</p></td></tr><tr><td style='padding: 15px;'><p>10. Solutions to the Practice Exercises - #3 - Video</p><p style='margin: 0'>Strings and Variables: Solutions to the Practice Exercises - #3 - Video</p></td></tr></tbody></table><br><h4>4. Numbers and Math</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Section Overview</p><p style='margin: 0'>Numbers and Math: Section Overview</p></td></tr><tr><td style='padding: 15px;'><p>2. Numbers, Numeric Operations, and Numeric Functions</p><p style='margin: 0'>Numbers and Math: Numbers, Numeric Operations, and Numeric Functions</p></td></tr><tr><td style='padding: 15px;'><p>3. Comments</p><p style='margin: 0'>Numbers and Math: Comments</p></td></tr><tr><td style='padding: 15px;'><p>4. Section Summary</p><p style='margin: 0'>Numbers and Math: Section Summary</p></td></tr></tbody></table><br><h4>5. Booleans and Conditionals</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Section Overview</p><p style='margin: 0'>Booleans and Conditionals: Section Overview</p></td></tr><tr><td style='padding: 15px;'><p>2. Booleans</p><p style='margin: 0'>Booleans and Conditionals: Booleans</p></td></tr><tr><td style='padding: 15px;'><p>3. Conditionals</p><p style='margin: 0'>Booleans and Conditionals: Conditionals</p></td></tr><tr><td style='padding: 15px;'><p>4. Section Summary</p><p style='margin: 0'>Booleans and Conditionals: Section Summary</p></td></tr></tbody></table><br><h4>6. Functions</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Section Overview</p><p style='margin: 0'>Functions: Section Overview</p></td></tr><tr><td style='padding: 15px;'><p>2. Functions, Part I</p><p style='margin: 0'>Functions: Functions, Part I</p></td></tr><tr><td style='padding: 15px;'><p>3. Functions, Part II</p><p style='margin: 0'>Functions: Functions, Part II</p></td></tr><tr><td style='padding: 15px;'><p>4. Section Summary</p><p style='margin: 0'>Functions: Section Summary</p></td></tr></tbody></table><br><h4>7. Lists</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Section Overview</p><p style='margin: 0'>Lists: Section Overview</p></td></tr><tr><td style='padding: 15px;'><p>2. Lists</p><p style='margin: 0'>Lists: Lists</p></td></tr><tr><td style='padding: 15px;'><p>3. Slices</p><p style='margin: 0'>Lists: Slices</p></td></tr><tr><td style='padding: 15px;'><p>4. Exception Handling</p><p style='margin: 0'>Lists: Exception Handling</p></td></tr><tr><td style='padding: 15px;'><p>5. Loops</p><p style='margin: 0'>Lists: Loops</p></td></tr><tr><td style='padding: 15px;'><p>6. Sorting and Ranges</p><p style='margin: 0'>Lists: Sorting and Ranges</p></td></tr><tr><td style='padding: 15px;'><p>7. Section Summary</p><p style='margin: 0'>Lists: Section Summary</p></td></tr></tbody></table><br><h4>8. Dictionaries</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Section Overview</p><p style='margin: 0'>Dictionaries: Section Overview</p></td></tr><tr><td style='padding: 15px;'><p>2. Dictionaries - Part I</p><p style='margin: 0'>Dictionaries: Dictionaries - Part I</p></td></tr><tr><td style='padding: 15px;'><p>3. Dictionaries - Part II</p><p style='margin: 0'>Dictionaries: Dictionaries - Part II</p></td></tr><tr><td style='padding: 15px;'><p>4. Section Summary</p><p style='margin: 0'>Dictionaries: Section Summary</p></td></tr></tbody></table><br><h4>9. Tuples</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Section Overview</p><p style='margin: 0'>Tuples: Section Overview</p></td></tr><tr><td style='padding: 15px;'><p>2. Tuples</p><p style='margin: 0'>Tuples: Tuples</p></td></tr><tr><td style='padding: 15px;'><p>3. Section Summary</p><p style='margin: 0'>Tuples: Section Summary</p></td></tr></tbody></table><br><h4>10. Files</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Section Overview</p><p style='margin: 0'>Files: Section Overview</p></td></tr><tr><td style='padding: 15px;'><p>2. Files, Part I</p><p style='margin: 0'>Files: Files, Part I</p></td></tr><tr><td style='padding: 15px;'><p>3. Files, Part II</p><p style='margin: 0'>Files: Files, Part II</p></td></tr><tr><td style='padding: 15px;'><p>4. Section Summary</p><p style='margin: 0'>Files: Section Summary</p></td></tr></tbody></table><br><h4>11. Modules</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Section Overview</p><p style='margin: 0'>Modules: Section Overview</p></td></tr><tr><td style='padding: 15px;'><p>2. Modules, Part I</p><p style='margin: 0'>Modules: Modules, Part I</p></td></tr><tr><td style='padding: 15px;'><p>3. Modules, Part II</p><p style='margin: 0'>Modules: Modules, Part II</p></td></tr><tr><td style='padding: 15px;'><p>4. Section Overview</p><p style='margin: 0'>Modules: Section Overview</p></td></tr></tbody></table>

Python

Learn Python Programming the Easy Way, Complete with Examples, Quizzes, Exercises and more. Learn Python 2 and Python 3.

Python for Beginners: Learn Python Programming (Python 3)

<p><strong>Start your career in Data Science and earn up to £90,000 per month.</strong></p><p>Are you eager to dive into the high-speed world of Data Science powered by Python? In the UK alone, Data Scientist job postings witnessed a dramatic increase of 67% in 2022, emphasising the burgeoning demand for proficient Python programmers. Amid such a dynamic job market, our online course - Data Science with Python, serves as your stepping-stone to a universe of opportunities. Whether you're taking your first step into the realm of Data Science or aiming to augment your existing skills, our program offers peerless support, ensuring you're industry-ready by the time you complete our course.</p><p><strong>Our mission is simple</strong> - to be your trusted partner every step of the way, from training to employment.</p><p>In addition to teaching you the technical skills you need, we will also provide you with <strong>career mentoring and support</strong>. We will help you build your resume, prepare for interviews, and land your <strong>dream job</strong>. We also have<strong> partnerships with many companies</strong> that are hiring Data <strong>Scientists</strong>, so we can help you get your foot in the door.</p><p>If you are not happy with our service, we also offer a <strong>100% money-back guarantee</strong>. So what are you waiting for? Enrol in our Data Scientist with Python Training Program today and start your journey to becoming a successful Data Scientist!</p><p>If you have any questions, you can <strong>contact us</strong>. We will be happy to provide you with all the information you need.</p><p><strong>Why Choose Us?</strong></p><p>So, what sets us apart from other programs? Let's dive into the exceptional benefits you'll experience when you join our Data Scientist with Python:</p><ul><li><strong>Personalised Guidance:</strong> We believe in the power of individual attention. Our experienced mentors will provide one-on-one counselling sessions tailored to your specific needs. Whether you're a beginner or have some Python experience, we will guide you towards honing your skills and developing a strong foundation in both Data Science and Python.<br /><br /></li><li><strong>One-On-One Consultation Sessions with Industry Experts:</strong> Gain invaluable insights and guidance from seasoned professionals who have thrived in the Data Science field. Our consultation sessions provide you with insider tips, tricks, and advice, empowering you to navigate the industry with confidence and expertise.<br /><br /></li><li><strong>Extensive Job Opportunities:</strong> We have established partnerships with numerous companies actively seeking Data Scientists. Through our network, we'll connect you with exclusive job openings that are not easily accessible elsewhere.<br /><br /></li><li><strong>Interview Preparation:</strong> No more stress over unexpected interview questions. We provide you with access to a comprehensive database of potential interview questions curated over years of industry experience. Walk into your interviews confident, well-prepared, and ready to impress.<br /><br /></li><li><strong>Money-Back Guarantee:</strong> Your satisfaction is our top priority. We are confident in the quality of our training and support, which is why we offer a <strong>100% money-back guarantee. </strong>If, for any reason, you're not happy with our services, we'll refund your investment, no questions asked. We believe in the value we provide and want you to feel completely satisfied with your decision to join us.<br /><br /></li><li><strong>Continuous Career Support: </strong>Our commitment doesn't end when you secure a job. We'll be there for you throughout your career journey, offering continued support and guidance.</li></ul><p><strong>Here are the courses we will provide once you enrol in the program:</strong></p><ul><li>Course 01: Business and Data Analytics for Beginners</li><li>Course 02: Quick Data Science Approach from Scratch</li><li>Course 03: Learn MySQL from Scratch for Data Science and Analytics</li><li>Course 04: SQL for Data Science, Data Analytics and Data Visualization</li><li>Course 05: Statistics &amp; Probability for Data Science &amp; Machine Learning</li><li>Course 06: R Programming for Data Science</li><li>Course 07: Python Data Science with Numpy, Pandas and Matplotlib</li><li>Course 08: Complete Python Machine Learning &amp; Data Science Fundamentals</li><li>Course 09: 2021 Data Science &amp; Machine Learning with R from A-Z</li><li>Course 10: Python Programming from Scratch with My SQL Database</li><li>Course 11: Level 2 Python Course</li><li>Course 12: Machine Learning for Predictive Maps in Python and Leaflet</li><li>Course 13: Python Programming Bible | Networking, GUI, Email, XML, CGI</li><li>Course 14: Python for Spatial Analysis in ArcGIS</li><li>Course 15: Ultimate Python Training for Beginners</li><li>Course 16: PyScript Fundamentals Training</li></ul><p><strong>How Can We Offer Job Guarantees?</strong></p><p>HF Online provides consultancy, professional and educational services to many of the companies in the UK. During our intense exclusive training program, you will not just gain and complete the industry valuable certification but will gain industry experience as well, which is imperative to get your 1st job in the sector.</p> <p><strong>The </strong><strong>Data Scientist with Python </strong><strong>Program is completed in 9 easy steps:<br /><br /></strong></p><p><strong>Step 1: Enrol in the Programme</strong></p><p>Begin your exciting journey with us by enrolling in the Data Science with Python Training program. Complete your registration and make a secure online payment. Remember, we offer a 14-day money-back guarantee if you're not completely satisfied.</p><p>After you enrol in the Program, you will get lifetime access to 16 premium courses related to Data Science with Python. These courses will teach you the knowledge and skills required to become a successful Data Scientist. Our customer service team will help you and keep in contact with you every step of the way. So you won't have to worry about a thing!</p><p><strong>Step 2: Initial One-On-One Counselling Session</strong></p><p>Once enrolled, you will be paired with a dedicated career mentor. Schedule your first one-on-one session to discuss your career aspirations, skills, experience, and any areas for potential growth. This conversation will shape your learning and development path.<br /><br /></p><p><strong>Step 3 - </strong><strong>Certification upon Course Completion</strong></p><p>After learning from the courses, you must obtain certificates for each course. There will be exams for every course, and you have to pass them to get your certificate. To pass successfully, you must get 90% marks. Once you pass the exams, you will receive hardcopy certificates. These certificates will prove that you're an expert in the subject.<br /><br /></p><p><strong>Step 4: </strong><strong>CV Revamping</strong></p><p>Our team of professionals will build you a compelling CV and <strong>LinkedIn profile</strong>. We'll ensure it presents your skills and qualifications effectively and is tailored to the needs and expectations of the Data Science with Python industry. With these powerful tools in hand, you'll be fully prepared to tackle job interviews confidently. <br /><br /></p><p><strong>Step 5: Building Network and Submitting CV</strong></p><p>We understand the power of casting a wide net. We'll strategically submit your CV to various platforms and networks, expanding your reach and connecting you with valuable opportunities that align with your career goals. We will also make connections with many<strong> high-profile individuals and companies</strong> through your LinkedIn profile.<br /><br /></p><p><strong>Step 6: Interview Preparation</strong></p><p>With your CV ready, we'll move on to interview preparation. Gain exclusive access to our database of potential interview questions. Through simulated interviews with your mentor, you'll practice your responses and receive valuable feedback to further refine your skills.<br /><br /></p><p><strong>Step 7: Securing Job Interviews</strong></p><p>Leveraging our partnerships with leading companies, <strong>we'll secure job interviews for you</strong>. We'll ensure you get the opportunity to showcase your skills to potential employers and <strong>get the dream job you want</strong>.<br /><br /></p><p><strong>Step 8: Post-Interview Support</strong></p><p>Post-interview, we'll provide a debriefing session to reflect on your performance and identify areas of improvement for future interviews if necessary. Remember, our commitment extends until you land your dream job.<br /><br /></p><p><strong>Step 9: Celebrate Your New Job!</strong></p><p>Once you've secured your dream job in Data Science with Python, it's time to celebrate! However, our support doesn't end there. We'll provide you with ongoing career advice to ensure you continue to thrive in your new role.</p><p>We're excited to accompany you on this journey to success. Enrol today, and let's get started! Your path to a successful career in Data Science with Python begins with us.</p> <h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        100 CPD hours / points
                                    </div>
                                        <div>
                                            Accredited by CPD Quality Standards
                                        </div>
                                </div>
                            </div>
                        </div> <h2>
        
        <div>Who is this course for?</div>
    </h2>

                        <div id="who_is_this_course_for">
                            <ul><li>Beginners with an interest in Data Science and Python programming.</li><li>Programmers and Software Engineers looking to transition into Data Science.</li><li>Business Analysts and Project Managers aiming to leverage Data Science in their domains.</li><li>Researchers and Academics who wish to utilise Python for complex data analysis.</li></ul>
                        </div> <h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>No experience required. Just enrol &amp; start learning.</p>
                        </div> <h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <ul><li>Data Scientist: £60,000 - £90,000</li><li>Machine Learning Engineer: £65,000 - £100,000</li><li>Data Analyst: £40,000 - £60,000</li><li>Business Intelligence Analyst: £45,000 - £70,000</li><li>Data Engineer: £50,000 - £80,000</li><li>Big Data Architect: £70,000 - £120,000</li></ul>
                        </div> <h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>CPD Accredited e-Certificate</h4>
        <p>
            Digital certificate -
            Included
        </p>
        <h4>CPD Accredited Framed (Hardcopy) Certificate</h4>
        <p>
            Hard copy certificate -
            Included
        </p>
        <h4>Enrolment Letter</h4>
        <p>
            Digital certificate -
            Included
        </p>
        <h4>QLS Endorsed Hard Copy Certificate</h4>
        <p>
            Hard copy certificate -
            Included
        </p>
        <h4>Student ID Card</h4>
        <p>
            Digital certificate -
            Included
        </p>

                        </div>

Start your career in Data Science and earn up to £90,000 per month.
Are you eager to dive into the high-speed world of Data Science powered by Python? In the UK alone, Data Scientist job postings witnessed a dramatic increase of 67% in 2022, emphasising the burgeoning demand for proficient Python programmers. Amid such a dynamic job market, our online course - Data Science with Python, serves as your stepping-stone to a universe of opportunities. Whether you're taking your first step into the realm of Data Science or aiming to augment your existing skills, our program offers peerless support, ensuring you're industry-ready by the time you complete our course.
Our mission is simple - to be your trusted partner every step of the way, from training to employment.
In addition to teaching you the technical skills you need, we will also provide you with career mentoring and support. We will help you build your resume, prepare for interviews, and land your dream job. We also have partnerships with many companies that are hiring Data Scientists, so we can help you get your foot in the door.
If you are not happy with our service, we also offer a 100% money-back guarantee. So what are you waiting for? Enrol in our Data Scientist with Python Training Program today and start your journey to becoming a successful Data Scientist!
If you have any questions, you can contact us. We will be happy to provide you with all the information you need.
Why Choose Us?
So, what sets us apart from other programs? Let's dive into the exceptional benefits you'll experience when you join our Data Scientist with Python:
Personalised Guidance: We believe in the power of individual attention. Our experienced mentors will provide one-on-one counselling sessions tailored to your specific needs. Whether you're a beginner or have some Python experience, we will guide you towards honing your skills and developing a strong foundation in both Data Science and Python.
One-On-One Consultation Sessions with Industry Experts: Gain invaluable insights and guidance from seasoned professionals who have thrived in the Data Science field. Our consultation sessions provide you with insider tips, tricks, and advice, empowering you to navigate the industry with confidence and expertise.
Extensive Job Opportunities: We have established partnerships with numerous companies actively seeking Data Scientists. Through our network, we'll connect you with exclusive job openings that are not easily accessible elsewhere.
Interview Preparation: No more stress over unexpected interview questions. We provide you with access to a comprehensive database of potential interview questions curated over years of industry experience. Walk into your interviews confident, well-prepared, and ready to impress.
Money-Back Guarantee: Your satisfaction is our top priority. We are confident in the quality of our training and support, which is why we offer a 100% money-back guarantee. If, for any reason, you're not happy with our services, we'll refund your investment, no questions asked. We believe in the value we provide and want you to feel completely satisfied with your decision to join us.
Continuous Career Support: Our commitment doesn't end when you secure a job. We'll be there for you throughout your career journey, offering continued support and guidance.
Here are the courses we will provide once you enrol in the program:
Course 01: Business and Data Analytics for Beginners
Course 02: Quick Data Science Approach from Scratch
Course 03: Learn MySQL from Scratch for Data Science and Analytics
Course 04: SQL for Data Science, Data Analytics and Data Visualization
Course 05: Statistics & Probability for Data Science & Machine Learning
Course 06: R Programming for Data Science
Course 07: Python Data Science with Numpy, Pandas and Matplotlib
Course 08: Complete Python Machine Learning & Data Science Fundamentals
Course 09: 2021 Data Science & Machine Learning with R from A-Z
Course 10: Python Programming from Scratch with My SQL Database
Course 11: Level 2 Python Course
Course 12: Machine Learning for Predictive Maps in Python and Leaflet
Course 13: Python Programming Bible | Networking, GUI, Email, XML, CGI
Course 14: Python for Spatial Analysis in ArcGIS
Course 15: Ultimate Python Training for Beginners
Course 16: PyScript Fundamentals Training
How Can We Offer Job Guarantees?
HF Online provides consultancy, professional and educational services to many of the companies in the UK. During our intense exclusive training program, you will not just gain and complete the industry valuable certification but will gain industry experience as well, which is imperative to get your 1st job in the sector.
The Data Scientist with Python Program is completed in 9 easy steps:


Step 1: Enrol in the Programme
Begin your exciting journey with us by enrolling in the Data Science with Python Training program. Complete your registration and make a secure online payment. Remember, we offer a 14-day money-back guarantee if you're not completely satisfied.
After you enrol in the Program, you will get lifetime access to 16 premium courses related to Data Science with Python. These courses will teach you the knowledge and skills required to become a successful Data Scientist. Our customer service team will help you and keep in contact with you every step of the way. So you won't have to worry about a thing!
Step 2: Initial One-On-One Counselling Session
Once enrolled, you will be paired with a dedicated career mentor. Schedule your first one-on-one session to discuss your career aspirations, skills, experience, and any areas for potential growth. This conversation will shape your learning and development path.


Step 3 - Certification upon Course Completion
After learning from the courses, you must obtain certificates for each course. There will be exams for every course, and you have to pass them to get your certificate. To pass successfully, you must get 90% marks. Once you pass the exams, you will receive hardcopy certificates. These certificates will prove that you're an expert in the subject.


Step 4: CV Revamping
Our team of professionals will build you a compelling CV and LinkedIn profile. We'll ensure it presents your skills and qualifications effectively and is tailored to the needs and expectations of the Data Science with Python industry. With these powerful tools in hand, you'll be fully prepared to tackle job interviews confidently. 


Step 5: Building Network and Submitting CV
We understand the power of casting a wide net. We'll strategically submit your CV to various platforms and networks, expanding your reach and connecting you with valuable opportunities that align with your career goals. We will also make connections with many high-profile individuals and companies through your LinkedIn profile.


Step 6: Interview Preparation
With your CV ready, we'll move on to interview preparation. Gain exclusive access to our database of potential interview questions. Through simulated interviews with your mentor, you'll practice your responses and receive valuable feedback to further refine your skills.


Step 7: Securing Job Interviews
Leveraging our partnerships with leading companies, we'll secure job interviews for you. We'll ensure you get the opportunity to showcase your skills to potential employers and get the dream job you want.


Step 8: Post-Interview Support
Post-interview, we'll provide a debriefing session to reflect on your performance and identify areas of improvement for future interviews if necessary. Remember, our commitment extends until you land your dream job.


Step 9: Celebrate Your New Job!
Once you've secured your dream job in Data Science with Python, it's time to celebrate! However, our support doesn't end there. We'll provide you with ongoing career advice to ensure you continue to thrive in your new role.
We're excited to accompany you on this journey to success. Enrol today, and let's get started! Your path to a successful career in Data Science with Python begins with us.
 CPD 
100 CPD hours / points  Accredited by CPD Quality Standards
 Who is this course for? 
Beginners with an interest in Data Science and Python programming.
Programmers and Software Engineers looking to transition into Data Science.
Business Analysts and Project Managers aiming to leverage Data Science in their domains.
Researchers and Academics who wish to utilise Python for complex data analysis.
 Requirements 
No experience required. Just enrol & start learning.
 Career path 
Data Scientist: £60,000 - £90,000
Machine Learning Engineer: £65,000 - £100,000
Data Analyst: £40,000 - £60,000
Business Intelligence Analyst: £45,000 - £70,000
Data Engineer: £50,000 - £80,000
Big Data Architect: £70,000 - £120,000
 Certificates 
CPD Accredited e-Certificate
 Digital certificate - Included 
CPD Accredited Framed (Hardcopy) Certificate
 Hard copy certificate - Included 
Enrolment Letter
 Digital certificate - Included 
QLS Endorsed Hard Copy Certificate
 Hard copy certificate - Included 
Student ID Card
 Digital certificate - Included 

Big Data Analytics

Data Skills

Data Science with Python - IT Job Ready Program with Career Support & Money Back Guarantee

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			<h2><b>Course Overview</b></h2>		</div>
				</div>
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				<div>
					<div><p><span>Are you looking to secure a career in Python programming or software engineering?</span></p><p><span>The</span><b> Python Programming</b><span> course will take you from beginner to expert in this programming language in no time, with step-by-step instructor-led guidance. Through audiovisual training, you will develop your data analysis, programming and coding skills, learning how to perform a wide range of tasks. It will teach you how to get set up on Mac OS X, Linux, and Ubuntu, best practices for string formatting, handling exceptions, and much more.</span></p><p><span>This course is open to anyone who wants to learn Python programming from the basics to an advanced level. Enrol as a part-time or full-time student today and gain the skills to become a Python programming pro.</span></p></div>
				</div>
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					<div><p>This best selling <strong>Python Programming </strong>has been developed by industry professionals and has already been completed by hundreds of satisfied students. This in-depth <strong>Python Programming </strong>is suitable for anyone who wants to build their professional skill set and improve their expert knowledge.</p><p>The <strong>Python Programming </strong>is CPD-accredited, so you can be confident you're completing a quality training course will boost your CV and enhance your career potential. The <strong>Python Programming </strong>is made up of several information-packed modules which break down each topic into bite-sized chunks to ensure you understand and retain everything you learn.</p><p>After successfully completing the<strong> Python Programming</strong>, you will be awarded a certificate of completion as proof of your new skills. If you are looking to pursue a new career and want to build your professional skills to excel in your chosen field, the certificate of completion from the <strong>Python Programming </strong>will help you stand out from the crowd. You can also validate your certification on our website.</p><p>We know that you are busy and that time is precious, so we have designed the <strong>Python Programming </strong>to be completed at your own pace, whether that's part-time or full-time. Get full course access upon registration and access the course materials from anywhere in the world, at any time, from any internet-enabled device. </p><p>Our experienced tutors are here to support you through the entire learning process and answer any queries you may have via email.</p></div>
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Course Cloud

Python Programming

<strong>You will master the fundamentals and more advanced principles of Python programming in this beginner's tutorial. This Python course covers every Python fundamental, including installation and more complex material such as Python data science.</strong>
        <p>'Python is the future of artificial intelligence and machine learning.'-Adrian Rosebrock, author.

Python is the programming language most loved by developers, data scientists, software engineers, and even hackers.

This Python basic to advanced course covers the fundamental concepts of Python programming and ways to apply this to real-world applications. The course modules, lesson-end quizzes, and lesson-end projects collectively cover the training course topics such as data operations, strings, file I/O, exception handling, error handling, conditional statements, CGI programming, shell scripting, web scraping, and Django.

It also covers Logging Framework, Unittest Framework, Socket Programming, Tornado Framework, and Networking. You will also build a Python chat server.

By the end of this course, you will have the skills to create and send robust Python applications using off-the-rack libraries confidently.

The code bundle for this course is available at: https://github.com/PacktPublishing/Python-Programming</p>
        <h2>What You Will Learn</h2><p>Learn the basics of Python<br>Learn networking and database access using Python and CGI programming<br>Understand the Python debugger<br>Understand web scraping using Beautiful Soup<br>Learn about Python Unittest<br>Build a Python chat server</p>
        <h2>Audience</h2><p>This course is for new Python users looking to make the best of this powerful programming language-college freshers, software developers, programming enthusiasts, and technical leads. Python is widely used in artificial intelligence, so if you are planning to start your career in AI/machine learning then you need to have an understanding of Python as a prerequisite.</p>
        <h2>Approach</h2><p>This course comprises self-paced videos, demos, lesson-end quizzes, and a competitive course-end project. This will help you increase your in-depth understanding of Python's design, memory models, object-arranged highlights, and information, and be industry-prepared.</p>
        <h2>Key Features</h2><p>Go from a beginner level to a confident level of Python programming * Increase your in-depth understanding of Python's design, memory models, and more * Work on a competitive project at the end of the course</p>
        <h2>Github Repo</h2><p>https://github.com/packtpublishing/python-programming</p>
        <h2>About the Author</h2><h3>Learnkart Technology Private Limited</h3><p>Learnkart understands the importance of upskilling and its impact on you. They pride themselves in creating specialized e-learning courses that will not only prepare you for certification exams but also help you gain hands-on knowledge for real-world applications. Thousands of students have developed their skills with Learnkart through a variety of courses, such as PgMP, Risk Management Professional (RMP), speech recognition, Python, Amazon Web Services (AWS), and more. Learnkart regularly adds courses to its portfolio to lend more value to your learning experience.</p>
        <h2>Course Outline</h2><h4>1. Course Introduction</h4><p></p><br><h4>2. Python Basics</h4><p></p><br><h4>3. Data Operations</h4><p></p><br><h4>4. Conditional Statements and Functions</h4><p></p><br><h4>5. Error Handling and File Operations</h4><p></p><br><h4>6. Shell Scripting and Django</h4><p></p><br><h4>7. Course End Project</h4><p></p>

You will master the fundamentals and more advanced principles of Python programming in this beginner's tutorial. This Python course covers every Python fundamental, including installation and more complex material such as Python data science.

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					<div><p>Basic Python 3.9  has been designed by industry experts to provide learners with everything they need to enhance their skills and knowledge in their chosen area of study. Enrol on the course today, and learn from the very best the industry has to offer!</p></div>
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					<div><p>This best selling Basic Python 3.9  has been developed by industry professionals and has already been completed by hundreds of satisfied students. This in-depth course is suitable for anyone who wants to build their professional skill set and improve their expert knowledge.</p><p>The Basic Python 3.9  is CPD-accredited, so you can be confident you're completing a quality training course which will boost your CV and enhance your career potential. This course is made up of several information-packed modules which break down each topic into bite-sized chunks to ensure you understand and retain everything you learn.</p><p>After successfully completing the Basic Python 3.9 , you will be awarded a certificate of completion as proof of your new skills. If you are looking to pursue a new career and want to build your professional skills to excel in your chosen field, the certificate of completion from the Basic Python 3.9  will help you stand out from the crowd. You can also validate your certification on our website.</p><p>We know that you are busy and that time is precious, so we have designed the Basic Python 3.9  to be completed at your own pace, whether that's part-time or full-time. Get full course access upon registration and access the course materials from anywhere in the world, at any time, from any internet-enabled device.</p></div>
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Basic Python 3.9

<p><strong>Introducing Coding using Python</strong></p>
<p>This course introduces your child to a very advanced, yet easy to learn programming languages &ndash; Python. It&rsquo;s safe to say that many apps we use today have been built using Python &ndash; Instagram Web, Netflix, YouTube, to name a few! This course teaches the fundamentals of coding, and creates a solid foundation to solve more complex real-life problems.</p>

Riva Learning

Programming Languages

Computing

Choose this course if your child is new to Python or has done a few hours of Python before. Or, they have a good understanding of block-based platforms like Scratch, and would like to start exploring text-based programming languages.

Introducing coding using Python

General admission

Network

Networking

Cisco

This course is an excellent resource to learn network programming using Python. With the help of practical examples, you will learn how to automate networks with Telnet, Secure Shell (SSH), Paramiko, Netmiko, and Network Automation and Programmability Abstraction Layer with Multivendor support (NAPALM).

Python Network Programming for Network Engineers (Python 3)

<strong>This course offers you the exact skills and principles you need to deliver a project using Python along with the tools you can use to create solid Python code. Master the language constructs, tools, and terminology with this carefully designed course for beginners.</strong>
        <p>Python is one of the most popular computer programming languages and this hands-on course for beginners will make it easy for someone who wants to get started with learning Python.

This course takes you through the introduction to the course and the learning objectives. You will learn to get started with Replit and write your first Python program. You will learn to store, process, and compare information in Python as well as learn to tidy messy data. You will learn about variables, strings, dictionaries, indexing, and slicing in Python. Further, you will understand loops in Python along with break, continue, and else functions.

Moving ahead, you will understand error handling in Python, get to know the try-and-catch block, and learn to add resources to Replit. You will also understand function parameters and explore the difference between local and global variables, and positional and keyword parameters. You will learn to work with JSON and clean the data along with various numeric functions such as min, max, and sum.

By the end of the course, you will gain a solid foundation in Python programming and be able to write high-quality code in Python.

All resources and code files are placed here: https://github.com/PacktPublishing/Python-Bootcamp-in-a-day---Python-Programming-for-Beginners</p>
        <h2>What You Will Learn</h2><p>Master Python programming fundamentals<br>Learn how to install Python to get up and running in no time<br>Learn how to process data to create Olympics Medals Tables<br>Solve multiple specific problems for a customer in the real world<br>Learn all about objects and variables in Python<br>Understand functions and function parameters in Python</p>
        <h2>Audience</h2><p>Whether you are a software engineer, software developer, computer programmer, web developer, transitioning into a new role, or simply someone who wants to understand what makes Python tick, this is the place to start. If you are preparing for a Python certification or job role, this course is for you.</p>
        <h2>Approach</h2><p>This course is video based course with no supporting document necessary. It takes you through the fundamentals of Python and teaches you how to use it with a simple tool so you can master the fundamentals in a day.</p>
        <h2>Key Features</h2><p>Be fluent in writing Python code and working with all the fundamentals of the language such as a list, string, function, dictionary, array, set, and much more * Learn to use Python's data analysis capabilities to analyze data from a real-world data source * A complete overview of the basics with exercises to test your knowledge of storing, processing, and storing information</p>
        <h2>Github Repo</h2><p>https://github.com/PacktPublishing/Python-Bootcamp-in-a-day---Python-Programming-for-Beginners</p>
        <h2>About the Author</h2><h3>Paul Ashun</h3><p>Paul Ashun is the CEO, MD, and chief consultant at Pashun Consulting Ltd., specializing in Scrum coaching and leadership within major global organizations. They are the authors of over 10 books on Scrum such as The Power of Scrum in the Real World, Confessions of a Scrum Master as well as the upcoming Agile User Storybook.

He started as a software developer and over ten years later, he became an Agile portfolio manager. He is a certified Scrum Master and a PMO manager. He has led projects for the BBC, General Electric, Oracle, BSkyB, HiT Entertainment, and Razorfish. He has been coaching product owners and business analysts in international blue-chip companies, dating back to 1999, in Agile and Scrum practices such as writing user stories.</p>
        <h2>Course Outline</h2><h4>1. Introduction</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction</p><p style='margin: 0'>This video is an introduction the course and what you can expect from the course.</p></td></tr><tr><td style='padding: 15px;'><p>2. Learning Objectives - Introduction</p><p style='margin: 0'>This video explains the learning objectives of the course.</p></td></tr><tr><td style='padding: 15px;'><p>3. What Is Python?</p><p style='margin: 0'>This video explains what Python is and the need for Python.</p></td></tr><tr><td style='padding: 15px;'><p>4. The Example</p><p style='margin: 0'>This video explains an example of a software engineer working in a media company to support the development team.</p></td></tr></tbody></table><br><h4>2. Getting Set Up</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Learning Objectives - Getting Set Up</p><p style='margin: 0'>This video explains the learning objectives of this section.</p></td></tr><tr><td style='padding: 15px;'><p>2. How to Get Started with Replit</p><p style='margin: 0'>This video explains how to get started with Replit.</p></td></tr><tr><td style='padding: 15px;'><p>3. Writing Your First Python Program-Hello World</p><p style='margin: 0'>This video explains writing your first Python program-Hello World.</p></td></tr></tbody></table><br><h4>3. Storing Information</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Learning Objectives - Storing Information</p><p style='margin: 0'>This video explains the learning objectives of this section.</p></td></tr><tr><td style='padding: 15px;'><p>2. Objects and Variables</p><p style='margin: 0'>This video explains objects and variables in Python using an example of Olympic results.</p></td></tr><tr><td style='padding: 15px;'><p>3. Variable Names</p><p style='margin: 0'>This video explains variable names in Python and the rules to use them.</p></td></tr><tr><td style='padding: 15px;'><p>4. Numbers</p><p style='margin: 0'>This video explains the different types of numbers in Python.</p></td></tr><tr><td style='padding: 15px;'><p>5. Strings</p><p style='margin: 0'>This video explains strings in Python.</p></td></tr><tr><td style='padding: 15px;'><p>6. Showing Output When Running Python</p><p style='margin: 0'>This video explains showing output when running Python.</p></td></tr></tbody></table><br><h4>4. Processing Information</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Learning Objectives - Processing Information</p><p style='margin: 0'>This video explains the learning objectives of the section.</p></td></tr><tr><td style='padding: 15px;'><p>2. Processing Information</p><p style='margin: 0'>This video explains processing information in Python.</p></td></tr><tr><td style='padding: 15px;'><p>3. Indexing</p><p style='margin: 0'>This video explains indexing in Python.</p></td></tr><tr><td style='padding: 15px;'><p>4. Slices</p><p style='margin: 0'>This video explains slices in Python.</p></td></tr><tr><td style='padding: 15px;'><p>5. String Functions</p><p style='margin: 0'>This video explains string functions in Python.</p></td></tr><tr><td style='padding: 15px;'><p>6. The 'input' Function</p><p style='margin: 0'>This video explains the input function in Python.</p></td></tr><tr><td style='padding: 15px;'><p>7. More String Operations</p><p style='margin: 0'>This video explains more string operations in Python.</p></td></tr><tr><td style='padding: 15px;'><p>8. Converting Between Different Types</p><p style='margin: 0'>This video explains converting between different types.</p></td></tr></tbody></table><br><h4>5. Comparing Information</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Learning Objectives - Comparing Information</p><p style='margin: 0'>This video explains the learning objectives of this section.</p></td></tr><tr><td style='padding: 15px;'><p>2. Comparing Information</p><p style='margin: 0'>This video explains comparing information in Python.</p></td></tr></tbody></table><br><h4>6. Tidying Messy Data</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Learning Objectives - Tidying Messy Data</p><p style='margin: 0'>This video explains the learning objectives of this section.</p></td></tr><tr><td style='padding: 15px;'><p>2. Tidying Messy Data</p><p style='margin: 0'>This video explains how to tidy messy data.</p></td></tr></tbody></table><br><h4>7. Storing Multiple Things</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Learning Objectives - Storing Multiple Things</p><p style='margin: 0'>This video explains the learning objectives of this section.</p></td></tr><tr><td style='padding: 15px;'><p>2. Storing Multiple Things</p><p style='margin: 0'>This video explains how to store multiple things.</p></td></tr><tr><td style='padding: 15px;'><p>3. Introducing Python Lists</p><p style='margin: 0'>This video explains lists in Python.</p></td></tr><tr><td style='padding: 15px;'><p>4. Adding Items to a List</p><p style='margin: 0'>This video explains how to add items to a list.</p></td></tr><tr><td style='padding: 15px;'><p>5. Indexing and Slicing Lists</p><p style='margin: 0'>This video explains indexing and slicing lists.</p></td></tr><tr><td style='padding: 15px;'><p>6. Deleting Items in a List</p><p style='margin: 0'>This video explains how to delete items in a list.</p></td></tr><tr><td style='padding: 15px;'><p>7. Tuples</p><p style='margin: 0'>This video explains tuples in Python.</p></td></tr><tr><td style='padding: 15px;'><p>8. Long Lines in Python</p><p style='margin: 0'>This video explains long lines in Python.</p></td></tr><tr><td style='padding: 15px;'><p>9. Dictionaries</p><p style='margin: 0'>This video explains dictionaries in Python.</p></td></tr><tr><td style='padding: 15px;'><p>10. List Functions - More Ways to Work with Lists</p><p style='margin: 0'>This video explains list functions.</p></td></tr><tr><td style='padding: 15px;'><p>11. Sets</p><p style='margin: 0'>This video explains sets in Python.</p></td></tr></tbody></table><br><h4>8. Processing Collections</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Learning Objectives - Processing Collections</p><p style='margin: 0'>This video explains the learning objectives of the section.</p></td></tr><tr><td style='padding: 15px;'><p>2. A Simple 'for' Loop</p><p style='margin: 0'>This video explains a simple for loop.</p></td></tr><tr><td style='padding: 15px;'><p>3. More Complex 'for' loops - 'break', 'continue', and 'else'</p><p style='margin: 0'>This video explains more complex 'for' loops.</p></td></tr><tr><td style='padding: 15px;'><p>4. The 'range' Function - How to Create a List of Numbers</p><p style='margin: 0'>This video explains how to create a list of numbers.</p></td></tr><tr><td style='padding: 15px;'><p>5. The 'while' Loop - Do Something for a While</p><p style='margin: 0'>This video explains the while loop.</p></td></tr></tbody></table><br><h4>9. Robust Programs - Handling Errors</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Learning Objectives - Robust Programs - Handling Errors</p><p style='margin: 0'>This video explains the learning objectives of the section.</p></td></tr><tr><td style='padding: 15px;'><p>2. Robust Programs - Handling Errors</p><p style='margin: 0'>This video explains error handling in Python.</p></td></tr><tr><td style='padding: 15px;'><p>3. Look Before You Leap</p><p style='margin: 0'>This video explains one way of making the code more robust, which is called 'look before you leap'.</p></td></tr><tr><td style='padding: 15px;'><p>4. The Try and Except Block</p><p style='margin: 0'>This video explains the try and except block in Python.</p></td></tr><tr><td style='padding: 15px;'><p>5. The Catch-All Block</p><p style='margin: 0'>This video explains the catch-all block.</p></td></tr><tr><td style='padding: 15px;'><p>6. Adding Resources to Replit</p><p style='margin: 0'>This video explains how to add resources to Replit.</p></td></tr><tr><td style='padding: 15px;'><p>7. The Finally Block</p><p style='margin: 0'>This video explains the finally block.</p></td></tr></tbody></table><br><h4>10. Saving the Results - Working with Files</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Learning Objectives - Saving the Results - Working with Files</p><p style='margin: 0'>This video explains the learning objectives of the course.</p></td></tr><tr><td style='padding: 15px;'><p>2. Adding Bad Data</p><p style='margin: 0'>This video explains adding bad data.</p></td></tr><tr><td style='padding: 15px;'><p>3. Saving the Results - Working with Files</p><p style='margin: 0'>This video explains saving the results and working with files.</p></td></tr><tr><td style='padding: 15px;'><p>4. Binary File Modes</p><p style='margin: 0'>This video explains binary file modes.</p></td></tr><tr><td style='padding: 15px;'><p>5. Text File Modes</p><p style='margin: 0'>This video explains text file modes.</p></td></tr><tr><td style='padding: 15px;'><p>6. The With Statement</p><p style='margin: 0'>This video explains the with statement.</p></td></tr></tbody></table><br><h4>11. Breaking Up Larger Programs, Part 1</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Learning Objectives - Breaking Up Larger Programs, Part 1</p><p style='margin: 0'>This video explains the learning objectives of the section.</p></td></tr><tr><td style='padding: 15px;'><p>2. About Replit.config</p><p style='margin: 0'>This video explains replit.config.</p></td></tr><tr><td style='padding: 15px;'><p>3. Functions</p><p style='margin: 0'>This video explains functions in Python.</p></td></tr><tr><td style='padding: 15px;'><p>4. Function Parameters</p><p style='margin: 0'>This video explains function parameters.</p></td></tr><tr><td style='padding: 15px;'><p>5. Local Versus Global Variables</p><p style='margin: 0'>This video explains local versus global variables.</p></td></tr><tr><td style='padding: 15px;'><p>6. Positional and Keyword Parameters</p><p style='margin: 0'>This video explains positional and keyword parameters.</p></td></tr><tr><td style='padding: 15px;'><p>7. Return Statement</p><p style='margin: 0'>This video explains the return statement.</p></td></tr><tr><td style='padding: 15px;'><p>8. Working With JSON</p><p style='margin: 0'>This video explains working with JSON.</p></td></tr><tr><td style='padding: 15px;'><p>9. Code Comments and Clear Code</p><p style='margin: 0'>This video explains code comments in Python.</p></td></tr></tbody></table><br><h4>12. Summarising and Presenting the Results</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Learning Objectives - Summarising and Presenting the Results</p><p style='margin: 0'>This video explains the learning objectives of the section.</p></td></tr><tr><td style='padding: 15px;'><p>2. Summarising and Presenting the Results Part 1</p><p style='margin: 0'>This video explains how to summarise the results using statistics.</p></td></tr><tr><td style='padding: 15px;'><p>3. Cleaning the Data</p><p style='margin: 0'>This video explains cleaning the data in Python.</p></td></tr><tr><td style='padding: 15px;'><p>4. Summarising and Presenting the Results Part 2</p><p style='margin: 0'>This video explains the code in which we will get a sum of the scores of a country.</p></td></tr><tr><td style='padding: 15px;'><p>5. More Numeric Functions - Min, Max, Sum</p><p style='margin: 0'>This video explains min, max, and sum functions in Python.</p></td></tr><tr><td style='padding: 15px;'><p>6. Formatted Strings, f-strings</p><p style='margin: 0'>This video explains formatted strings and f-strings in Python.</p></td></tr></tbody></table><br><h4>13. Breaking Up Larger Programs, Part 2</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Learning Objectives - Breaking Up Larger Programs, Part 2</p><p style='margin: 0'>This video explains the learning objectives of the section.</p></td></tr><tr><td style='padding: 15px;'><p>2. Splitting Code into Modules</p><p style='margin: 0'>This video explains splitting code into modules.</p></td></tr><tr><td style='padding: 15px;'><p>3. Namespaces</p><p style='margin: 0'>This video explains namespaces in Python.</p></td></tr><tr><td style='padding: 15px;'><p>4. Using Our Modules</p><p style='margin: 0'>This video explains how to use modules in Python.</p></td></tr></tbody></table><br><h4>14. Getting Set Up on a PC or MAC</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Learning Objectives - Getting Set Up on a PC or MAC</p><p style='margin: 0'>This video explains the learning objectives of the section.</p></td></tr><tr><td style='padding: 15px;'><p>2. Getting Set Up</p><p style='margin: 0'>This video explains how to set up Python on our systems.</p></td></tr><tr><td style='padding: 15px;'><p>3. Starting Python on Windows 10</p><p style='margin: 0'>This video explains how to start Python on Windows 10.</p></td></tr><tr><td style='padding: 15px;'><p>4. Starting a Terminal or Command Prompt on Windows</p><p style='margin: 0'>This video explains how to start a terminal or command prompt on Windows.</p></td></tr><tr><td style='padding: 15px;'><p>5. Installing Python on Windows</p><p style='margin: 0'>This video explains the installation of Python on Windows.</p></td></tr><tr><td style='padding: 15px;'><p>6. Installing Python on MacOS</p><p style='margin: 0'>This video explains the installation on Python on MacOS.</p></td></tr><tr><td style='padding: 15px;'><p>7. Quick Python Test - Running Python</p><p style='margin: 0'>This video explains how to run a Python script.</p></td></tr><tr><td style='padding: 15px;'><p>8. Python Scripts and IDLE</p><p style='margin: 0'>This video explains Python scripts and IDE.</p></td></tr><tr><td style='padding: 15px;'><p>9. Code Editors and IDEs</p><p style='margin: 0'>This video explains code editors and IDEs.</p></td></tr><tr><td style='padding: 15px;'><p>10. Running Python Scripts</p><p style='margin: 0'>This video explains how to run Python scripts.</p></td></tr></tbody></table>

This course offers you the exact skills and principles you need to deliver a project using Python along with the tools you can use to create solid Python code. Master the language constructs, tools, and terminology with this carefully designed course for beginners.

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