Name: Data Science & Machine Learning with R
Price: 12 GBP
Availability: InStock

Packt

Statistics

Linear Algebra

Data Science

Probability

Python

Pandas

Start your data science journey with this carefully constructed comprehensive course and get hands-on experience with Python for data science. Gain in-depth knowledge about core Python and essential mathematical concepts in linear algebra, probability, and statistics. Complete data science training with 13+ hours of content.

Data Science 101: Methodology, Python, and Essential Math

General Admission

<div id="course-pills-1">Duration<p>2 Days</p><p>12 CPD hours</p>This course is intended for<p>Audience: Data Scientists, Software Developers, IT Architects, and Technical Managers. Participants should have the general knowledge of statistics and programming<br />Also familiar with Python</p>Overview<p>? NumPy, pandas, Matplotlib,  scikit-learn<br />? Python REPLs<br />? Jupyter Notebooks<br />? Data analytics life-cycle phases<br />? Data repairing and normalizing<br />? Data aggregation and grouping<br />? Data visualization<br />? Data science algorithms for supervised and unsupervised machine learning</p><p>Covers theoretical and technical aspects of using Python in Applied Data Science projects and Data Logistics use cases.</p></div><div id="course-pills-2"><h4>Python for Data Science</h4><ul><li>? Using Modules</li><li>? Listing Methods in a Module</li><li>? Creating Your Own Modules</li><li>? List Comprehension</li><li>? Dictionary Comprehension</li><li>? String Comprehension</li><li>? Python 2 vs Python 3</li><li>? Sets (Python 3+)</li><li>? Python Idioms</li><li>? Python Data Science ?Ecosystem?</li><li>? NumPy</li><li>? NumPy Arrays</li><li>? NumPy Idioms</li><li>? pandas</li><li>? Data Wrangling with pandas' DataFrame</li><li>? SciPy</li><li>? Scikit-learn</li><li>? SciPy or scikit-learn?</li><li>? Matplotlib</li><li>? Python vs R</li><li>? Python on Apache Spark</li><li>? Python Dev Tools and REPLs</li><li>? Anaconda</li><li>? IPython</li><li>? Visual Studio Code</li><li>? Jupyter</li><li>? Jupyter Basic Commands</li><li>? Summary</li></ul><h4>Applied Data Science</h4><ul><li>? What is Data Science?</li><li>? Data Science Ecosystem</li><li>? Data Mining vs. Data Science</li><li>? Business Analytics vs. Data Science</li><li>? Data Science, Machine Learning, AI?</li><li>? Who is a Data Scientist?</li><li>? Data Science Skill Sets Venn Diagram</li><li>? Data Scientists at Work</li><li>? Examples of Data Science Projects</li><li>? An Example of a Data Product</li><li>? Applied Data Science at Google</li><li>? Data Science Gotchas</li><li>? Summary</li></ul><h4>Data Analytics Life-cycle Phases</h4><ul><li>? Big Data Analytics Pipeline</li><li>? Data Discovery Phase</li><li>? Data Harvesting Phase</li><li>? Data Priming Phase</li><li>? Data Logistics and Data Governance</li><li>? Exploratory Data Analysis</li><li>? Model Planning Phase</li><li>? Model Building Phase</li><li>? Communicating the Results</li><li>? Production Roll-out</li><li>? Summary</li></ul><h4>Repairing and Normalizing Data</h4><ul><li>? Repairing and Normalizing Data</li><li>? Dealing with the Missing Data</li><li>? Sample Data Set</li><li>? Getting Info on Null Data</li><li>? Dropping a Column</li><li>? Interpolating Missing Data in pandas</li><li>? Replacing the Missing Values with the Mean Value</li><li>? Scaling (Normalizing) the Data</li><li>? Data Preprocessing with scikit-learn</li><li>? Scaling with the scale() Function</li><li>? The MinMaxScaler Object</li><li>? Summary</li></ul><h4>Descriptive Statistics Computing Features in Python</h4><ul><li>? Descriptive Statistics</li><li>? Non-uniformity of a Probability Distribution</li><li>? Using NumPy for Calculating Descriptive Statistics Measures</li><li>? Finding Min and Max in NumPy</li><li>? Using pandas for Calculating Descriptive Statistics Measures</li><li>? Correlation</li><li>? Regression and Correlation</li><li>? Covariance</li><li>? Getting Pairwise Correlation and Covariance Measures</li><li>? Finding Min and Max in pandas DataFrame</li><li>? Summary</li></ul><h4>Data Aggregation and Grouping</h4><ul><li>? Data Aggregation and Grouping</li><li>? Sample Data Set</li><li>? The pandas.core.groupby.SeriesGroupBy Object</li><li>? Grouping by Two or More Columns</li><li>? Emulating the SQL's WHERE Clause</li><li>? The Pivot Tables</li><li>? Cross-Tabulation</li><li>? Summary</li></ul><h4>Data Visualization with matplotlib</h4><ul><li>? Data Visualization<br />? What is matplotlib?<br />? Getting Started with matplotlib<br />? The Plotting Window<br />? The Figure Options<br />? The matplotlib.pyplot.plot() Function<br />? The matplotlib.pyplot.bar() Function<br />? The matplotlib.pyplot.pie () Function<br />? Subplots<br />? Using the matplotlib.gridspec.GridSpec Object<br />? The matplotlib.pyplot.subplot() Function<br />? Hands-on Exercise<br />? Figures<br />? Saving Figures to File<br />? Visualization with pandas<br />? Working with matplotlib in Jupyter Notebooks<br />? Summary</li></ul><h4>Data Science and ML Algorithms in scikit-learn</h4><ul><li>? Data Science, Machine Learning, AI?</li><li>? Types of Machine Learning</li><li>? Terminology: Features and Observations</li><li>? Continuous and Categorical Features (Variables)</li><li>? Terminology: Axis</li><li>? The scikit-learn Package</li><li>? scikit-learn Estimators</li><li>? Models, Estimators, and Predictors</li><li>? Common Distance Metrics</li><li>? The Euclidean Metric</li><li>? The LIBSVM format</li><li>?  Scaling of the Features</li><li>? The Curse of Dimensionality</li><li>? Supervised vs Unsupervised Machine Learning</li><li>? Supervised Machine Learning Algorithms</li><li>? Unsupervised Machine Learning Algorithms</li><li>? Choose the Right Algorithm</li><li>? Life-cycles of Machine Learning Development</li><li>? Data Split for Training and Test Data Sets</li><li>? Data Splitting in scikit-learn</li><li>? Hands-on Exercise</li><li>? Classification Examples</li><li>? Classifying with k-Nearest Neighbors (SL)</li><li>? k-Nearest Neighbors Algorithm</li><li>? k-Nearest Neighbors Algorithm</li><li>? The Error Rate</li><li>? Hands-on Exercise</li><li>? Dimensionality Reduction</li><li>? The Advantages of Dimensionality Reduction</li><li>? Principal component analysis (PCA)</li><li>? Hands-on Exercise</li><li>? Data Blending</li><li>? Decision Trees (SL)</li><li>? Decision Tree Terminology</li><li>? Decision Tree Classification in Context of Information Theory</li><li>? Information Entropy Defined</li><li>? The Shannon Entropy Formula</li><li>? The Simplified Decision Tree Algorithm</li><li>? Using Decision Trees</li><li>? Random Forests</li><li>? SVM</li><li>? Naive Bayes Classifier (SL)</li><li>? Naive Bayesian Probabilistic Model in a Nutshell</li><li>? Bayes Formula</li><li>? Classification of Documents with Naive Bayes</li><li>? Unsupervised Learning Type: Clustering</li><li>? Clustering Examples</li><li>? k-Means Clustering (UL)</li><li>? k-Means Clustering in a Nutshell</li><li>? k-Means Characteristics</li><li>? Regression Analysis</li><li>? Simple Linear Regression Model</li><li>? Linear vs Non-Linear Regression</li><li>? Linear Regression Illustration</li><li>? Major Underlying Assumptions for Regression Analysis</li><li>? Least-Squares Method (LSM)</li><li>? Locally Weighted Linear Regression</li><li>? Regression Models in Excel</li><li>? Multiple Regression Analysis</li><li>? Logistic Regression</li><li>? Regression vs Classification</li><li>? Time-Series Analysis</li><li>? Decomposing Time-Series</li><li>? Summary</li></ul><h4>Lab Exercises</h4><ul><li>Lab 1 - Learning the Lab Environment     </li><li>Lab 2 -  Using Jupyter Notebook </li><li>Lab 3 -  Repairing and Normalizing Data  </li><li>Lab 4 -  Computing Descriptive Statistics </li><li>Lab 5 - Data Grouping and Aggregation   </li><li>Lab 6 - Data Visualization with matplotlib              </li><li>Lab 7 - Data Splitting       </li><li>Lab 8 -  k-Nearest Neighbors Algorithm  </li><li>Lab 9 -  The k-means Algorithm  </li><li>Lab 10 -  The Random Forest Algorithm </li></ul></div>

Nexus Human

Data Engineering

Machine Learning (ML)

Big Data Analytics

Data Mining

Data Skills

Python With Data Science

Janets

Online Course Creation

Computing Skills

R (programming language)

R Programming for Data Science

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			<h2>Overview
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					<p><span>This comprehensive course on <b>Quick Data Science Approach from Scratch</b> 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 <b>Quick Data Science Approach from Scratch</b> 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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					<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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					<p><span>There is no experience or previous qualifications required for enrolment on this <b>Quick Data Science Approach from Scratch</b>. It is available to all students, of all academic backgrounds.</span></p>					</div>
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					<p><span>Our <b>Quick Data Science Approach from Scratch</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.</span></p><p><span>There is no time limit for completing this course, it can be studied in your own time at your own pace.</span></p>					</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>Open doors of opportunities</li><li>Increase your adaptability</li><li>Keep you relevant</li><li>Boost confidence</li></ul><p>And much more!</p>					</div>
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					</div> <h3>Course Curriculum</h3><div><p>4 sections • 15 lectures • 01:00:00 total length</p></div><div><div><div><div><div><div><div><p>•Introduction: 00:02:00</p></div><div><div><p>•Data Science Explanation: 00:05:00</p></div><div><div><p>•Need of Data Science: 00:02:00</p></div><div><div><p>•8 Common mistakes by Aspiring Data Scientists/Data Science Enthusiasts: 00:08:00</p></div><div><div><p>•Myths about Data Science: 00:03:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Data Types and Variables: 00:04:00</p></div><div><div><p>•Descriptive Analysis: 00:02:00</p></div><div><div><p>•Data Cleaning: 00:02:00</p></div><div><div><p>•Feature Engineering: 00:02:00</p></div><div><div><p>•Data Thinking Development: 00:03:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Problem Definition: 00:05:00</p></div><div><div><p>•Algorithms: 00:14:00</p></div><div><div><p>•Prediction: 00:03:00</p></div><div><div><p>•Learning Methods: 00:05:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Assignment - Quick Data Science Approach from Scratch: 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>

Apex Learning

Professional Skills Course (PSC)

Trainers Course

Digital Skills

Quick Data Science Approach from Scratch

<h2 style="color: var(--text-heading); box-sizing: border-box;" id="isPasted" fr-original-style="color: var(--text-heading);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><span style="font-size: 24px; box-sizing: border-box;" fr-original-style="font-size: 24px;">This course at a glance</span></strong></h2><ul style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color: rgb(0, 0, 0);"><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color: rgb(0, 0, 0);">Accredited by CPDQE</li><li id="isPasted" fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(38, 99, 82) !important; box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">Set up and configure a data science environment, ensuring optimal productivity and efficiency in data analysis workflows.</span></li><li fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(38, 99, 82) !important; box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">Utilize the powerful features of the NumPy package for efficient manipulation and computation of numerical data.</span></li><li fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(38, 99, 82) !important; box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">Harness the capabilities of the Pandas package for data manipulation, exploration, and analysis, enabling insightful decision-making.</span></li><li fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(38, 99, 82) !important; box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">Create visually compelling data visualizations using Matplotlib, mastering both basic and advanced plotting techniques.</span></li><li fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(38, 99, 82) !important; box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">Apply data analysis and visualization techniques to real-world datasets, deriving actionable insights to drive business success.</span></li></ul><div data-id="4afcd14" data-element_type="widget" data-widget_type="text-editor.default" style="color: rgb(35, 35, 35); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(35, 35, 35);"><div data-id="4afcd14" data-element_type="widget" data-widget_type="text-editor.default" style="color: rgb(35, 35, 35); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(35, 35, 35);"><div data-id="4afcd14" data-element_type="widget" data-widget_type="text-editor.default" style="color: rgb(35, 35, 35); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(35, 35, 35);"><div data-id="4afcd14" data-element_type="widget" data-widget_type="text-editor.default" style="color: rgb(35, 35, 35); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(35, 35, 35);"><div data-id="4afcd14" data-element_type="widget" data-widget_type="text-editor.default" style="color: rgb(35, 35, 35); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(35, 35, 35);"><div data-id="4afcd14" data-element_type="widget" data-widget_type="text-editor.default" style="color: rgb(35, 35, 35); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(35, 35, 35);"><p style="color: rgb(38, 99, 82) !important; font-size: var(--font-size); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(38, 99, 82) !important;">Embark on a transformative journey into the world of data with our &ldquo;Data Science and Data Analytics&rdquo; course. Designed for aspiring data professionals and analysts, this comprehensive program equips you with the essential tools and techniques to excel in the dynamic field of data science. From setting up your data science environment to mastering powerful packages like NumPy, Pandas, and Matplotlib, this course covers all facets of data analysis and visualization, empowering you to unlock actionable insights and drive informed decision-making.</p><p style="color: rgb(38, 99, 82) !important; font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">Uncover the foundations of data science in the introductory modules, where you&rsquo;ll learn to navigate the data science environment and harness the capabilities of essential tools like NumPy and Pandas. Dive deeper into data visualization with comprehensive tutorials on Matplotlib, exploring advanced techniques to create compelling visual representations of your data. Whether you&rsquo;re a novice eager to enter the world of data or an experienced professional seeking to enhance your skill set, this course is your gateway to mastering the art and science of data analytics.</p></div></div></div></div></div></div><h3 style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);"><span style="font-size: 24px; box-sizing: border-box;" fr-original-style="font-size: 24px;">Accredited by</span></h3><p style="color: rgb(15, 21, 26); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(15, 21, 26);">This course is <strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">CPDQE&nbsp;</strong>accredited, which serves as an impactful mechanism for skill enhancement.&nbsp;</p><p style="color: rgb(0, 0, 0); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">Continuing Professional Development (CPD) stands as a crucial, widely acknowledged method that aids individuals, organisations, and entire industries in staying current with their skills and knowledge.</p><p style="color: rgb(0, 0, 0); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">CPD not only facilitates the elevation of global standards and benchmarks, aligning with the growing forces of globalisation and consumer expectations but also transforms learning into a deliberate and proactive process. It motivates professionals to uphold a consistently high level of performance and demonstrates their unwavering commitment to a specific job role or profession.</p><p style="color: rgb(0, 0, 0); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><span style="font-size: 24px; box-sizing: border-box;" fr-original-style="font-size: 24px;">Course Curriculum</span></strong></p><ul fr-original-style="" style="box-sizing: border-box;"><li id="isPasted" style="font-weight: bold; box-sizing: border-box;" fr-original-style="font-weight: bold;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Introduction to Data Science &nbsp; &nbsp; &nbsp; &nbsp;</strong></li><li style="font-weight: bold; box-sizing: border-box;" fr-original-style="font-weight: bold;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Science Environment setup &nbsp; &nbsp; &nbsp; &nbsp;</strong></li><li style="font-weight: bold; box-sizing: border-box;" fr-original-style="font-weight: bold;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Working with the Numpy package &nbsp; &nbsp; &nbsp; &nbsp;</strong></li><li style="font-weight: bold; box-sizing: border-box;" fr-original-style="font-weight: bold;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Working with Pandas Data science package &nbsp; &nbsp; &nbsp; &nbsp;</strong></li><li style="font-weight: bold; box-sizing: border-box;" fr-original-style="font-weight: bold;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Working with Matplotlib Data Science package part &ndash; 1 &nbsp; &nbsp; &nbsp; &nbsp;</strong></li><li style="font-weight: bold; box-sizing: border-box;" fr-original-style="font-weight: bold;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Working with Matplotlib Data Science part &ndash; 2</strong></li></ul>

LearnDrive UK

Engineering Management

Electrical engineering (EE)

Unlock the power of data with our “Data Science and Data Analytics” course. From setting up your data science environment to mastering essential packages like NumPy, Pandas, and Matplotlib, this program empowers you to analyze, visualize, and derive actionable insights from data.





























Online Data Science & Data Analytics Course with Certificate

<h3><b>Overview</b></h3>
<p><span>In the era where information is abundant and decisions are driven by data, have you ever pondered, 'what is machine learning?' or 'what is data science?' Dive into the realm of '</span><strong><span>Data Science &amp; Machine Learning with R from A-Z</span></strong><span>,' a comprehensive guide to unravel these complexities. This course effortlessly blends the foundational aspects of data science with the intricate depths of machine learning algorithms, all through the versatile medium of R. As the digital economy booms, the demand for machine learning jobs continues to surge. Equip yourself with the proficiency to navigate this dynamic field and transition from being an inquisitive mind to a sought-after professional in the space of data science and machine learning with R.</span></p>
<p><strong><span>Learning Outcomes:</span></strong></p>
<ol>
<li><span>Understand the foundational concepts of data science and machine learning.</span></li>
<li><span>Familiarise oneself with the R environment and its functionalities.</span></li>
<li><span>Master data types, structures, and advanced techniques in R.</span></li>
<li><span>Acquire proficiency in data manipulation and visual representation using R.</span></li>
<li><span>Generate comprehensive reports using R Markdown and design web applications with R Shiny.</span></li>
<li><span>Gain a thorough understanding of machine learning methodologies and their applications.</span></li>
<li><span>Gain insights into initiating a successful career in the data science sector.</span></li>
</ol>
<h3><b>Why buy this Data Science &amp; Machine Learning with R from A-Z course?</b></h3>
<ol>
<li><span>Unlimited access to the course for forever</span></li>
<li><b>Digital Certificate, Transcript, student ID</b><span> all included in the price</span></li>
<li><span>Absolutely no hidden fees</span></li>
<li><span>Directly receive </span><b>CPD </b><span>accredited qualifications after course completion</span></li>
<li><span>Receive one to one assistance on every weekday from professionals</span></li>
<li><span>Immediately receive the PDF certificate after passing</span></li>
<li><span>Receive the original copies of your certificate and transcript on the next working day</span></li>
<li><span>Easily learn the skills and knowledge from the comfort of your home</span></li>
</ol>
<h3><b>Certification</b></h3>
<p><span>After studying the course materials of the </span><b>Data Science &amp; Machine Learning with R from A-Z</b><span> there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60.</span></p>
<h3><b>Who is this Data Science &amp; Machine Learning with R from A-Z course for?</b></h3>
<p><span>This </span><span>course is ideal for</span></p>
<ul>
<li><span>Individuals keen on exploring the intricacies of machine learning and data science.</span></li>
<li><span>Aspiring data analysts and scientists looking to specialise in Machine Learning with R.</span></li>
<li><span>IT professionals aiming to diversify their skill set in the emerging data-driven market.</span></li>
<li><span>Researchers seeking to harness the power of R for data representation and analysis.</span></li>
<li><span>Academics and students aiming to bolster their understanding of modern data practices with R.</span></li>
</ul>
<h3><b>Prerequisites</b></h3>
<p><span>This </span><b>Data Science &amp; Machine Learning with R from A-Z</b><span> does not require you to have any prior qualifications or experience. You can just enrol and start learning.This </span><b>Data Science &amp; Machine Learning with R from A-Z</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>Career path</b></h3>
<ol>
<li><strong><span>Data Scientist</span></strong><span> - Average salary range: £35,000 - £70,000 Per Annum</span></li>
<li><strong><span>Machine Learning Engineer</span></strong><span> - Average salary range: £50,000 - £80,000 Per Annum</span></li>
<li><strong><span>Data Analyst</span></strong><span> - Average salary range: £28,000 - £55,000 Per Annum</span></li>
<li><strong><span>R Developer</span></strong><span> - Average salary range: £30,000 - £60,000 Per Annum</span></li>
<li><strong><span>R Shiny Web Developer</span></strong><span> - Average salary range: £32,000 - £65,000 Per Annum</span></li>
<li><strong><span>Machine Learning Researcher</span></strong><span> - Average salary range: £40,000 - £75,000 Per Annum</span></li>
</ol><div>
				<h3>
	<span>Course Curriculum</span>
</h3>

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					<td colspan="4"> Data Science and Machine Learning Course Intro</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Data Science and Machine Learning Introduction</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>What is Data Science</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Machine Learning Overview</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Who is This Course for</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Data Science and Machine Learning Marketplace</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Data Science and Machine Learning Job Opportunities</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Getting Started with R</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Getting Started</td>
					<td> </td>
					<td><span><i></i> 00:11:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Basics</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Files</td>
					<td> </td>
					<td><span><i></i> 00:11:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>RStudio</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Tidyverse</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Resources</td>
					<td> </td>
					<td><span><i></i> 00:04:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Data Types and Structures in R</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Unit Introduction</td>
					<td> </td>
					<td><span><i></i> 00:30:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Basic Type</td>
					<td> </td>
					<td><span><i></i> 00:09:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Vector Part One</td>
					<td> </td>
					<td><span><i></i> 00:20:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Vectors Part Two</td>
					<td> </td>
					<td><span><i></i> 00:25:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Vectors - Missing Values</td>
					<td> </td>
					<td><span><i></i> 00:16:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Vectors - Coercion</td>
					<td> </td>
					<td><span><i></i> 00:14:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Vectors - Naming</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Vectors - Misc</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Creating Matrics</td>
					<td> </td>
					<td><span><i></i> 00:31:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>List</td>
					<td> </td>
					<td><span><i></i> 00:32:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Introduction to Data Frames</td>
					<td> </td>
					<td><span><i></i> 00:19:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Creating Data Frames</td>
					<td> </td>
					<td><span><i></i> 00:20:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Data Frames: Helper Functions</td>
					<td> </td>
					<td><span><i></i> 00:31:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Data Frames Tibbles</td>
					<td> </td>
					<td><span><i></i> 00:39:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Intermediate R</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Intermediate Introduction</td>
					<td> </td>
					<td><span><i></i> 00:47:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Relational Operations</td>
					<td> </td>
					<td><span><i></i> 00:11:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Conditional Statements</td>
					<td> </td>
					<td><span><i></i> 00:11:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Loops</td>
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Functions</td>
					<td> </td>
					<td><span><i></i> 00:14:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Packages</td>
					<td> </td>
					<td><span><i></i> 00:11:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Factors</td>
					<td> </td>
					<td><span><i></i> 00:28:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Dates and Times</td>
					<td> </td>
					<td><span><i></i> 00:30:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Functional Programming</td>
					<td> </td>
					<td><span><i></i> 00:37:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Data Import or Export</td>
					<td> </td>
					<td><span><i></i> 00:22:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Database</td>
					<td> </td>
					<td><span><i></i> 00:27:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Data Manipulation in R</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Data Manipulation in R Introduction</td>
					<td> </td>
					<td><span><i></i> 00:36:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Tidy Data</td>
					<td> </td>
					<td><span><i></i> 00:11:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>The Pipe Operator</td>
					<td> </td>
					<td><span><i></i> 00:15:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>The Filter Verb</td>
					<td> </td>
					<td><span><i></i> 00:22:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>The Select Verb</td>
					<td> </td>
					<td><span><i></i> 00:46:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>The Mutate Verb</td>
					<td> </td>
					<td><span><i></i> 00:32:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>The Arrange Verb</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>The Summarize Verb</td>
					<td> </td>
					<td><span><i></i> 00:23:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Data Pivoting</td>
					<td> </td>
					<td><span><i></i> 00:43:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>JSON Parsing</td>
					<td> </td>
					<td><span><i></i> 00:11:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>String Manipulation</td>
					<td> </td>
					<td><span><i></i> 00:33:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Web Scraping</td>
					<td> </td>
					<td><span><i></i> 00:59:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Data Visualization in R</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Data Visualization in R Section Intro</td>
					<td> </td>
					<td><span><i></i> 00:17:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Getting Started</td>
					<td> </td>
					<td><span><i></i> 00:16:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Aesthetics Mappings</td>
					<td> </td>
					<td><span><i></i> 00:25:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Single Variable Plots</td>
					<td> </td>
					<td><span><i></i> 00:37:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Two Variable Plots</td>
					<td> </td>
					<td><span><i></i> 00:21:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Facets, Layering, and Coordinate Systems</td>
					<td> </td>
					<td><span><i></i> 00:18:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Styling and Saving</td>
					<td> </td>
					<td><span><i></i> 00:12:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Creating Reports with R Markdown</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Creating with R Markdown</td>
					<td> </td>
					<td><span><i></i> 00:29:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Building Webapps with R Shiny</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Introduction to R Shiny</td>
					<td> </td>
					<td><span><i></i> 00:26:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>A Basic R Shiny App</td>
					<td> </td>
					<td><span><i></i> 00:31:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Other Examples with R Shiny</td>
					<td> </td>
					<td><span><i></i> 00:34:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Introduction to Machine Learning</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Machine Learning Part 1</td>
					<td> </td>
					<td><span><i></i> 00:22:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Machine Learning Part 2</td>
					<td> </td>
					<td><span><i></i> 00:47:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Starting A Career in Data Science</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Starting a Data Science Career Section Overview</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Data Science Resume</td>
					<td> </td>
					<td><span><i></i> 00:04:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Getting Started with Freelancing</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Top Freelance Websites</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Personal Branding</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Importance of Website and Blo</td>
					<td> </td>
					<td><span><i></i> 00:04:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Networking Do's and Don'ts</td>
					<td> </td>
					<td><span><i></i> 00:04:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Assignment</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Assignment - Data Science &amp; Machine Learning with R</td>
					<td> </td>
					<td><span><i></i> 00:00:00</span></td>
				</tr>
				</tbody></table></div>

			</div>

Studyhub UK

Data Science & Machine Learning with R from A-Z

<p dir="ltr" id="isPasted" fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color:#000000;">Python for Data Science and Machine Learning Bootcamp course is a comprehensive and practical online course designed to teach you how to use Python for data science and machine learning.&nbsp;</span></p><p dir="ltr" fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color:#000000;">The course comprises several sections, each covering different topics in data science and machine learning. It includes all the essential concepts and tools required to analyse and manipulate data, build machine learning models, and make predictions or decisions.</span></p><p dir="ltr" fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color:#000000;">It also covers dataset summary statistics and visualisation techniques using libraries like matplotlib and seaborn. You&#39;ll learn about model selection, ensemble approaches, and parameter adjustment. Additionally, you will discover how to export and load machine learning models using libraries such as pickle and joblib.</span></p><p dir="ltr" fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color:#000000;">This course is suitable for anyone interested in learning Python for data science and machine learning. Whether you are an aspiring data scientist or a professional looking to enhance your data analysis skills, this course will help you achieve your goals.</span></p><p dir="ltr" fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color:#000000;">Enrol now to gain instant access to the course materials and start your learning journey. Don&#39;t miss out on the opportunity to acquire one of the most in-demand skills in the market today and become a proficient data scientist and machine learning expert.</span></p><h2 dir="ltr" id="isPasted" fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color:#000000;">Learning Outcome of Python for Data Science and Machine Learning Bootcamp &nbsp; &nbsp;</span></h2><ul fr-original-style="" style="box-sizing: border-box;"><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Master fundamental concepts of machine learning and its applications.</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Gain proficiency in Python programming for data analysis and manipulation.</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Learn to load, read, and manipulate CSV data files using Python libraries.</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Understand dataset summary statistics and visualization techniques.</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Acquire skills in data preparation and preprocessing.</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Explore feature selection techniques and their importance.</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Evaluate machine learning algorithms using various techniques and metrics.</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Spot check classification and regression algorithms for model selection.</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Improve model performance using ensemble methods and parameter tuning.</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Learn to export, save, load, and finalize machine learning models for real-time predictions.</li></ul><h2 dir="ltr" fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color:#000000;">Key Features of the Course</span></h2><ul fr-original-style="" style="box-sizing: border-box;"><li dir="ltr" style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">A CPD certificate that is recognised worldwide.</li><li dir="ltr" style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">A great online learning experience.</li><li dir="ltr" style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Interesting and unique online materials and activities.</li><li dir="ltr" style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Expert guidance and support from the field leaders.</li><li dir="ltr" style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Access to the study resources anytime you want.</li><li dir="ltr" style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Friendly and helpful customer service and admin support by email, phone, and chat from Monday through Friday.</li><li dir="ltr" style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Get a year-long access to the course.</li></ul><h2 dir="ltr" fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color:#000000;">Who is this course for</span></h2><p dir="ltr" fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span style="color: rgb(0, 0, 0); font-size: 16px; box-sizing: border-box;" fr-original-style="color: rgb(0, 0, 0); font-size: 16px;">This Python for Data Science and Machine Learning Bootcamp Course is suitable for -</span></p><ul fr-original-style="" style="box-sizing: border-box;"><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Aspiring data scientists and machine learning enthusiasts</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Professionals seeking to enhance their data analysis skills</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Individuals interested in Python programming for data science</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Anyone looking to break into the field of data science and machine learning</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Students pursuing studies in computer science or related fields</li></ul><h2 dir="ltr" fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color:#000000;">Requirements</span></h2><ul fr-original-style="" style="box-sizing: border-box;"><li id="isPasted" style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Basic understanding of programming concepts</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Familiarity with Python programming language is beneficial but not mandatory</li><li dir="ltr" style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">No prerequisites; suitable for individuals from any academic background.</li><li dir="ltr" style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Accessible course materials from any internet-enabled device.</li></ul><h2 dir="ltr" fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color:#000000;">CPD Certificate from Course Gate</span></h2><p dir="ltr" fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color:#000000;">At the successful completion of the course, you can obtain your CPD certificate from us. You can order the PDF certificate for &pound;9 and the hard copy for &pound;15. Also, you can order both PDF and hardcopy certificates for &pound;22.</span></p><h2 dir="ltr" fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color:#000000;">Career path</span><span style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color: rgb(0, 0, 0);"><br fr-original-style="" style="box-sizing: border-box;"></span></h2><div style="color: rgb(68, 68, 68); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(68, 68, 68);"><div style="color: rgb(68, 68, 68); box-sizing: border-box;" fr-original-style=" color: rgb(68, 68, 68);"><div data-elementor-type="wp-post" data-elementor-id="357815" data-elementor-post-type="course" fr-original-style="" style="box-sizing: border-box;"><section data-id="5767f71a" data-element_type="section" fr-original-style="" style="box-sizing: border-box;"><div data-id="58784751" data-element_type="column" fr-original-style="" style="box-sizing: border-box;"><div data-id="ce105db" data-element_type="widget" data-widget_type="text-editor.default" style="color: var( --e-global-color-text ); box-sizing: border-box;" fr-original-style=" color: var( --e-global-color-text );"><ul fr-original-style="" style="box-sizing: border-box;"><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Data Scientist</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Data Analyst</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Machine Learning Engineer</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Business Intelligence Analyst</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Data Engineer</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Research Scientist</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Quantitative Analyst</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Artificial Intelligence Specialist</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Data Consultant</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Statistician</li></ul></div></div></section></div></div></div>

Course Gate

Python for Data Science and Machine Learning Bootcamp online course is suitable for anyone interested in learning Python for data science and machine learning. It is especially ideal for aspiring data scientists and professionals seeking to enhance their data analysis skills. 

Python for Data Science and Machine Learning Bootcamp

<strong>In this compact intermediate-level course, you will learn how to use Facebook Prophet to do time series analysis and forecasting. You will learn how Prophet works under the hood and the Prophet API. We will apply Prophet to a variety of datasets, including store sales and stock prices.</strong>
        <p>Prophet enables Python and R developers to build scalable time series forecasts. This course will help you implement Prophet's cutting-edge forecasting techniques to model future data with higher accuracy and with very few lines of code.

In this course, you will learn how to use Facebook Prophet to do time series analysis and forecasting. You will learn how the Prophet works under the hood (that is, what are its modeling assumptions?) and the Prophet API (that is, how to write the code).

This course is a practice-oriented course, demonstrating how to prepare your data for Prophet, fit a model, and use it to forecast, analyze the results, and evaluate the model's predictions. We will apply Prophet to a variety of datasets, including store sales and stock prices. You will learn how to use Prophet to plot the model's in-sample predictions and forecast. Then, learn how to plot the components of the fitted model. You will also learn how to deal with outliers, missing data, and non-daily (for example, monthly) data.

By the end of this course, you will be able to use Prophet confidently to forecast your data.</p>
        <h2>What You Will Learn</h2><p>Prepare your data (a Pandas dataframe) for Facebook Prophet<br>Learn how to fit a Prophet model to a time series<br>Plot the components of the fitted model<br>Model holidays and exogenous regressors<br>Evaluate your model with forecasting metrics<br>Learn how to do changepoint detection with Prophet</p>
        <h2>Audience</h2><p>Anyone interested in data science, machine learning, or who wishes to use time series analysis on their own data should take this course. Good Python programming skills are required, as well as knowledge of Pandas, Dataframes, and preferably some familiarity with Scikit-Learn, though this is not required.</p>
        <h2>Approach</h2><p>This course is a learn-by-doing course where you will learn how to prepare your data for Prophet, fit a model, and use it to forecast, analyze the results, and evaluate the model's predictions. The course is well-balanced with both theoretical and practical coding exercises. In each section, we first cover the theory concept and demonstrate it using a real-world example for better understanding.</p>
        <h2>Key Features</h2><p>Teaches how to make a forecast using Prophet * Explains how to use Prophet to predict stock prices * Covers how to use Prophet to plot the model's in-sample predictions and forecast</p>
        
        <h2>About the Author</h2><h3>Lazy Programmer</h3><p>The Lazy Programmer is an AI/ML engineer focusing on deep learning with experience in data science, big data engineering, and full-stack development. With a background in computer engineering and specialization in ML, he holds two master's degrees in computer engineering and statistics with finance applications. His online advertising and digital media expertise include data science and big data.

He has created DL models for prediction and has experience in recommender systems using reinforcement learning and collaborative filtering. He is a skilled instructor who has taught at universities including Columbia, NYU, Hunter College, and The New School. He is a web programmer with experience in Python, Ruby/Rails, PHP, and Angular.</p>
        <h2>Course Outline</h2><h4>1. Welcome</h4><p>Welcome to the course! In this section, we will get introduced to the course goals.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction</p><p style='margin: 0'>In this video, we will introduce Facebook Prophet and understand the course learning objective.</p></td></tr><tr><td style='padding: 15px;'><p>2. Outline</p><p style='margin: 0'>In this video, we will understand the course learning approach and what is required to start with this course. Then we will also understand what is covered in this course.</p></td></tr></tbody></table><br><h4>2. Time Series Basics</h4><p>In this section, we will talk about time series basics.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Time Series Basics Section Introduction</p><p style='margin: 0'>In this video, we will get introduced to time series and understand some basics.</p></td></tr><tr><td style='padding: 15px;'><p>2. Forecasting Metrics</p><p style='margin: 0'>In this video, we will understand how to forecast metrics.</p></td></tr><tr><td style='padding: 15px;'><p>3. The Naive Forecast and the Importance of Baselines</p><p style='margin: 0'>In this video, we will discuss baselines and naïve forecast.</p></td></tr><tr><td style='padding: 15px;'><p>4. Walk-Forward Validation</p><p style='margin: 0'>In this video, we will discuss the concept of walk-forward validation.</p></td></tr><tr><td style='padding: 15px;'><p>5. Suggestion Box</p><p style='margin: 0'>In this video, we will take a look at the suggestion box where we can add feedback for this course.</p></td></tr></tbody></table><br><h4>3. Facebook Prophet</h4><p>In this section, we will explore Facebook Prophet.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. How Does Prophet Work?</p><p style='margin: 0'>In this video, we will understand concepts behind Facebook Prophet and understand how it works.</p></td></tr><tr><td style='padding: 15px;'><p>2. Prophet: Code Preparation</p><p style='margin: 0'>In this video, we will go through the code structure for Prophet.</p></td></tr><tr><td style='padding: 15px;'><p>3. Prophet in Code: Data Preparation</p><p style='margin: 0'>In this video, we will work on data preparation with Prophet.</p></td></tr><tr><td style='padding: 15px;'><p>4. Prophet in Code: Fit, Forecast, Plot</p><p style='margin: 0'>In this video, you will learn how to fit, forecast, and plot our data.</p></td></tr><tr><td style='padding: 15px;'><p>5. Prophet in Code: Holidays and Exogenous Regressors</p><p style='margin: 0'>In this video, you will learn how to add holidays and exogenous regressors to our data.</p></td></tr><tr><td style='padding: 15px;'><p>6. Prophet in Code: Cross-Validation</p><p style='margin: 0'>In this video, you will learn how to do cross-validation with Prophet.</p></td></tr><tr><td style='padding: 15px;'><p>7. Prophet in Code: Changepoint Detection</p><p style='margin: 0'>In this video, you will learn how to detect changepoint with Prophet.</p></td></tr><tr><td style='padding: 15px;'><p>8. Prophet: Multiplicative Seasonality, Outliers, Non-Daily Data</p><p style='margin: 0'>In this video, we will work on multiplicative seasonality, outliers, and non-daily data with Prophet.</p></td></tr><tr><td style='padding: 15px;'><p>9. (The Dangers of) Prophet for Stock Price Prediction</p><p style='margin: 0'>In this video, we will work with Prophet for stock price prediction.</p></td></tr><tr><td style='padding: 15px;'><p>10. Prophet Section Summary</p><p style='margin: 0'>In this video, we will summarize what we have learnt in this section.</p></td></tr></tbody></table>

In this compact intermediate-level course, you will learn how to use Facebook Prophet to do time series analysis and forecasting. You will learn how Prophet works under the hood and the Prophet API. We will apply Prophet to a variety of datasets, including store sales and stock prices.

Data Science - Time Series Forecasting with Facebook Prophet in Python

<strong>This course will be mainly focusing on machine learning algorithms. Throughout this course, we are preparing our machine to make it ready for a prediction test.</strong>
        <p>Artificial intelligence, machine learning, and deep learning neural networks are the most used terms in the technology world today. They're also the most misunderstood and confused terms. Artificial intelligence is a broad spectrum of science that tries to make machines intelligent like humans, while machine learning and neural networks are two subsets that sit within this vast machine learning platform. But in this course, you will focus mainly on machine learning, which will include preparing your machine to make it ready for a prediction test.
You will be using Python as your programming language. Python is a great tool for the development of programs that perform data analysis and prediction. It has a variety of classes and features that perform complex mathematical analyses and provide solutions in just a few lines of code, making it easier for you to get up to speed with data science and machine learning.

Machine learning and data science jobs are among the most lucrative in the technology industry in recent times. Exploring this course will help you get well-versed with essential concepts and prepare you for a career in these fields.

All the code and supporting files for this course are available at https://github.com/PacktPublishing/Machine-Learning-and-Data-Science-with-Python-A-Complete-Beginners-Guide</p>
        <h2>What You Will Learn</h2><p>Install Python and required libraries<br>Choose the best machine learning model<br>Automate and combine workflows with pipeline<br>Look at performance improvement with ensembles<br>Study performance improvement with algorithm parameter tuning<br>Finalize a machine learning project</p>
        <h2>Audience</h2><p>This course is for beginners who are interested in machine learning using Python.</p>
        <h2>Approach</h2><p>An exhaustive course packed with step-by-step instructions, working examples, and helpful advice. This course is divided into clear chunks so you can learn at your own pace and focus on your own area of interest.</p>
        <h2>Key Features</h2><p>Learn machine learning and data science using Python * A practical course designed for beginners who are interested in machine learning using Python * Work on predictions and case studies</p>
        <h2>Github Repo</h2><p>https://github.com/packtpublishing/machine-learning-and-data-science-with-python-a-complete-beginners-guide</p>
        <h2>About the Author</h2><h3>Abhilash Nelson </h3><p>Abhilash Nelson is a pioneering, talented, and security-oriented Android/iOS mobile and PHP/Python web application developer with more than eight years of IT experience involving designing, implementing, integrating, testing, and supporting impactful web and mobile applications. He has a master's degree in computer science and engineering and has PHP/Python programming experience, which is an added advantage for server-based Android and iOS client applications. Abhilash is currently a senior solution architect managing projects from start to finish to ensure high quality and innovative and functional design.</p>
        <h2>Course Outline</h2><h4>1. Course Overview and Table of Contents</h4><p></p><br><h4>2. Introduction to Machine Learning</h4><p></p><br><h4>3. System and Environment Preparation</h4><p></p><br><h4>4. Learn Basics of Python</h4><p></p><br><h4>5. Learn Basics of NumPy</h4><p></p><br><h4>6. Learn Basics of Matplotlib</h4><p></p><br><h4>7. Learn Basics of Pandas</h4><p></p><br><h4>8. Understanding the CSV Data File</h4><p></p><br><h4>9. Load and Read CSV Data File</h4><p></p><br><h4>10. Dataset Summary</h4><p></p><br><h4>11. Dataset Visualization</h4><p></p><br><h4>12. Data Preparation</h4><p></p><br><h4>13. Feature Selection</h4><p></p><br><h4>14. Refresher Session - the Mechanism of Re-Sampling, Training, and Testing</h4><p></p><br><h4>15. Algorithm Evaluation Techniques</h4><p></p><br><h4>16. Algorithm Evaluation Metrics</h4><p></p><br><h4>17. Classification Algorithm Spot Check - Logistic Regression</h4><p></p><br><h4>18. Classification Algorithm Spot Check - Linear Discriminant Analysis</h4><p></p><br><h4>19. Classification Algorithm Spot Check - K-Nearest Neighbors</h4><p></p><br><h4>20. Classification Algorithm Spot Check - Naive Bayes</h4><p></p><br><h4>21. Classification Algorithm Spot Check - CART</h4><p></p><br><h4>22. Classification Algorithm Spot Check - Support Vector Machines</h4><p></p><br><h4>23. Regression Algorithm Spot Check - Linear Regression</h4><p></p><br><h4>24. Regression Algorithm Spot Check - Ridge Regression</h4><p></p><br><h4>25. Regression Algorithm Spot Check - LASSO Linear Regression</h4><p></p><br><h4>26. Regression Algorithm Spot Check - Elastic Net Regression</h4><p></p><br><h4>27. Regression Algorithm Spot Check - K-Nearest Neighbors</h4><p></p><br><h4>28. Regression Algorithm Spot Check - CART</h4><p></p><br><h4>29. Regression Algorithm Spot Check - Support Vector Machines (SVM)</h4><p></p><br><h4>30. Compare Algorithms - Part 1: Choosing the Best Machine Learning Model</h4><p></p><br><h4>31. Compare Algorithms - Part 2: Choosing the Best Machine Learning Model</h4><p></p><br><h4>32. Pipelines: Data Preparation and Data Modelling</h4><p></p><br><h4>33. Pipelines: Feature Selection and Data Modelling</h4><p></p><br><h4>34. Performance Improvement: Ensembles - Voting</h4><p></p><br><h4>35. Performance Improvement: Ensembles - Bagging</h4><p></p><br><h4>36. Performance Improvement: Ensembles - Boosting</h4><p></p><br><h4>37. Performance Improvement: Parameter Tuning Using Grid Search</h4><p></p><br><h4>38. Performance Improvement: Parameter Tuning Using Random Search</h4><p></p><br><h4>39. Export, Save and Load Machine Learning Models: Pickle</h4><p></p><br><h4>40. Export, Save and Load Machine Learning Models: Joblib</h4><p></p><br><h4>41. Finalizing a Model - Introduction and Steps</h4><p></p><br><h4>42. Finalizing a Classification Model - the Pima Indian Diabetes Dataset</h4><p></p><br><h4>43. Quick Session: Imbalanced Dataset - Issue Overview and Steps</h4><p></p><br><h4>44. Iris Dataset: Finalizing Multi-Class Dataset</h4><p></p><br><h4>45. Finalizing a Regression Model - the Boston Housing Price Dataset</h4><p></p><br><h4>46. Real-Time Predictions: Using the Pima Indian Diabetes Classification Model</h4><p></p><br><h4>47. Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset</h4><p></p><br><h4>48. Real-Time Predictions: Using the Boston Housing Regression Model</h4><p></p>

This course will be mainly focusing on machine learning algorithms. Throughout this course, we are preparing our machine to make it ready for a prediction test.

Machine Learning and Data Science with Python: A Complete Beginners Guide

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					<p><span>This comprehensive course on <b>Data Science &amp; Machine Learning with R</b> 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 <b>Data Science &amp; Machine Learning with R</b> comes with accredited certification, 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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					<p>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.<br /></p>					</div>
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					<p><span>There is no experience or previous qualifications required for enrolment on this <b>Data Science &amp; Machine Learning with R</b>. It is available to all students, of all academic backgrounds.</span></p>					</div>
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					<p><span>Our <b>Data Science &amp; Machine Learning with R</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.</span></p><p><span>There is no time limit for completing this course, it can be studied in your own time at your own pace.</span></p>					</div>
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					<p><span>Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business &amp; Management, Admin, Accountancy &amp; Finance, Secretarial &amp; PA, Teaching &amp; Mentoring etc.</span></p>					</div>
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					</div> <h3>Course Curriculum</h3><div><p>10 sections • 69 lectures • 22:07:00 total length</p></div><div><div><div><div><div><div><div><p>•Data Science and Machine Learning Introduction: 00:03:00</p></div><div><div><p>•What is Data Science: 00:10:00</p></div><div><div><p>•Machine Learning Overview: 00:05:00</p></div><div><div><p>•Who is This Course for: 00:03:00</p></div><div><div><p>•Data Science and Machine Learning Marketplace: 00:05:00</p></div><div><div><p>•Data Science and Machine Learning Job Opportunities: 00:03:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Getting Started: 00:11:00</p></div><div><div><p>•Basics: 00:06:00</p></div><div><div><p>•Files: 00:11:00</p></div><div><div><p>•RStudio: 00:07:00</p></div><div><div><p>•Tidyverse: 00:05:00</p></div><div><div><p>•Resources: 00:04:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Unit Introduction: 00:30:00</p></div><div><div><p>•Basic Type: 00:09:00</p></div><div><div><p>•Vector Part One: 00:20:00</p></div><div><div><p>•Vectors Part Two: 00:25:00</p></div><div><div><p>•Vectors - Missing Values: 00:16:00</p></div><div><div><p>•Vectors - Coercion: 00:14:00</p></div><div><div><p>•Vectors - Naming: 00:10:00</p></div><div><div><p>•Vectors - Misc: 00:06:00</p></div><div><div><p>•Creating Matrics: 00:31:00</p></div><div><div><p>•List: 00:32:00</p></div><div><div><p>•Introduction to Data Frames: 00:19:00</p></div><div><div><p>•Creating Data Frames: 00:20:00</p></div><div><div><p>•Data Frames: Helper Functions: 00:31:00</p></div><div><div><p>•Data Frames Tibbles: 00:39:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Intermediate Introduction: 00:47:00</p></div><div><div><p>•Relational Operations: 00:11:00</p></div><div><div><p>•Conditional Statements: 00:11:00</p></div><div><div><p>•Loops: 00:08:00</p></div><div><div><p>•Functions: 00:14:00</p></div><div><div><p>•Packages: 00:11:00</p></div><div><div><p>•Factors: 00:28:00</p></div><div><div><p>•Dates and Times: 00:30:00</p></div><div><div><p>•Functional Programming: 00:37:00</p></div><div><div><p>•Data Import or Export: 00:22:00</p></div><div><div><p>•Database: 00:27:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Data Manipulation in R Introduction: 00:36:00</p></div><div><div><p>•Tidy Data: 00:11:00</p></div><div><div><p>•The Pipe Operator: 00:15:00</p></div><div><div><p>•The Filter Verb: 00:22:00</p></div><div><div><p>•The Select Verb: 00:46:00</p></div><div><div><p>•The Mutate Verb: 00:32:00</p></div><div><div><p>•The Arrange Verb: 00:10:00</p></div><div><div><p>•The Summarize Verb: 00:23:00</p></div><div><div><p>•Data Pivoting: 00:43:00</p></div><div><div><p>•JSON Parsing: 00:11:00</p></div><div><div><p>•String Manipulation: 00:33:00</p></div><div><div><p>•Web Scraping: 00:59:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Data Visualization in R Section Intro: 00:17:00</p></div><div><div><p>•Getting Started: 00:16:00</p></div><div><div><p>•Aesthetics Mappings: 00:25:00</p></div><div><div><p>•Single Variable Plots: 00:37:00</p></div><div><div><p>•Two Variable Plots: 00:21:00</p></div><div><div><p>•Facets, Layering, and Coordinate Systems: 00:18:00</p></div><div><div><p>•Styling and Saving: 00:12:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Creating with R Markdown: 00:29:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Introduction to R Shiny: 00:26:00</p></div><div><div><p>•A Basic R Shiny App: 00:31:00</p></div><div><div><p>•Other Examples with R Shiny: 00:34:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Machine Learning Part 1: 00:22:00</p></div><div><div><p>•Machine Learning Part 2: 00:47:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Starting a Data Science Career Section Overview: 00:03:00</p></div><div><div><p>•Data Science Resume: 00:04:00</p></div><div><div><p>•Getting Started with Freelancing: 00:05:00</p></div><div><div><p>•Top Freelance Websites: 00:05:00</p></div><div><div><p>•Personal Branding: 00:05:00</p></div><div><div><p>•Importance of Website and Blo: 00:04:00</p></div><div><div><p>•Networking Do's and Don'ts: 00:04:00</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></div></div>

Online Course Marketing

Data Science & Machine Learning with R

<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 

Academy for Health and Fitness

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

<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>

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

Loughborough

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			<p>This course will enable you to bring value to the business by putting data science concepts into practice. Data is crucial for understanding where the business is and where it's headed. Not only can data reveal insights, but it can also inform - by guiding decisions and influencing day-to-day operations.</p>
			<div><i></i> 5 Days - 1 Exam</div>
			<div><i></i>  £595.00 incl. VAT</div>
			
			
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		<h3>Description</h3>
		<p></p><p>For a business to thrive in our data-driven world, it must treat data as one of its most important assets. Data is crucial for understanding where the business is and where it's headed. Not only can data reveal insights, but it can also inform - by guiding decisions and influencing day-to-day operations. This calls for a robust workforce of professionals who can analyze, understand, manipulate, and present data within an effective and repeatable process framework. In other words, the business world needs data science practitioners. This course will enable you to bring value to the business by putting data science concepts into practice. This course includes hands-on activities for each topic area.</p>
<h3>Course Objectives: </h3>
<p>In this course, you will implement data science techniques in order to address business issues. You will:</p>
<p>• Use data science principles to address business issues. <br />• Apply the extract, transform, and load (ETL) process to prepare datasets. <br />• Use multiple techniques to analyze data and extract valuable insights. <br />• Design a machine learning approach to address business issues. <br />• Train, tune, and evaluate classification models. <br />• Train, tune, and evaluate regression and forecasting models. <br />• Train, tune, and evaluate clustering models. <br />• Finalize a data science project by presenting models to an audience, putting models into production, and monitoring model performance.</p>
<p></p>
	
		<h3>Target Student</h3>
		<p></p><p>This course is designed for business professionals who leverage data to address business issues. The typical student in this course will have several years of experience with computing technology, including some aptitude in computer programming.  However, there is not necessarily a single organizational role that this course targets. A prospective student might be a programmer looking to expand their knowledge of how to guide business decisions by collecting, wrangling, analyzing, and manipulating data through code; or a data analyst with a background in applied math and statistics who wants to take their skills to the next level; or any number of other data-driven situations. </p>
<p>Ultimately, the target student is someone who wants to learn how to more effectively extract insights from their work and leverage that insight in addressing business issues, thereby bringing greater value to the business.  This course is also designed to assist students in preparing for the Certified Data Science Practitioner certification.</p>
<p></p>
	
		<h3>Prerequisites</h3>
		<p></p><p>To ensure your success in this course, you should have at least a high-level understanding of fundamental data science concepts, including, but not limited to: types of data, data science roles, the overall data science lifecycle, and the benefits and challenges of data science.</p>
<p>You should have also have experience with high-level programming languages like Python. Being comfortable using fundamental Python data science libraries like NumPy and pandas is highly recommended.</p>
<p>In addition to programming, you should also have experience working with databases, including querying languages like SQL. </p>
<p></p>
	
		<h3>Modules/Lessons</h3>
		<p></p><h4>Lesson 1: Addressing Business Issues with Data Science</h4>
<div>
<p>Topic A: Initiate a Data Science Project<br />Topic B: Formulate a Data Science Problem</p>
<h4>Lesson 2: Extracting, Transforming, and Loading Data</h4>
<p>Topic A: Extract Data <br />Topic B: Transform Data <br />Topic C: Load Data</p>
<h4>Lesson 3: Analyzing Data</h4>
<p>Topic A: Examine Data<br />Topic B: Explore the Underlying Distribution of Data <br />Topic C: Use Visualizations to Analyze Data<br />Topic D: Preprocess Data</p>
<h4>Lesson 4: Designing a Machine Learning Approach</h4>
<p>Topic A: Identify Machine Learning Concepts<br />Topic B: Test a Hypothesis</p>
</div>
<h4>Lesson 5: Developing Classification Models</h4>
<p>Topic A: Train and Tune Classification Models <br />Topic B: Evaluate Classification Models</p>
<h4>Lesson 6: Developing Regression Models</h4>
<p>Topic A: Train and Tune Regression Models <br />Topic B: Evaluate Regression Models</p>
<h4>Lesson 7: Developing Clustering Models</h4>
<p>Topic A: Train and Tune Clustering Models <br />Topic B: Evaluate Clustering Models</p>
<h4>Lesson 8: Finalizing a Data Science Project</h4>
<p>Topic A: Communicate Results to Stakeholders <br />Topic B: Demonstrate Models in a Web App <br />Topic C: Implement and Test Production Pipelines</p>
<p></p>

Mpi Learning - Professional Learning And Development Provider

This course will enable you to bring value to the business by putting data science concepts into practice. Data is crucial for understanding where the business is and where it's headed. Not only can data reveal insights, but it can also inform - by guiding decisions and influencing day-to-day operations.

Certified Data Science Practitioner

<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. Our aim is to maximise your employment prospects and provide you with a range of exciting opportunities to choose from.<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. Whether you need advice on career advancement, assistance with new projects, or simply a friendly ear to share your achievements, we'll be your trusted partner for long-term success.</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>These courses will help you to develop your knowledge and skills to become a <strong>successful </strong>Cyber Security Expert.</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. Our aim is to maximise your employment prospects and provide you with a range of exciting opportunities to choose from.
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. Whether you need advice on career advancement, assistance with new projects, or simply a friendly ear to share your achievements, we'll be your trusted partner for long-term success.
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
These courses will help you to develop your knowledge and skills to become a successful Cyber Security Expert.
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 

Data Analyst

Data Scientist Job Ready Program with Career Support & Money Back Guarantee

<p><strong>***Don't Spend More; Spend Smart with This 14 in 1 Data Science Bundle***</strong></p><p><strong>Get Hard Copy + PDF Certificates + Transcript + Student ID Card + e-Learning App as a Gift - Enrol Data Science Bundle Now</strong></p><p>Tired of browsing and searching for the Data Science course you are looking for? Can't find the complete package that fulfils all your needs? Then don't worry, as you have just found the solution. Take a minute and look through this 14-in-1 extensive Data Science bundle that has everything you need to succeed in <strong>Data Science </strong>and other relevant fields!</p><p>After surveying thousands of learners just like you and considering their valuable feedback, this all-in<strong>-</strong>one <strong>Data Science </strong>bundle has been designed by industry experts. We prioritised what learners were looking for in a complete package and developed this in-demand course that will enhance your Data Science skills and prepare you for the competitive job market.</p><p>Furthermore, to help you showcase your expertise in <strong>Data Science, </strong> we have prepared a special gift of 1 hardcopy certificate and 1 PDF certificate for the title course completely free of cost. These certificates will enhance your credibility and encourage possible employers to pick you over the rest.</p><p><strong>This Data Science Bundle Consists of the following Premium courses: </strong></p><ul><li><strong>Course 01: </strong>Data Analysis</li><li><strong>Course 02: </strong>Data Science &amp; Machine Learning with Python</li><li><strong>Course 03: </strong>R Programming for Data Science</li><li><strong>Course 04: </strong>Statistics &amp; Probability for Data Science &amp; Machine Learning</li><li><strong>Course 05: </strong>Complete Google Analytics Course</li><li><strong>Course 06: </strong>Excel Data Analysis for Beginner</li><li><strong>Course 07: </strong>Introduction to Data Analysis</li><li><strong>Course 08: </strong>Data Analysis in Excel Level 3 Course</li><li><strong>Course 09: </strong>Google Data Studio: Data Analytics</li><li><strong>Course 10: </strong>Data Center Training Essentials: General Introduction</li><li><strong>Course 11: </strong>SQL Programming Masterclass</li><li><strong>Course 12: </strong>Web Scraping and Mapping Dam Levels in Python and Leaflet Level 4</li><li><strong>Course 13: </strong>Learn to Use Python for Spatial Analysis in ArcGIS</li><li><strong>Course 14: </strong>GDPR Data Protection Level 5</li></ul><p>So enrol now in this Data science bundle to kick-start/ advance your career!</p><p>Curriculum of <strong>Data Science Bundle</strong></p><p><strong>Data Science with Python</strong></p><ul><li>Introduction to Python Data Science</li><li>Data Cleaning Packages</li><li>Data Visualization packages</li></ul><p><strong>How will I get my Data Science Certificate?</strong></p><p>After successfully completing the <strong>Data Science </strong>course you will be able to order your CPD Accredited Certificates (PDF + Hard Copy) as proof of your achievement.</p><ul><li><strong>PDF Certificate: Free (For The Title Course)</strong></li><li><strong>Hard Copy Certificate: Free (For The Title Course)</strong></li></ul><h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        145 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">
                            <p>Anyone from any background can enrol in this <strong>Data Science </strong>bundle including;</p><ul><li>Administrator</li><li>&amp; Data Analyst</li><li>Architect</li><li>Cabler</li><li>Manager</li><li>Centre Manager</li></ul>
                        </div><h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>Our <strong>Data science</strong>course is fully compatible with PC's, Mac's, laptops, tablets and Smartphone devices.</p>
                        </div><h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <p>Having this <strong>Data science </strong>expertise will increase the value of your CV and open you up to multiple job sectors. Explore</p><ul><li>Data Science<br /><ul><li>Administrator</li><li>Data Analyst</li><li>Architect</li><li>Cabler</li><li>Manager</li><li>Centre Manager</li></ul></li></ul>
                        </div><h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>Certificate of completion</h4>
        <p>
            Digital certificate -
            Included
        </p>
            <div> <p>You will get the PDF Certificate for the title course (<strong>Data Science with Python</strong>) absolutely Free! </p> </div>
        <h4>Certificate of completion</h4>
        <p>
            Hard copy certificate -
            Included
        </p>
            <div> <p>You will get the Hard Copy certificate for the title course (<strong>Data Science with Python</strong>) absolutely Free! Other Hard Copy certificates are available for £10 each. </p><p>Please Note: The delivery charge inside the UK is £3.99, and the international students must pay a £9.99 shipping cost.</p> </div>

                        </div>

Data Science - CPD Accredited

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			<p>The ability to identify and respond to changing trends is a hallmark of a successful business. Whether those trends are related to customers and sales, or to regulatory and industry standards, businesses are wise to keep track of the variables that can affect the bottom line. In today's business landscape, data comes from numerous sources and in diverse forms.</p>
			<div><i></i> 120 minutes</div>
			<div><i></i>  £50.00 incl. VAT</div>
			
			
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			<p>Want to run this event in-house?  Enquire about running this event in-house </p>
			
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			<p>Interested in attending? Have a suggestion about running this event near you?<br />Register your interest now</p>
			
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		<h3>Description</h3>
		<p></p><p>The ability to identify and respond to changing trends is a hallmark of a successful business. Whether those trends are related to customers and sales, or to regulatory and industry standards, businesses are wise to keep track of the variables that can affect the bottom line. In today's business landscape, data comes from numerous sources and in diverse forms. By leveraging data science concepts and technologies, businesses can mold all of that raw data into information that facilitates decisions to improve and expand the success of the business.</p>
<p></p>
	
		<h3>Modules/Lessons</h3>
		<p></p><h4><span><strong>Lesson 1:</strong> Data Science Fundamentals</span></h4>
<p>Topic A: What is Data Science?<br />Topic B: Types of Data<br />Topic C: The Data Science Lifecycle</p>
<h4><span><strong>Lesson 2:</strong> Data Science Implementation</span></h4>
<p>Topic A: Data Acquisition and Preparation<br />Topic B: Data Modeling and Visualization<br />Topic C: Data Science Roles</p>
<h4><span><strong>Lesson 3:</strong> The Impact of Data Science</span></h4>
<p>Topic A: Benefits of Data Science<br />Topic B: Challenges of Data Science<br />Topic C: Business Use Cases for Data Science</p>
<p></p>
	
		<h3>Target Student</h3>
		<p></p><p>This course is designed for business leaders and decision-makers, including C-level executives, project managers, HR leaders, Marketing and Sales leaders, and technical sales consultants, who want to increase their knowledge of and familiarity with concepts surrounding data science. Other individuals who want to know more about basic data science concepts are also candidates for this course.</p>
<p></p>

The ability to identify and respond to changing trends is a hallmark of a successful business. Whether those trends are related to customers and sales, or to regulatory and industry standards, businesses are wise to keep track of the variables that can affect the bottom line. In today's business landscape, data comes from numerous sources and in diverse forms.

Data Science for Business Professionals

<p><strong>Start your career as a Data Scientist and earn upto £90,000/ Year</strong></p><p>Are you ready to unlock the power of Python and dive into the exciting world of data science? Look no further because we have the ultimate solution for you: Introducing our Data Science with Python Course with Career Support and Job Ready Program!</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 <strong>Data 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 <strong>Data Scientist</strong> experience, we will guide you towards honing your skills and developing a strong foundation in <strong>Data Science</strong>.<br /><br /></li><li><strong>Tailored CV Building:</strong> Crafting an impressive CV is crucial in today's competitive job market. Our team of experts will work closely with you to create a professional CV that showcases your skills and highlights your potential as a Data Scientist. We'll ensure that your CV stands out among the rest, increasing your chances of landing that dream job.<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 <strong>Data Science</strong> 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. <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. Whether you need advice on career advancement, assistance with new projects, or simply a friendly ear to share your achievements, we'll be your trusted partner for long-term success.</li></ul><p><strong>Here are the courses we will provide once you enrol in the program:</strong></p><ul><li>Course 01: Ultimate Python Training for Beginners</li><li>Course 02: Python Intermediate Training</li><li>Course 03: Python Advanced Training</li><li>Course 04: SQL for Data Science, Data Analytics and Data Visualization</li><li>Course 05: Basic Data Analysis</li><li>Course 06: Develop Big Data Pipelines with R &amp; Sparklyr &amp; Tableau</li><li>Course 07: Develop Big Data Pipelines with R, Sparklyr &amp; Power BI</li><li>Course 08: Customer Analytics Training</li><li>Course 09: Google Analytics for Everyone</li><li>Course 10: Google Data Studio: Data Analytics</li><li>Course 11: Big Data Analytics with PySpark Tableau Desktop and MongoDB</li><li>Course 12: Big Data Analytics with PySpark Power BI and MongoDB</li><li>Course 13: Excel Data Analysis</li><li>Course 14: Introduction to Data Analytics with Tableau</li><li>Course 15: Machine Learning with Python Course</li><li>Course 16: Python Programming Bible | Networking, GUI, Email, XML, CGI</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:</strong></p><p><strong>Step 1: Enrol in the Programme</strong></p><p>Begin your exciting journey with us by enrolling in the <strong>Data Scientist </strong>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 <strong>Data Scientist</strong>. 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.</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.</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 <strong>Data Scientist</strong> industry. With these powerful tools in hand, you'll be fully prepared to tackle job interviews confidently.</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.</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.</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>.</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.</p><p><strong>Step 9: Celebrate Your New Job!</strong></p><p>Once you've secured your dream job in Data Science, 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 <strong>Data Science</strong> 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>Aspiring data scientists looking to enter the exciting field of data science.</li><li>Professionals from other disciplines who want to transition into the data science domain.</li><li>Software engineers or programmers interested in expanding their skill set to include data science.</li><li>Analysts or researchers who want to enhance their data analysis and modeling capabilities.</li><li>Students or graduates seeking to kick-start their careers in data science with a strong foundation.</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 Analyst: £25,000 - £55,000 per year</li><li>Data Scientist: £40,000 - £85,000 per year</li><li>Machine Learning Engineer: £50,000 - £100,000 per year</li><li>Data Engineer: £45,000 - £80,000 per year</li><li>Business Intelligence Analyst: £35,000 - £65,000 per year</li><li>Data Science Manager: £70,000 - £120,000 per year.</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 as a Data Scientist and earn upto £90,000/ Year
Are you ready to unlock the power of Python and dive into the exciting world of data science? Look no further because we have the ultimate solution for you: Introducing our Data Science with Python Course with Career Support and Job Ready Program!
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 Data Scientist experience, we will guide you towards honing your skills and developing a strong foundation in Data Science.
Tailored CV Building: Crafting an impressive CV is crucial in today's competitive job market. Our team of experts will work closely with you to create a professional CV that showcases your skills and highlights your potential as a Data Scientist. We'll ensure that your CV stands out among the rest, increasing your chances of landing that dream job.
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.
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. Whether you need advice on career advancement, assistance with new projects, or simply a friendly ear to share your achievements, we'll be your trusted partner for long-term success.
Here are the courses we will provide once you enrol in the program:
Course 01: Ultimate Python Training for Beginners
Course 02: Python Intermediate Training
Course 03: Python Advanced Training
Course 04: SQL for Data Science, Data Analytics and Data Visualization
Course 05: Basic Data Analysis
Course 06: Develop Big Data Pipelines with R & Sparklyr & Tableau
Course 07: Develop Big Data Pipelines with R, Sparklyr & Power BI
Course 08: Customer Analytics Training
Course 09: Google Analytics for Everyone
Course 10: Google Data Studio: Data Analytics
Course 11: Big Data Analytics with PySpark Tableau Desktop and MongoDB
Course 12: Big Data Analytics with PySpark Power BI and MongoDB
Course 13: Excel Data Analysis
Course 14: Introduction to Data Analytics with Tableau
Course 15: Machine Learning with Python Course
Course 16: Python Programming Bible | Networking, GUI, Email, XML, CGI
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 Scientist 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 Scientist. 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 Scientist 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, 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 begins with us.
 CPD 
100 CPD hours / points  Accredited by CPD Quality Standards
 Who is this course for? 
Aspiring data scientists looking to enter the exciting field of data science.
Professionals from other disciplines who want to transition into the data science domain.
Software engineers or programmers interested in expanding their skill set to include data science.
Analysts or researchers who want to enhance their data analysis and modeling capabilities.
Students or graduates seeking to kick-start their careers in data science with a strong foundation.
 Requirements 
No experience required. Just enrol & start learning.
 Career path 
Data Analyst: £25,000 - £55,000 per year
Data Scientist: £40,000 - £85,000 per year
Machine Learning Engineer: £50,000 - £100,000 per year
Data Engineer: £45,000 - £80,000 per year
Business Intelligence Analyst: £35,000 - £65,000 per year
Data Science Manager: £70,000 - £120,000 per year.
 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 

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

<strong>This course will show you how to create a professional and attractive user interface (UI) in Django for data science using the Semantic UI framework.</strong>
        <p>This course will show you how to create a professional and attractive user interface (UI) in Django for data science using the Semantic UI framework. If you don't have a programming background, this course will help you create custom analytic tools in the browser by taking you through the core concepts of pandas, NumPy, Matplotlib, and Seaborn. With a step-by-step introduction to new concepts, this Django course will gradually help you get to grips with the essentials of data science.
The code bundle for this course available at https://github.com/PacktPublishing/Django-with-Data-Science</p>
        <h2>What You Will Learn</h2><p>Understand the integration of Django and Python data science libraries: pandas, Matplotlib, Seaborn, and NumPy<br>Populate the database from CSV files<br>Explore the Semantic UI framework<br>Get to grips with the basics of data science</p>
        <h2>Audience</h2><p>If you are a developer looking to dive into the world of data science with Django, this course is for you.</p>
        <h2>Approach</h2><p>A good resource for beginners with a programming mindset, this course explains each concept in a precise and easy-to-understand way. The instructor takes you through the content systematically to help you make the most of the topics covered.</p>
        <h2>Key Features</h2><p>Work with Django forms and model forms * Create a modal with price statistics * Transform the database and populate rows of the .csv file with sales data</p>
        <h2>Github Repo</h2><p>https://github.com/packtpublishing/django-with-data-science</p>
        <h2>About the Author</h2><h3>Lukasz Makinia</h3><p>Lukasz Makinia is a freelance web developer and a Lean Sigma Six Black Belt. From the beginning of his 8-year professional career, he's related to the field of continuous improvement by providing IT and Lean Management solutions to medium and large companies. He also creates web applications mainly for data gathering and processing using Python/Django, JavaScript, React, and ML. In his free time, Luke writes articles for his blog-PyPlane.

He is associated with 'Django Ninjas'-a web framework for building APIs with Django and Python 3.6+ type hints. They provide online educational courses mainly about Python/Django by the community of web developers across the globe. Their classes are project-based only, which means 'teaching by doing'.</p>
        <h2>Course Outline</h2><h4>1. Django Project</h4><p></p><br><h4>2. Python Data Science Libraries [Optional]</h4><p></p><br><h4>3. Field Types in Django [OPTIONAL]</h4><p></p>

This course will show you how to create a professional and attractive user interface (UI) in Django for data science using the Semantic UI framework.

Django with Data Science

<p>Give a compliment to your career and take it to the next level. This<strong> Data Science </strong>will provide you with the essential knowledge to shine in your professional career. Whether you want to develop skills for your next job or elevate your skills for your next promotion, this Data Sciencebundle will help you stay ahead of the pack.</p><p>Throughout the Data Scienceprogramme, it stresses how to improve your competency as a person in your chosen field while also outlining essential career insights in the relevant job sector.</p><p>Along with this Data Science course, you will get <strong>10 premium courses, an original</strong><strong>Hardcopy</strong>, <strong>11 PDF Certificates (Main Course + Additional Courses) </strong>Student ID card as gifts.</p><p><strong>This Data Science Bundle Consists of the following Premium courses: </strong></p><ul><li><strong> Course 01: </strong>Data Science with Python</li><li><strong> Course 02: </strong>Data Science &amp; Machine Learning with Python</li><li><strong> Course 03: </strong>R Programming for Data Science</li><li><strong> Course 04: </strong>Python for Data Analysis</li><li><strong> Course 05: </strong>Machine Learning for Predictive Maps in Python and Leaflet</li><li><strong> Course 06: </strong>Learn to Use Python for Spatial Analysis in ArcGIS</li><li><strong> Course 07: </strong>Python Programming for Everybody</li><li><strong> Course 08: </strong>Encryption</li><li><strong> Course 09: </strong>GDPR Data Protection Level 5</li><li><strong> Course</strong> 10: Decision Making and Critical Thinking</li><li><strong> Course 11: </strong>Time Management</li></ul><p>Enrol now in Data Science to advance your career, and use the premium study materials from Apex Learning.<br /><strong>Certificate:</strong></p><ul><li><strong>PDF Certificate: Free (Previously it was £6*11 = £66)</strong></li><li><strong>Hard Copy Certificate: Free (For The Title Course: Previously it was £10)</strong></li></ul><p>The bundle incorporates basic to advanced level skills to shed some light on your way and boost your career. Hence, you can strengthen your Data Scienceexpertise and essential knowledge, which will assist you in reaching your goal.</p><p><strong>Curriculum:</strong></p><p><strong> Course 01: R Programming for Data Science</strong></p><ul><li>Unit 01: Data Science Overview</li><li>Unit 02: R and RStudio</li><li>Unit 03: Introduction to Basics</li><li>Unit 04: Vectors</li><li>Unit 05: Matrices</li><li>Unit 06: Factors</li><li>Unit 07: Data Frames</li><li>Unit 08: Lists</li><li>Unit 09: Relational Operators</li><li>Unit 10: Logical Operators</li><li>Unit 11: Conditional Statements</li><li>Unit 12: Loops</li><li>Unit 13: Functions</li><li>Unit 14: R Packages</li><li>Unit 15: The Apply Family - lapply</li><li>Unit 16: The apply Family - sapply &amp; vapply</li><li>Unit 17: Useful Functions</li><li>Unit 18: Regular Expressions</li><li>Unit 19: Dates and Times</li><li>Unit 20: Getting and Cleaning Data</li><li>Unit 21: Plotting Data in R</li><li>Unit 22: Data Manipulation with dplyr</li></ul><p>And much more...</p><h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        120 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">
                            <p>Anyone from any background can enrol in this Data Science bundle.</p>
                        </div><h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>This Data Science course has been designed to be fully compatible with tablets and smartphones.</p>
                        </div><h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <p>Having this expertise will increase the value of your CV and open you up to multiple job sectors.</p>
                        </div><h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>Certificate of completion</h4>
        <p>
            Digital certificate -
            Included
        </p>
        <h4>Certificate of completion</h4>
        <p>
            Hard copy certificate -
            Included
        </p>
            <div> <p>You will get the Hard Copy certificate for the title course (<strong>R Programming for Data Science</strong>) absolutely Free! Other Hard Copy certificates are available for £10 each. </p><p>Please Note: The delivery charge inside the UK is £3.99, and the international students must pay a £9.99 shipping cost.</p> </div>

                        </div>

Data Science with Python Course

<p><strong>Boost Your Career with Apex Learning and Get Noticed By Recruiters in this Hiring Season! Get Hard Copy + PDF Certificates + Transcript + Student ID Card worth £160 as a Gift - Enrol Now</strong></p><p>With a single payment you will gain access to <strong>Data Science Course Bundle 2022</strong> including <strong>10</strong> Career development courses, <strong>original hardcopy certificate, transcript</strong> and a <strong>student ID card</strong> which will allow you to get discounts on things like music, food, travel and clothes etc.</p><p>The world is one big data bank, and data science is one of the most demanding professional sectors of the present era.</p><p>The analytical and programming-oriented field of data science has limited resources for candidates to learn and develop skills, which is why you need our highly advanced [course_title] course.With step-by-step interactive video content, our training will equip you with extensive knowledge and expertise in data science, including machine learning.</p><p>This bundle course offers an opportunity to foster your career opportunities with an expert-level understanding of data science and become skilful in this industry.</p><p>Take this course anywhere and at any time. Don't let your lifestyle limit your learning or your potential.</p><p><strong>Data Science Course Bundle 2022</strong> will provide you with the <strong> CPD certificate </strong>that you'll need to succeed.</p><p>Gain experience online and interact with experts. This can prove to be the perfect way to get noticed by a prospective employer and stand out from the crowd.</p><p><strong>Data Science Course Bundle 2022 </strong>has been rated and reviewed highly by our learners and professionals alike. We have a passion for teaching, and it shows.</p><p>All of our courses have interactive online modules that allow studying to take place where and when you want it to.</p><p>The only thing you need to take <strong>Data Science Course Bundle 2022 </strong> is Wi-Fi and a screen. You'll never be late for class again.</p><p>Experienced tutors and mentors will be there for you whenever you need them, and solve all your queries through email and chat boxes.</p><p><strong>Benefits you'll get choosing Apex Learning for this Course:</strong></p><ul><li>One payment, but lifetime access to 11 CPD courses</li><li>Certificates, student ID for the title course included in a one-time fee</li><li>Full tutor support available from Monday to Friday</li><li>Free up your time - don't waste time and money travelling for classes</li><li>Accessible, informative modules taught by expert instructors</li><li>Learn at your ease - anytime, from anywhere</li><li>Study the course from your computer, tablet or mobile device</li><li>CPD accredited course - improve the chance of gaining professional skills</li><li>Gain valuable knowledge without leaving your home</li></ul><p><strong>What other courses are included with this Course?</strong></p><ol><li>Level 2 Microsoft Office Essentials</li><li>Microsoft Teams</li><li>Leadership &amp; Management Diploma</li><li>Working from Home Essentials</li><li>Mental Health and Working from Home</li><li>Online Meeting Management</li><li>Effective Communication Skills</li><li>Time Management</li><li>Report Writing</li><li>Emotional Intelligence and Human Behaviour</li></ol><p><strong>Curriculum</strong></p><p><strong>***Data Science Course Bundle 2022***</strong></p><p><strong>Welcome, Course Introduction &amp; overview, and Environment set-up</strong></p><ul><li>Welcome &amp; Course Overview</li><li>Set-up the Environment for the Course (lecture 1)</li><li>Set-up the Environment for the Course (lecture 2)</li><li>Two other options to setup environment</li></ul><p><strong>Python Essentials</strong></p><ul><li>Python data types Part 1</li><li>Python Data Types Part 2</li><li>Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 1)</li><li>Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 2)</li><li>Python Essentials Exercises Overview</li><li>Python Essentials Exercises Solutions</li></ul><p><strong>Python for Data Analysis using NumPy</strong></p><ul><li>What is Numpy? A brief introduction and installation instructions.</li><li>NumPy arrays, built-in methods, array methods and attributes.</li><li>Indexing, slicing, broadcasting &amp; boolean masking</li><li>Arithmetic Operations &amp; Universal Functions</li><li>Exercises Overview</li><li>Exercises Solutions</li></ul><p><strong>Python for Data Analysis using Pandas</strong></p><ul><li>What is pandas? A brief introduction and installation instructions.</li><li>Pandas Introduction</li><li>Pandas Data Structures - Series</li><li>Pandas Data Structures - DataFrame</li><li>Handling Missing Data</li><li>Data Wrangling - Combining, merging, joining</li><li>Groupby</li><li>Useful Methods and Operations</li><li>Project 1 (Overview) Customer Purchases Data</li><li>Project 1 (Solutions) Customer Purchases Data</li><li>Project 2 (Overview) Chicago Payroll Data</li><li>Project 2 (Solutions Part 1) Chicago Payroll Data</li></ul><p><strong>Python for Data Visualization using matplotlib</strong></p><ul><li>Matplotlib Essentials (Part 1) - Basic Plotting &amp; Object Oriented Approach</li><li>Matplotlib Essentials (Part 2) - Basic Plotting &amp; Object Oriented Approach</li><li>Matplotlib Essentials (Part 3) - Basic Plotting &amp; Object Oriented Approach</li><li>Matplotlib Essentials - Exercises Overview</li><li>Matplotlib Essentials - Exercises Solutions</li></ul><p><strong>Python for Data Visualization using Seaborn</strong></p><ul><li>Introduction &amp; Installation</li><li>Distribution Plots</li><li>Categorical Plots (Part 1)</li><li>Categorical Plots (Part 2)</li><li>Axis Grids</li><li>Matrix Plots</li><li>Regression Plots</li><li>Controlling Figure Aesthetics</li><li>Exercises Overview</li><li>Exercise Solutions</li></ul><p><strong>Python for Data Visualization using pandas</strong></p><ul><li>Pandas Built-in Data Visualization</li><li>Pandas Data Visualization Exercises Overview</li><li>Panda Data Visualization Exercises Solutions</li></ul><p><strong>Python for interactive &amp; geographical plotting using Plotly and Cufflinks</strong></p><ul><li>Interactive &amp; Geographical Plotting (Part 1)</li><li>Interactive &amp; Geographical Plotting (Part 2)</li><li>Interactive &amp; Geographical Plotting Exercises (Overview)</li><li>Interactive &amp; Geographical Plotting Exercises (Solutions)</li></ul><p><strong>Capstone Project - Python for Data Analysis &amp; Visualization</strong></p><ul><li>Project 1 - Oil vs Banks Stock Price during recession (Overview)</li><li>Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 1)</li><li>Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 2)</li><li>Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 3)</li><li>Project 2 (Optional) - Emergency Calls from Montgomery County, PA (Overview)</li></ul><p><strong>Python for Machine Learning (ML) - scikit-learn - Linear Regression Model</strong></p><ul><li>Introduction to ML - What, Why and Typesâ¦..</li><li>Theory Lecture on Linear Regression Model, No Free Lunch, Bias Variance Tradeoff</li><li>Linear Regression Model - Hands-on (Part 1)</li><li>Linear Regression Model Hands-on (Part 2)</li><li>Good to know! How to save and load your trained Machine Learning Model!</li><li>Linear Regression Model (Insurance Data Project Overview)</li><li>Linear Regression Model (Insurance Data Project Solutions)</li></ul><p><strong>Python for Machine Learning - scikit-learn - Logistic Regression Model</strong></p><ul><li>Theory: Logistic Regression, conf. mat., TP, TN, Accuracy, Specificityâ¦etc.</li><li>Logistic Regression Model - Hands-on (Part 1)</li><li>Logistic Regression Model - Hands-on (Part 2)</li><li>Logistic Regression Model - Hands-on (Part 3)</li><li>Logistic Regression Model - Hands-on (Project Overview)</li><li>Logistic Regression Model - Hands-on (Project Solutions)</li></ul><p><strong>Python for Machine Learning - scikit-learn - K Nearest Neighbors</strong></p><ul><li>Theory: K Nearest Neighbors, Curse of dimensionality â¦.</li><li>K Nearest Neighbors - Hands-on</li><li>K Nearest Neighbors (Project Overview)</li><li>K Nearest Neighbors (Project Solutions)</li></ul><p><strong>Python for Machine Learning - scikit-learn - Decision Tree and Random Forests</strong></p><ul><li>Theory: D-Tree &amp; Random Forests, splitting, Entropy, IG, Bootstrap, Baggingâ¦.</li><li>Decision Tree and Random Forests - Hands-on (Part 1)</li><li>Decision Tree and Random Forests (Project Overview)</li><li>Decision Tree and Random Forests (Project Solutions)</li></ul><p><strong>Python for Machine Learning - scikit-learn -Support Vector Machines (SVMs)</strong></p><ul><li>Support Vector Machines (SVMs) - (Theory Lecture)</li><li>Support Vector Machines - Hands-on (SVMs)</li><li>Support Vector Machines (Project 1 Overview)</li><li>Support Vector Machines (Project 1 Solutions)</li><li>Support Vector Machines (Optional Project 2 - Overview)</li></ul><p><strong>Python for Machine Learning - scikit-learn - K Means Clustering</strong></p><ul><li>Theory: K Means Clustering, Elbow method â¦..</li><li>K Means Clustering - Hands-on</li><li>K Means Clustering (Project Overview)</li><li>K Means Clustering (Project Solutions)</li></ul><p><strong>Python for Machine Learning - scikit-learn - Principal Component Analysis (PCA)</strong></p><ul><li>Theory: Principal Component Analysis (PCA)</li><li>Principal Component Analysis (PCA) - Hands-on</li><li>Principal Component Analysis (PCA) - (Project Overview)</li><li>Principal Component Analysis (PCA) - (Project Solutions)</li></ul><p><strong>Recommender Systems with Python - (Additional Topic)</strong></p><ul><li>Theory: Recommender Systems their Types and Importance</li><li>Python for Recommender Systems - Hands-on (Part 1)</li><li>Python for Recommender Systems - - Hands-on (Part 2)</li></ul><p><strong>Python for Natural Language Processing (NLP) - NLTK - (Additional Topic)</strong></p><ul><li>Natural Language Processing (NLP) - (Theory Lecture)</li><li>NLP-Challenges, Data Sources, Data Processing â¦..</li><li>Feature Engineering and Text Preprocessing in Natural Language Processing</li><li>NLP - Tokenization, Text Normalization, Vectorization, BoWâ¦.</li><li>BoW, TF-IDF, Machine Learning, Training &amp; Evaluation, Naive Bayes â¦</li><li>Pipeline feature to assemble several steps for cross-validationâ¦</li></ul><p><strong>How will I get my Certificate?</strong></p><p>After successfully completing the course you will be able to order your CPD Accredited Certificates (PDF + Hard Copy) as proof of your achievement.</p><ul><li><strong>PDF Certificate: Free (Previously it was £10 * 11 = £110)</strong></li></ul><ul><li><strong>Hard Copy Certificate: Free (For The Title Course)</strong></li></ul><p>If you want to get hardcopy certificates for other courses, generally you have to pay £20 for each. But this Fall, Apex Learning is offering a<strong> Flat 50% discount </strong>on hard copy certificates, and you can get each for just <strong>£10</strong>!</p><p><strong>P.S. The delivery charge inside the U.K. is £3.99 and the international students have to pay £9.99. </strong></p><h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        20 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">
                            <p>There is no experience or previous qualifications required for enrolment on this <strong>Data Science Course Bundle 2022</strong>. It is available to all students, of all academic backgrounds.</p>
                        </div><h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>Our <strong>Data Science Course Bundle 2022</strong> is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible on tablets and smartphones so you can access your course on wifi, 3G or 4G.</p><p>There is no time limit for completing this course, it can be studied in your own time at your own pace.</p>
                        </div><h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <p>Having this CPD certificate will increase the value in your CV and open you up to multiple sectors such as Business &amp; Management, Admin, Accountancy &amp; Finance, Secretarial &amp; PA, Teaching &amp; Mentoring etc.</p>
                        </div><h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>Certificate of completion</h4>
        <p>
            Digital certificate -
            Included
        </p>

                        </div>

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