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<p>Data Analytics and Business Intelligence course teaches you everything on the topic thoroughly from scratch so you can achieve a certificate for free to showcase your achievement in professional life.</p><p>This Data Analytics and Business Intelligence course is a comprehensive course designed to provide a detailed understanding of the nature of the related sector and your key roles within it.</p><p>The training materials of this Data Analytics and Business Intelligence course are available online for you to learn at your own pace and fast-track your career with ease.</p><p>Data Analytics and Business Intelligence Combo Training Included:</p><ul><li><strong>Course 01: </strong>Data Analytics</li><li><strong>Course 02: </strong>Business Intelligence Analyst</li></ul><p><strong>Key Features </strong></p><ul><li>CPD Accredited Data Analytics and Business Intelligence courses</li><li>Instant 2 PDF certificate</li><li>Fully online, interactive Data Analytics and Business Intelligence course with audio voiceover</li><li>Self-paced learning and laptop, tablet, smartphone-friendly</li><li>24/7 Learning Assistance</li><li>Discounts on bulk purchases</li></ul><p><strong>Enrol now in this </strong><strong>Data Analytics and Business Intelligence</strong><strong> course to excel! </strong></p><p>To become successful in your profession, you must have a specific set of skills to succeed in today's competitive world. In this in-depth Data Analytics and Business Intelligence training course, you will develop the most in-demand skills to kickstart your career, as well as upgrade your existing knowledge &amp; skills.</p><p>The curriculum of the Data Analytics and Business Intelligence course has been designed by experts with years of experience behind them which is extremely dynamic and well-paced to help you understand the subject matter with ease.</p><p><strong>Curriculum</strong></p><p><strong>Course 01: Data Analytics</strong></p><ul><li>Module 01: Introduction to the World of Data</li><li>Module 02: Basics of Data Analytics</li><li>Module 03: Statistics for Data Analytics</li><li>Module 04: Actions Taken in the Data Analysis Process</li><li>Module 05: Gathering the Right Information</li><li>Module 06: Storing Data</li><li>Module 07: Data Mining</li><li>Module 08: Excel for Data Analytics</li><li>Module 09: Tools for Data Analytics</li><li>Module 10: Data-Analytic Thinking</li><li>Module 11: Data Visualisation That Clearly Describes Insights</li><li>Module 12: Data Visualisation Tools</li></ul><p><strong>Course 02: Business Intelligence Analyst</strong></p><ul><li>Module 01: An Introduction to Business Intelligence</li><li>Module 02: Real-time Business Intelligence</li><li>Module 03: Fundamentals of Statistics and Data Science</li><li>Module 04: Fundamentals of SQL</li><li>Module 05: Database Management Essentials</li><li>Module 06: Data Warehouse Concepts</li><li>Module 07: Data Visualisation in Business Intelligence</li><li>Module 08: Basics of Python</li></ul><p><strong>Accreditation</strong></p><p>All of our courses are fully accredited, including this Data Analytics and Business Intelligence course, providing you with up-to-date skills and knowledge and helping you to become more competent and effective in your chosen field.</p><p><strong>Certification</strong></p><p>Once you've successfully completed your Data Analytics and Business Intelligence course, you will immediately be sent a digital certificate. Also, you can have your printed certificate delivered by post (shipping cost £3.99).</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>This course is ideal for all employees or anyone who genuinely wishes to learn more about Data Analytics and Business Intelligence basics.</p>
                        </div><h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>No prior degree or experience is required to enrol in this course.</p>
                        </div><h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>Certificate of completion</h4>
        <p>
            Digital certificate -
            Included
        </p>
        <h4>Hard copy certificate</h4>
        <p>
            Hard copy certificate -
            Included
        </p>
            <div> <p>You will get the hard copy certificates for Free! The delivery charge of the hard copy certificate inside the UK is £3.99 each.</p> </div>

                        </div>

Training Express

Data Analytics and Business Intelligence Course

General Admission

<strong>Learn complete hands-on Regression analysis for practical Statistical modelling and Machine Learning in R</strong>
        <p>With so many R Statistics and Machine Learning courses around, why enroll for this?

Regression analysis is one of the central aspects of both Statistics and Machine Learning based analysis. This course will teach you Regression analysis for both Statistical data analysis and ML in R. It explores relevant concepts in a practical way, from basic to expert level. This course can help you achieve better grades, gain new analysis tools for your academic career, implement your knowledge in a work setting, and make business forecasting-related decisions. You will go all the way from implementing and inferring simple OLS (Ordinary Least Square) regression models to dealing with issues of multicollinearity in regression to ML based regression models.

Become a Regression analysis expert and harness the power of R for your analysis

&bull; Get started with R and RStudio. Install these on your system, learn to load packages, and read in different types of data in R
&bull; Carry out data cleaning and data visualization using R
&bull; Implement Ordinary Least Square (OLS) regression in R and learn how to interpret the results.
&bull; Learn how to deal with multicollinearity both through the variable selection and regularization techniques such as ridge regression
&bull; Carry out variable and regression model selection using both statistical and machine learning techniques, including using cross-validation methods.
&bull; Evaluate the regression model accuracy
&bull; Implement Generalized Linear Models (GLMs) such as logistic regression and Poisson regression. Use logistic regression as a binary classifier to distinguish between male and female voices.
&bull; Use non-parametric techniques such as Generalized Additive Models (GAMs) to work with non-linear and non-parametric data.
&bull; Work with tree-based ML models

All the code and supporting files for this course are available at - https://github.com/PacktPublishing/Regression-Analysis-for-Statistics-and-Machine-Learning-in-R</p>
        <h2>What You Will Learn</h2><p>Implement and infer Ordinary Least Square (OLS) regression using R<br>Apply statistical and ML based regression models to deal with problems such as multicollinearity<br>Carry out the variable selection and assess model accuracy using techniques such as cross-validation<br>Implement and infer Generalized Linear Models (GLMs), including using logistic regression as a binary classifier</p>
        <h2>Audience</h2><p>This course is for students interested in getting started with data science applications in the RStudio environment. Students wishing to learn to implement statistical modeling techniques for regression analysis on real data. Anyone with prior exposure to R who wants to get started with practical data science.</p>
        <h2>Approach</h2><p>This is a practical, hands-on course. We will spend some time dealing with some theoretical concepts related to both statistical and machine learning regression analysis. However, the majority of the course will focus on implementing different techniques on real data and interpreting the results. After each video, you will learn a new concept or technique which you can apply to your own projects.</p>
        <h2>Key Features</h2><p>Provided practical indepth training for you to get started with R * Perform some of the most common advanced regression analysis-based techniques * Use R to perform different statistical and machine learning data analysis and visualization tasks</p>
        <h2>Github Repo</h2><p>https://github.com/packtpublishing/regression-analysis-for-statistics-and-machine-learning-in-r</p>
        <h2>About the Author</h2><h3>Minerva Singh</h3><p>Minerva Singh is a PhD graduate from Cambridge University where she specialized in Tropical Ecology. She is also a part-time Data Scientist. As part of her research, she must carry out extensive data analysis, including spatial data analysis. For this purpose, she prefers to use a combination of freeware tools: R, QGIS, and Python. She does most of her spatial data analysis work using R and QGIS. Apart from being free, these are very powerful tools for data visualization, processing, and analysis. She also holds an MPhil degree in Geography and Environment from Oxford University. She has honed her statistical and data analysis skills through several MOOCs, including The Analytics Edge and Statistical. In addition to spatial data analysis, she is also proficient in statistical analysis, machine learning, and data mining.</p>
        <h2>Course Outline</h2><h4>1. Get Started with Practical Regression Analysis in R</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. INTRODUCTION TO THE COURSE: The Key Concepts and Software Tools</p><p style='margin: 0'>Get Started with Practical Regression Analysis in R: INTRODUCTION TO THE COURSE: The Key Concepts and Software Tools</p></td></tr><tr><td style='padding: 15px;'><p>2. Difference Between Statistical Analysis & Machine Learning</p><p style='margin: 0'>Get Started with Practical Regression Analysis in R: Difference Between Statistical Analysis &amp; Machine Learning</p></td></tr><tr><td style='padding: 15px;'><p>3. Getting Started with R and R Studio</p><p style='margin: 0'>Get Started with Practical Regression Analysis in R: Getting Started with R and R Studio</p></td></tr><tr><td style='padding: 15px;'><p>4. Reading in Data with R</p><p style='margin: 0'>Get Started with Practical Regression Analysis in R: Reading in Data with R</p></td></tr><tr><td style='padding: 15px;'><p>5. Data Cleaning with R</p><p style='margin: 0'>Get Started with Practical Regression Analysis in R: Data Cleaning with R</p></td></tr><tr><td style='padding: 15px;'><p>6. Some More Data Cleaning with R</p><p style='margin: 0'>Get Started with Practical Regression Analysis in R: Some More Data Cleaning with R</p></td></tr><tr><td style='padding: 15px;'><p>7. Basic Exploratory Data Analysis in R</p><p style='margin: 0'>Get Started with Practical Regression Analysis in R: Basic Exploratory Data Analysis in R</p></td></tr><tr><td style='padding: 15px;'><p>8. Conclusion to Section 1</p><p style='margin: 0'>Get Started with Practical Regression Analysis in R: Conclusion to Section 1</p></td></tr></tbody></table><br><h4>2. Ordinary Least Square Regression Modelling</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. OLS Regression- Theory</p><p style='margin: 0'>Ordinary Least Square Regression Modelling: OLS Regression- Theory</p></td></tr><tr><td style='padding: 15px;'><p>2. OLS-Implementation</p><p style='margin: 0'>Ordinary Least Square Regression Modelling: OLS-Implementation</p></td></tr><tr><td style='padding: 15px;'><p>3. More on Result Interpretations</p><p style='margin: 0'>Ordinary Least Square Regression Modelling: More on Result Interpretations</p></td></tr><tr><td style='padding: 15px;'><p>4. Confidence Interval-Theory</p><p style='margin: 0'>Ordinary Least Square Regression Modelling: Confidence Interval-Theory</p></td></tr><tr><td style='padding: 15px;'><p>5. Calculate the Confidence Interval in R</p><p style='margin: 0'>Ordinary Least Square Regression Modelling: Calculate the Confidence Interval in R</p></td></tr><tr><td style='padding: 15px;'><p>6. Confidence Interval and OLS Regressions</p><p style='margin: 0'>Ordinary Least Square Regression Modelling: Confidence Interval and OLS Regressions</p></td></tr><tr><td style='padding: 15px;'><p>7. Linear Regression without Intercept</p><p style='margin: 0'>Ordinary Least Square Regression Modelling: Linear Regression without Intercept</p></td></tr><tr><td style='padding: 15px;'><p>8. Implement ANOVA on OLS Regression</p><p style='margin: 0'>Ordinary Least Square Regression Modelling: Implement ANOVA on OLS Regression</p></td></tr><tr><td style='padding: 15px;'><p>9. Multiple Linear Regression</p><p style='margin: 0'>Ordinary Least Square Regression Modelling: Multiple Linear Regression</p></td></tr><tr><td style='padding: 15px;'><p>10. Multiple Linear regression with Interaction and Dummy Variables</p><p style='margin: 0'>Ordinary Least Square Regression Modelling: Multiple Linear regression with Interaction and Dummy Variables</p></td></tr><tr><td style='padding: 15px;'><p>11. Some Basic Conditions that OLS Models Have to Fulfill</p><p style='margin: 0'>Ordinary Least Square Regression Modelling: Some Basic Conditions that OLS Models Have to Fulfill</p></td></tr><tr><td style='padding: 15px;'><p>12. Conclusions to Section 2</p><p style='margin: 0'>Ordinary Least Square Regression Modelling: Conclusions to Section 2</p></td></tr></tbody></table><br><h4>3. Deal with Multicollinearity in OLS Regression Models</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Identify Multicollinearity</p><p style='margin: 0'>Deal with Multicollinearity in OLS Regression Models: Identify Multicollinearity</p></td></tr><tr><td style='padding: 15px;'><p>2. Doing Regression Analyses with Correlated Predictor Variables</p><p style='margin: 0'>Deal with Multicollinearity in OLS Regression Models: Doing Regression Analyses with Correlated Predictor Variables</p></td></tr><tr><td style='padding: 15px;'><p>3. Principal Component Regression in R</p><p style='margin: 0'>Deal with Multicollinearity in OLS Regression Models: Principal Component Regression in R</p></td></tr><tr><td style='padding: 15px;'><p>4. Partial Least Square Regression in R</p><p style='margin: 0'>Deal with Multicollinearity in OLS Regression Models: Partial Least Square Regression in R</p></td></tr><tr><td style='padding: 15px;'><p>5. Ridge Regression in R</p><p style='margin: 0'>Deal with Multicollinearity in OLS Regression Models: Ridge Regression in R</p></td></tr><tr><td style='padding: 15px;'><p>6. LASSO Regression</p><p style='margin: 0'>Deal with Multicollinearity in OLS Regression Models: LASSO Regression</p></td></tr><tr><td style='padding: 15px;'><p>7. Conclusion to Section 3</p><p style='margin: 0'>Deal with Multicollinearity in OLS Regression Models: Conclusion to Section 3</p></td></tr></tbody></table><br><h4>4. Variable & Model Selection</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Why Do Any Kind of Selection?</p><p style='margin: 0'>Variable &amp; Model Selection: Why Do Any Kind of Selection?</p></td></tr><tr><td style='padding: 15px;'><p>2. Select the Most Suitable OLS Regression Model</p><p style='margin: 0'>Variable &amp; Model Selection: Select the Most Suitable OLS Regression Model</p></td></tr><tr><td style='padding: 15px;'><p>3. Select Model Subsets</p><p style='margin: 0'>Variable &amp; Model Selection: Select Model Subsets</p></td></tr><tr><td style='padding: 15px;'><p>4. Machine Learning Perspective on Evaluate Regression Model Accuracy</p><p style='margin: 0'>Variable &amp; Model Selection: Machine Learning Perspective on Evaluate Regression Model Accuracy</p></td></tr><tr><td style='padding: 15px;'><p>5. Evaluate Regression Model Performance</p><p style='margin: 0'>Variable &amp; Model Selection: Evaluate Regression Model Performance</p></td></tr><tr><td style='padding: 15px;'><p>6. LASSO Regression for Variable Selection</p><p style='margin: 0'>Variable &amp; Model Selection: LASSO Regression for Variable Selection</p></td></tr><tr><td style='padding: 15px;'><p>7. Identify the Contribution of Predictors in Explaining the Variation in Y</p><p style='margin: 0'>Variable &amp; Model Selection: Identify the Contribution of Predictors in Explaining the Variation in Y</p></td></tr><tr><td style='padding: 15px;'><p>8. Conclusions to Section 4</p><p style='margin: 0'>Variable &amp; Model Selection: Conclusions to Section 4</p></td></tr></tbody></table><br><h4>5. Dealing with Other Violations of the OLS Regression Models</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Data Transformations</p><p style='margin: 0'>Dealing with Other Violations of the OLS Regression Models: Data Transformations</p></td></tr><tr><td style='padding: 15px;'><p>2. Robust Regression-Deal with Outliers</p><p style='margin: 0'>Dealing with Other Violations of the OLS Regression Models: Robust Regression-Deal with Outliers</p></td></tr><tr><td style='padding: 15px;'><p>3. Dealing with Heteroscedasticity</p><p style='margin: 0'>Dealing with Other Violations of the OLS Regression Models: Dealing with Heteroscedasticity</p></td></tr><tr><td style='padding: 15px;'><p>4. Conclusions to Section 5</p><p style='margin: 0'>Dealing with Other Violations of the OLS Regression Models: Conclusions to Section 5</p></td></tr></tbody></table><br><h4>6. Generalized Linear Models (GLMs)</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. What are GLMs?</p><p style='margin: 0'>Generalized Linear Models (GLMs): What are GLMs?</p></td></tr><tr><td style='padding: 15px;'><p>2. Logistic regression</p><p style='margin: 0'>Generalized Linear Models (GLMs): Logistic regression</p></td></tr><tr><td style='padding: 15px;'><p>3. Logistic Regression for Binary Response Variable</p><p style='margin: 0'>Generalized Linear Models (GLMs): Logistic Regression for Binary Response Variable</p></td></tr><tr><td style='padding: 15px;'><p>4. Multinomial Logistic Regression</p><p style='margin: 0'>Generalized Linear Models (GLMs): Multinomial Logistic Regression</p></td></tr><tr><td style='padding: 15px;'><p>5. Regression for Count Data</p><p style='margin: 0'>Generalized Linear Models (GLMs): Regression for Count Data</p></td></tr><tr><td style='padding: 15px;'><p>6. Goodness of fit testing</p><p style='margin: 0'>Generalized Linear Models (GLMs): Goodness of fit testing</p></td></tr><tr><td style='padding: 15px;'><p>7. Conclusions to Section 6</p><p style='margin: 0'>Generalized Linear Models (GLMs): Conclusions to Section 6</p></td></tr></tbody></table><br><h4>7. Working with Non-Parametric and Non-Linear Data</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Polynomial and Non-linear regression</p><p style='margin: 0'>Working with Non-Parametric and Non-Linear Data: Polynomial and Non-linear regression</p></td></tr><tr><td style='padding: 15px;'><p>2. Generalized Additive Models (GAMs) in R</p><p style='margin: 0'>Working with Non-Parametric and Non-Linear Data: Generalized Additive Models (GAMs) in R</p></td></tr><tr><td style='padding: 15px;'><p>3. Boosted GAM Regression</p><p style='margin: 0'>Working with Non-Parametric and Non-Linear Data: Boosted GAM Regression</p></td></tr><tr><td style='padding: 15px;'><p>4. Multivariate Adaptive Regression Splines (MARS)</p><p style='margin: 0'>Working with Non-Parametric and Non-Linear Data: Multivariate Adaptive Regression Splines (MARS)</p></td></tr><tr><td style='padding: 15px;'><p>5. CART-Regression Trees in R</p><p style='margin: 0'>Working with Non-Parametric and Non-Linear Data: CART-Regression Trees in R</p></td></tr><tr><td style='padding: 15px;'><p>6. Conditional Inference Trees</p><p style='margin: 0'>Working with Non-Parametric and Non-Linear Data: Conditional Inference Trees</p></td></tr><tr><td style='padding: 15px;'><p>7. Random Forest(RF)</p><p style='margin: 0'>Working with Non-Parametric and Non-Linear Data: Random Forest(RF)</p></td></tr><tr><td style='padding: 15px;'><p>8. Gradient Boosting Regression</p><p style='margin: 0'>Working with Non-Parametric and Non-Linear Data: Gradient Boosting Regression</p></td></tr><tr><td style='padding: 15px;'><p>9. ML Model Selection</p><p style='margin: 0'>Working with Non-Parametric and Non-Linear Data: ML Model Selection</p></td></tr><tr><td style='padding: 15px;'><p>10. Conclusions to Section 7</p><p style='margin: 0'>Working with Non-Parametric and Non-Linear Data: Conclusions to Section 7</p></td></tr></tbody></table>

Packt

Statistics

Programming

Learn complete hands-on Regression analysis for practical Statistical modelling and Machine Learning in R

Regression Analysis for Statistics & Machine Learning in R

<strong>This course is designed for candidates looking to demonstrate foundational-level knowledge of cloud services of Microsoft Azure by clearing the AZ-900 Microsoft Azure fundamentals exam. The course is recommended for job seekers looking for a career in the cloud domain.</strong>
        <p>AZ-900 Azure fundamentals exam is intended for candidates with non-technical backgrounds, such as those involved in selling or purchasing cloud-based solutions and services, as well as those with a technical background who have a need to validate their foundational-level knowledge around cloud services and Azure. 

This course starts off by setting up a blueprint of what the course covers and how you will travel through the concepts. You will begin by exploring the benefits of cloud services and how as-a-service offerings function. You will further cover cloud models and core Azure architectural components. In the concluding modules, you will understand the Internet of Things (IoT) on Azure along with monitoring tools in Azure. 

There are four main parts to the course, first, you will learn cloud concepts, followed by acquiring core Azure services. Then, you will learn security, privacy, compliance, and trust in Azure. Finally, you will look at Azure pricing and support. 

The course comes bundled with Azure real-world examples to help you master Microsoft Azure at the same time help you in clearing the AZ-900 exam. 

By the end of this course, you will become skilled enough to confidently appear and pass the Microsoft Azure fundamentals examination in your first attempt.

All the resources are available on the GitHub repository at: https://github.com/PacktPublishing/AZ-900-Microsoft-Azure-Fundamentals-Exam-Quick-Prep</p>
        <h2>What You Will Learn</h2><p>Get well-versed with core Azure services and architecture components<br>Deploy an Azure virtual network, use Azure load balancer and VPN gateway<br>Provision a storage account and an Azure file share<br>Implement Azure database migration services<br>Understand Azure pricing and support options in Azure Cloud<br>Understand security, privacy, compliance, and trust in Azure</p>
        <h2>Audience</h2><p>The course is intended for a broader audience to help them learn Azure concepts quickly, crack the AZ-900 certificate exam, and earn the badge students willing to get certified from Microsoft, anyone who wants to build carrier in cloud Services, IT employees seeking promotion in their current role, a system administrator who are using cloud services in their day-to-day life, technology lovers who want to learn the latest technology and keep themselves up to date, will be highly benefitted from this course.<br><br>The zeal to learn new concepts and stay up to date are the only prerequisites required.</p>
        <h2>Approach</h2><p>The course is intended to help you learn Azure concepts quickly and give enough practice exercises which come under the curriculum of the AZ-900 Microsoft Azure fundamentals exam. You can crack this AZ-900 certificate exam and earn the badge with the help of this course.</p>
        <h2>Key Features</h2><p>Get to grips with Azure fundamental concepts in an engaging and quick way * Filled with real-world examples to help you master Microsoft Azure and clear the AZ-900 exam easily * Prepare for the Microsoft AZ-900 Azure certification exam with real-world scenarios to help you master Azure</p>
        <h2>Github Repo</h2><p>https://github.com/packtpublishing/az-900-microsoft-azure-fundamentals-exam-quick-prep</p>
        <h2>About the Author</h2><h3>Vijay Saini</h3><p>Vijay Saini is an accomplished IT professional who brings a wealth of expertise to the table. With a diversified background across multiple domains, Vijay has proven himself a valuable asset to his current role as a leading cloud service provider. His strong focus on automation has resulted in significant cost savings for the business, making him a valuable asset to the team.

Vijay is highly knowledgeable in the areas of Microsoft Azure, cloud technologies, DBMS, and Python, and is a specialist in automation using PowerShell. With a passion for teaching, Vijay has leveraged e-learning platforms to share his expertise with others, helping them develop their own skills and knowledge.</p>
        <h2>Course Outline</h2><h4>1. Course Introduction</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Course Introduction and Structure</p><p style='margin: 0'>This video provides an introduction to the course and its structure.</p></td></tr><tr><td style='padding: 15px;'><p>2. About Exam AZ-900: Microsoft Azure Fundamentals</p><p style='margin: 0'>This video briefs you about AZ-900: Microsoft Azure fundamentals exam.</p></td></tr></tbody></table><br><h4>2. Getting Started with Azure</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. How to Create your Free Azure Account</p><p style='margin: 0'>This video demonstrates how to create your free Azure account.</p></td></tr><tr><td style='padding: 15px;'><p>2. Azure Portal Walk-Through</p><p style='margin: 0'>This video shows the walk-through of Azure portal.</p></td></tr></tbody></table><br><h4>3. Understanding Cloud Computing Concepts</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Section Introduction</p><p style='margin: 0'>This video provides an introduction to the section.</p></td></tr><tr><td style='padding: 15px;'><p>2. Essential Cloud Terminology</p><p style='margin: 0'>This video gets you acquainted with essential cloud terminology.</p></td></tr><tr><td style='padding: 15px;'><p>3. What is Cloud</p><p style='margin: 0'>This video provides an overview of cloud and standard definition for the same.</p></td></tr><tr><td style='padding: 15px;'><p>4. Why Cloud? Benefits and Considerations of Using Cloud Services</p><p style='margin: 0'>This video explains why cloud is important and what are the benefits and considerations of using cloud services. You will also look at advantages and disadvantages of using cloud.</p></td></tr><tr><td style='padding: 15px;'><p>5. Different Cloud Deployment Models</p><p style='margin: 0'>This video shows different cloud deployment models.</p></td></tr><tr><td style='padding: 15px;'><p>6. Different Cloud Service Models</p><p style='margin: 0'>This video talks about different cloud service models. You will also learn what and all type of cloud services are out there which you can use as per your requirement.</p></td></tr></tbody></table><br><h4>4. Core Architectural Components of Azure</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Azure Subscriptions</p><p style='margin: 0'>This video talks and demonstrates Azure Subscriptions.</p></td></tr><tr><td style='padding: 15px;'><p>2. Azure Management Groups</p><p style='margin: 0'>This video talks about the Azure Management Groups.</p></td></tr><tr><td style='padding: 15px;'><p>3. Resource Group</p><p style='margin: 0'>This video explains resource group.</p></td></tr></tbody></table><br><h4>5. Understand Core Azure Services - Compute</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Core Azure Products - Compute</p><p style='margin: 0'>This video explains core Azure products - compute.</p></td></tr><tr><td style='padding: 15px;'><p>2. Create a Virtual Machine (Basic Options)</p><p style='margin: 0'>This video helps you create a virtual machine (basic options).</p></td></tr><tr><td style='padding: 15px;'><p>3. Create a Virtual Machine (Advanced Options)</p><p style='margin: 0'>This video helps you create a virtual machine (advanced options).</p></td></tr><tr><td style='padding: 15px;'><p>4. Virtual Machine Walkthrough</p><p style='margin: 0'>This video focuses on virtual machine walkthrough.</p></td></tr><tr><td style='padding: 15px;'><p>5. Creating a Virtual Machine Using Azure PowerShell</p><p style='margin: 0'>This video focuses on creating a virtual machine using Azure PowerShell.</p></td></tr></tbody></table><br><h4>6. Core Azure Products - Compute (App Service and Serverless Computing)</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Azure Container Instances</p><p style='margin: 0'>This video explains the Azure Container instances.</p></td></tr><tr><td style='padding: 15px;'><p>2. Serverless Computing</p><p style='margin: 0'>This video talks about serverless computing.</p></td></tr><tr><td style='padding: 15px;'><p>3. Introduction to Azure App Service</p><p style='margin: 0'>This video provides an introduction to Azure App Service.</p></td></tr><tr><td style='padding: 15px;'><p>4. Brief Overview of Azure App Service</p><p style='margin: 0'>This video provides a brief overview of Azure App Service.</p></td></tr></tbody></table><br><h4>7. Understand Core Azure Services - Networking Services</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Core Azure Architectural Components</p><p style='margin: 0'>This video explains the core Azure architectural components.</p></td></tr><tr><td style='padding: 15px;'><p>2. Core Azure Products - Networking</p><p style='margin: 0'>This video talks about core Azure products - networking.</p></td></tr><tr><td style='padding: 15px;'><p>3. Securing Network Connectivity</p><p style='margin: 0'>This video talks about securing network connectivity.</p></td></tr><tr><td style='padding: 15px;'><p>4. Azure DNS</p><p style='margin: 0'>This video talks about Azure DNS.</p></td></tr><tr><td style='padding: 15px;'><p>5. Virtual Network Gateway and VNET Peering</p><p style='margin: 0'>This video talks about the Virtual Network Gateway and VNET Peering.</p></td></tr></tbody></table><br><h4>8. Understand Core Azure Services - Storage</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Core Azure Products - Storage</p><p style='margin: 0'>This video explains the core Azure products - storage.</p></td></tr><tr><td style='padding: 15px;'><p>2. Core Azure Products - Database</p><p style='margin: 0'>This video explains core Azure products - database.</p></td></tr><tr><td style='padding: 15px;'><p>3. Importance of Storage</p><p style='margin: 0'>This video talks about the importance of storage.</p></td></tr><tr><td style='padding: 15px;'><p>4. Create Storage Account</p><p style='margin: 0'>This video helps create a storage account.</p></td></tr><tr><td style='padding: 15px;'><p>5. Understanding Storage Redundancy Options</p><p style='margin: 0'>This video helps us with understanding storage redundancy options.</p></td></tr><tr><td style='padding: 15px;'><p>6. Introduction to Azure File Sync</p><p style='margin: 0'>This video provides an introduction to Azure File Sync.</p></td></tr><tr><td style='padding: 15px;'><p>7. AzCopy</p><p style='margin: 0'>This video explains AzCopy.</p></td></tr><tr><td style='padding: 15px;'><p>8. Shared Access Keys</p><p style='margin: 0'>This video explains about shared access keys.</p></td></tr><tr><td style='padding: 15px;'><p>9. Shared Access Signature</p><p style='margin: 0'>This video explains about the shared access signature.</p></td></tr></tbody></table><br><h4>9. Azure Identity, Access, and Security</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Core Identity Services</p><p style='margin: 0'>This video explains the core identity services.</p></td></tr><tr><td style='padding: 15px;'><p>2. Zero Trust Model</p><p style='margin: 0'>This video explains the zero trust model.</p></td></tr><tr><td style='padding: 15px;'><p>3. Defense in depth</p><p style='margin: 0'>This video talks about defense in depth.</p></td></tr></tbody></table><br><h4>10. Cost Management in Azure</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Factors that Affect Cost in Azure</p><p style='margin: 0'>This video explains what are the factors that affect cost in Azure.</p></td></tr><tr><td style='padding: 15px;'><p>2. Pricing Calculator and the Total Cost of Ownership (TCO) Calculator</p><p style='margin: 0'>This video demonstrates the pricing calculator and the Total Cost of Ownership (TCO) calculator.</p></td></tr><tr><td style='padding: 15px;'><p>3. Use Azure Cost Management + Billing to Control Spending</p><p style='margin: 0'>This video talks about the use of Azure cost management + billing to control spending.</p></td></tr><tr><td style='padding: 15px;'><p>4. Purpose of Tags in Azure</p><p style='margin: 0'>This video talks about the purpose of tags in Azure.</p></td></tr></tbody></table><br><h4>11. Azure for Governance and Compliance</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Azure Governance Methodologies</p><p style='margin: 0'>This video talks about the Azure governance methodologies.</p></td></tr><tr><td style='padding: 15px;'><p>2. Security Tools and Features of Azure</p><p style='margin: 0'>This video talks about the security tools and features of Azure.</p></td></tr></tbody></table><br><h4>12. Features and Tools for Managing and Deploying Azure Resources</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Azure Management Tools</p><p style='margin: 0'>This video talks about the Azure management tools.</p></td></tr><tr><td style='padding: 15px;'><p>2. What Is Azure Resource Manager?</p><p style='margin: 0'>This video talks about the Azure Resource Manager.</p></td></tr><tr><td style='padding: 15px;'><p>3. ARM Template Overview</p><p style='margin: 0'>This video provides an overview of the ARM Templates, and you will explore it further to understand what lies in the future of it.</p></td></tr></tbody></table><br><h4>13. Monitoring Tools in Azure</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Monitoring and Reporting Options in Azure</p><p style='margin: 0'>This video helps us with monitoring and reporting options in Azure.</p></td></tr></tbody></table>

Cloud Computing

Microsoft

Microsoft Azure

This course is designed for candidates looking to demonstrate foundational-level knowledge of cloud services of Microsoft Azure by clearing the AZ-900 Microsoft Azure fundamentals exam. The course is recommended for job seekers looking for a career in the cloud domain.

AZ-900 Microsoft Azure Fundamentals Exam Quick Prep

NextGen Learning

Learn Ethical Hacking From A-Z: Beginner To Expert Course

<div id="course-pills-1">Duration<p>4 Days</p><p>24 CPD hours</p>This course is intended for<p>This class is intended for experienced developers who are responsible for managing big data transformations including:<br />Extracting, loading, transforming, cleaning, and validating data.<br />Designing pipelines and architectures for data processing.<br />Creating and maintaining machine learning and statistical models.<br />Querying datasets, visualizing query results and creating reports</p>Overview<p>Design and build data processing systems on Google Cloud Platform.<br />Leverage unstructured data using Spark and ML APIs on Cloud Dataproc.<br />Process batch and streaming data by implementing autoscaling data pipelines on Cloud Dataflow.<br />Derive business insights from extremely large datasets using Google BigQuery.<br />Train, evaluate and predict using machine learning models using TensorFlow and Cloud ML.<br />Enable instant insights from streaming data</p><p>Get hands-on experience with designing and building data processing systems on Google Cloud. This course uses lectures, demos, and hand-on labs to show you how to design data processing systems, build end-to-end data pipelines, analyze data, and implement machine learning. This course covers structured, unstructured, and streaming data.</p></div><div id="course-pills-2"><h4>Introduction to Data Engineering</h4><ul><li>Explore the role of a data engineer.</li><li>Analyze data engineering challenges.</li><li>Intro to BigQuery.</li><li>Data Lakes and Data Warehouses.</li><li>Demo: Federated Queries with BigQuery.</li><li>Transactional Databases vs Data Warehouses.</li><li>Website Demo: Finding PII in your dataset with DLP API.</li><li>Partner effectively with other data teams.</li><li>Manage data access and governance.</li><li>Build production-ready pipelines.</li><li>Review GCP customer case study.</li><li>Lab: Analyzing Data with BigQuery.</li></ul><h4>Building a Data Lake</h4><ul><li>Introduction to Data Lakes.</li><li>Data Storage and ETL options on GCP.</li><li>Building a Data Lake using Cloud Storage.</li><li>Optional Demo: Optimizing cost with Google Cloud Storage classes and Cloud Functions.</li><li>Securing Cloud Storage.</li><li>Storing All Sorts of Data Types.</li><li>Video Demo: Running federated queries on Parquet and ORC files in BigQuery.</li><li>Cloud SQL as a relational Data Lake.</li><li>Lab: Loading Taxi Data into Cloud SQL.</li></ul><h4>Building a Data Warehouse</h4><ul><li>The modern data warehouse.</li><li>Intro to BigQuery.</li><li>Demo: Query TB+ of data in seconds.</li><li>Getting Started.</li><li>Loading Data.</li><li>Video Demo: Querying Cloud SQL from BigQuery.</li><li>Lab: Loading Data into BigQuery.</li><li>Exploring Schemas.</li><li>Demo: Exploring BigQuery Public Datasets with SQL using INFORMATION_SCHEMA.</li><li>Schema Design.</li><li>Nested and Repeated Fields.</li><li>Demo: Nested and repeated fields in BigQuery.</li><li>Lab: Working with JSON and Array data in BigQuery.</li><li>Optimizing with Partitioning and Clustering.</li><li>Demo: Partitioned and Clustered Tables in BigQuery.</li><li>Preview: Transforming Batch and Streaming Data.</li></ul><h4>Introduction to Building Batch Data Pipelines</h4><ul><li>EL, ELT, ETL.</li><li>Quality considerations.</li><li>How to carry out operations in BigQuery.</li><li>Demo: ELT to improve data quality in BigQuery.</li><li>Shortcomings.</li><li>ETL to solve data quality issues.</li></ul><h4>Executing Spark on Cloud Dataproc</h4><ul><li>The Hadoop ecosystem.</li><li>Running Hadoop on Cloud Dataproc.</li><li>GCS instead of HDFS.</li><li>Optimizing Dataproc.</li><li>Lab: Running Apache Spark jobs on Cloud Dataproc.</li></ul><h4>Serverless Data Processing with Cloud Dataflow</h4><ul><li>Cloud Dataflow.</li><li>Why customers value Dataflow.</li><li>Dataflow Pipelines.</li><li>Lab: A Simple Dataflow Pipeline (Python/Java).</li><li>Lab: MapReduce in Dataflow (Python/Java).</li><li>Lab: Side Inputs (Python/Java).</li><li>Dataflow Templates.</li><li>Dataflow SQL.</li></ul><h4>Manage Data Pipelines with Cloud Data Fusion and Cloud Composer</h4><ul><li>Building Batch Data Pipelines visually with Cloud Data Fusion.</li><li>Components.</li><li>UI Overview.</li><li>Building a Pipeline.</li><li>Exploring Data using Wrangler.</li><li>Lab: Building and executing a pipeline graph in Cloud Data Fusion.</li><li>Orchestrating work between GCP services with Cloud Composer.</li><li>Apache Airflow Environment.</li><li>DAGs and Operators.</li><li>Workflow Scheduling.</li><li>Optional Long Demo: Event-triggered Loading of data with Cloud Composer, Cloud Functions, Cloud Storage, and BigQuery.</li><li>Monitoring and Logging.</li><li>Lab: An Introduction to Cloud Composer.</li></ul><h4>Introduction to Processing Streaming Data</h4><ul><li>Processing Streaming Data.</li></ul><h4>Serverless Messaging with Cloud Pub/Sub</h4><ul><li>Cloud Pub/Sub.</li><li>Lab: Publish Streaming Data into Pub/Sub.</li></ul><h4>Cloud Dataflow Streaming Features</h4><ul><li>Cloud Dataflow Streaming Features.</li><li>Lab: Streaming Data Pipelines.</li></ul><h4>High-Throughput BigQuery and Bigtable Streaming Features</h4><ul><li>BigQuery Streaming Features.</li><li>Lab: Streaming Analytics and Dashboards.</li><li>Cloud Bigtable.</li><li>Lab: Streaming Data Pipelines into Bigtable.</li></ul><h4>Advanced BigQuery Functionality and Performance</h4><ul><li>Analytic Window Functions.</li><li>Using With Clauses.</li><li>GIS Functions.</li><li>Demo: Mapping Fastest Growing Zip Codes with BigQuery GeoViz.</li><li>Performance Considerations.</li><li>Lab: Optimizing your BigQuery Queries for Performance.</li><li>Optional Lab: Creating Date-Partitioned Tables in BigQuery.</li></ul><h4>Introduction to Analytics and AI</h4><ul><li>What is AI?.</li><li>From Ad-hoc Data Analysis to Data Driven Decisions.</li><li>Options for ML models on GCP.</li></ul><h4>Prebuilt ML model APIs for Unstructured Data</h4><ul><li>Unstructured Data is Hard.</li><li>ML APIs for Enriching Data.</li><li>Lab: Using the Natural Language API to Classify Unstructured Text.</li></ul><h4>Big Data Analytics with Cloud AI Platform Notebooks</h4><ul><li>What's a Notebook.</li><li>BigQuery Magic and Ties to Pandas.</li><li>Lab: BigQuery in Jupyter Labs on AI Platform.</li></ul><h4>Production ML Pipelines with Kubeflow</h4><ul><li>Ways to do ML on GCP.</li><li>Kubeflow.</li><li>AI Hub.</li><li>Lab: Running AI models on Kubeflow.</li></ul><h4>Custom Model building with SQL in BigQuery ML</h4><ul><li>BigQuery ML for Quick Model Building.</li><li>Demo: Train a model with BigQuery ML to predict NYC taxi fares.</li><li>Supported Models.</li><li>Lab Option 1: Predict Bike Trip Duration with a Regression Model in BQML.</li><li>Lab Option 2: Movie Recommendations in BigQuery ML.</li></ul><h4>Custom Model building with Cloud AutoML</h4><ul><li>Why Auto ML?</li><li>Auto ML Vision.</li><li>Auto ML NLP.</li><li>Auto ML Tables.</li></ul></div>

Nexus Human

Google Data Analytics

Data Engineering

Big Data Analytics

Data Science

Google Cloud

Data Skills

Data Engineering on Google Cloud

<div id="course-pills-1">Duration<p>3 Days</p><p>18 CPD hours</p>This course is intended for<p>Experienced system administrators or network administrators, software and DevOps engineers</p>Overview<p>By the end of the course, you should be able to meet the following objectives:<br />Describe VMware NSX Advanced Load Balancer architecture<br />Describe VMware NSX Advanced Load Balancer components and main functions<br />Explain VMware NSX Advanced Load Balancer key features and benefits<br />Describe and leverage VMware NSX Advanced Load Balancer REST API<br />Describe and leverage VMware NSX Advanced Load Balancer SDKs with extended focus on Python SDK<br />Leverage REST API and SDK features and functions to provision application delivery components<br />Describe and leverage VMware NSX Advanced Load Balancer Ansible and Terraform integrations<br />Describe and leverage VMware NSX Advanced Load Balancer Github, Docker (avinetworks/avitools), Ansible Galaxy and other open source resources to accelerate the automation planning and implementation<br />Leverage VMware NSX Advanced Load Balancer Ansible and Terraform integrations to provision infrastructure components<br />Leverage VMware NSX Advanced Load Balancer Ansible and Terraform integrations to automate and streamline application delivery services provisioning</p><p>This three-day, fast-paced course provides comprehensive training on how to automate infrastructure and application components of VMware NSX Advanced Load Balancer (Avi Networks) solution. This course covers key application delivery features of NSX Advanced Load Balancer (Avi Networks) features and functionality offered in VMware NSX Advanced Load Balancer 18.2 release and focuses on how to plan and implement automation of infrastructure and application components leveraging REST API, SDK or automation solutions such as Ansible, Terraform or similar. Access to a software-defined data center environment is provided through hands-on labs to reinforce the skills and concepts presented in the course.</p></div><div id="course-pills-2"><h4>Course Introduction</h4><ul><li>Introductions and course logistics</li><li>Course objectives</li></ul><h4>Introduction to NSX Advanced Load Balancer</h4><ul><li>Introduce NSX Advanced Load Balancer</li><li>Discuss NSX Advanced Load Balancer use cases, and benefits</li><li>Explain NSX Advanced Load Balancer architecture and components</li><li>Explain the management, control, data, and consumption planes and functions</li></ul><h4>Virtual Services Configuration Concepts</h4><ul><li>Explain Virtual Service components</li><li>Explain Virtual Service types</li><li>Explain and configure basic virtual services components such as Application Profiles, Network Profiles,Pools and Health Monitors</li></ul><h4>Pools Configuration Concepts</h4><ul><li>Explain and deep dive on Pool configuration options</li><li>Describe multiple load balancing algorithms</li><li>Explain multiple Health Monitor types</li><li>Explain multiple Persistent profiles</li><li>Explain and configure Pool Groups</li></ul><h4>Leveraging NSX Advanced Load Balancer REST API</h4><ul><li>Explain NSX Advanced Load Balancer automation vision</li><li>Explain and introduce NSX Advanced Load Balancer REST API</li><li>Describe NSX Advanced Load Balancer REST API methods and capabilities</li><li>Describe NSX Advanced Load Balancer REST API session handling properties such authentication, API versioning and tenancy model</li><li>Deep dive on NSX Advanced Load Balancer REST API Object Model</li><li>Explain and investigate NSX Advanced Load Balancer REST API leveraging browser and command line utilities</li><li>Explain and interact with NSX Advanced Load Balancer REST API leveraging browser, Postman and Curl</li><li>Explain Swagger-based API Documentation</li><li>Explain and leverage NSX Advanced Load Balancer Inventory API</li><li>Explain and leverage NSX Advanced Load Balancer methods such as GET, PUT, POST and PATCH and associated queries, filters and parameters</li><li>Deep dive on NSX Advanced Load Balancer PATCH method</li><li>Explain and leverage NSX Advanced Load Balancer Analytics API</li><li>Explain and leverage NSX Advanced Load Balancer MACRO API</li></ul><h4>NSX Advanced Load Balancer Software-Defined Kits (SDKs) and ControlScripts</h4><ul><li>Introduce NSX Advanced Load Balancer SDKs</li><li>Describe, install and leverage NSX Advanced Load Balancer Python SDK</li><li>Deep dive on NSX Advanced Load Balancer Python SDK</li><li>Describe and leverage Golang SDK</li><li>Leverage NSX Advanced Load Balancer open source resources such as Github, etc to accelerate SDKs adoption</li><li>Describe NSX Advanced Load Balancer Events and Alerts framework</li><li>Introduce ControlScripts foundations</li><li>Leverage ControlScripts to automate configuration changes and alerts remediation</li></ul><h4>Automating NSX Advanced Load Balancer Application Delivery Services with Ansible and Terraform</h4><ul><li>Introduce NSX Advanced Load Balancer Configuration Orchestration and Management vision</li><li>Introduce and explain Ansible foundations</li><li>Describe Ansible and NSX Advanced Load Balancer Ansible capabilities</li><li>Deep dive and implement NSX Advanced Load Balancer Ansible Core configuration modules (avinetworks/avisdk)</li><li>Deep dive and implement Ansible NSX Advanced</li><li>Load Balancer Declarative configuration role (avinetworks/aviconfig)</li><li>Leverage Swagger NSX Advanced Load Balancer REST API models to develop and implement Ansible playbooks</li><li>Explain application delivery configuration automation</li><li>approach and models</li><li>Apply configuration automation models with Ansible</li><li>Introduce and explain Terraform foundations</li><li>Describe Terraform and NSX Advanced Load Balancer Terraform capabilities</li><li>Deep dive and implement NSX Advanced Load Balancer Terraform Provider</li><li>Leverage Swagger NSX Advanced Load Balancer REST API models to develop and implement Terraform plans</li><li>Apply configuration automation models with Terraform</li></ul><h4>Automating NSX Advanced Load Balancer Infrastructure with Ansible and Terraform</h4><ul><li>Introduce NSX Advanced Load Balancer infrastructure Automation vision</li><li>Describe infrastructure deployment approach and capabilities</li><li>Describe Ansible and NSX Advanced Load Balancer Ansible Infrastructure deployment approach and capabilities</li><li>Describe Terraform and NSX Advanced Load Balancer Terraform deployment approach and capabilities</li><li>Leverage Terraform to deploy Controllers and perform system configuration, including control plane cluster setup</li><li>Leverage Terraform to provision Cloud, Service Engine Groups and Service Engine components</li><li>Describe and leverage Ansible roles to deploy Controllers and perform initial system configuration, including control plane cluster setup</li><li>Leverage Ansible declarative and core roles to provision Cloud, Service Engine Groups and Service Engine components</li><li>Describe and implement combined Terraform + Ansible model to streamline NSX Advanced Load Balancer solution deployment</li></ul></div>

VMware Vsphere

Service Design Courses (SDC)

Microsoft Virtual Academy (MVA)

VMware NSX Advanced Load Balancer: Infrastructure and Application Automation

<p><strong>Level 3 Data Entry, Data Analytics, Document Control &amp; Virtual Assistant Diploma</strong></p><p><br />Learn everything there is to discover an array of limitless opportunities in our Data Entry, Data Analytics, Document Control &amp; Virtual Assistant Diploma Course. Explore the complexities of handling, evaluating, and managing data as you set out to become a professional.</p><p><strong>4-in-1 Bundle Includes: </strong></p><ul><li><strong>Course 01: </strong>Data Entry</li><li><strong>Course 02: </strong>Data Analytics</li><li><strong>Course 03: </strong>Document Control</li><li><strong>Course 04: </strong>Virtual Assistant</li></ul><p>Become proficient in doing Data Entry in Microsoft Word and in Microsoft Excel, understand Advanced Data Entry Techniques which will help with your Data Entry Career and Portfolio.</p><p>Go through the statistics of data analytics, learning the storing and gathering of data along with the tools to do so. Learn document control strategies next to document control lifecycle and the management as well.</p><p>Gain an understanding of the role and responsibilities along with the knowledge and skills required to become a Virtual Assistant. These 4 courses are your perfect gateway to your ultimate success in the field of Data Entry Administrator, a Virtual Assistant, Document Control Analyst or a Data Analytics Manager.</p><p>So don't miss out on this opportunity to upskill your career to the next level and in doing so without making a dent in your wallet as you will save up to 90% off.</p><p><strong>Key Features</strong></p><ul><li>Instant e-certificate</li><li>Fully online, interactive course with audio voiceover</li><li>Developed by qualified professionals in the field</li><li>Self-paced learning and laptop, tablet, smartphone-friendly</li><li>24/7 Learning Assistance</li><li>Discounts on bulk purchases</li></ul><p><strong>Course Curriculum</strong></p><p><strong>Efficient Data Entry</strong></p><ul><li>Module 01: Introduction to Data Entry and Essential Tools</li><li>Module 02: Data Entry in Microsoft Word</li><li>Module 03: Data Entry in Microsoft Excel</li><li>Module 04: Advanced Data Entry Techniques and Tools</li><li>Module 05: Data Entry Best Practices and Accuracy</li><li>Module 06: Building Your Data Entry Career and Portfolio</li></ul><p><strong>Data Analytics</strong></p><ul><li>Module 01: Introduction to the World of Data</li><li>Module 02: Basics of Data Analytics</li><li>Module 03: Statistics for Data Analytics</li><li>Module 04: Actions Taken in the Data Analysis Process</li><li>Module 05: Gathering the Right Information</li><li>Module 06: Storing Data</li><li>Module 07: Data Mining</li><li>Module 08: Excel for Data Analytics</li><li>Module 09: Tools for Data Analytics</li><li>Module 10: Data-Analytic Thinking</li><li>Module 11: Data Visualisation That Clearly Describes Insights</li><li>Module 12: Data Visualisation Tools</li></ul><p><strong>Document Control</strong></p><ul><li>Module 01: Introduction to Document Control</li><li>Module 02: Principles of Document Control and Elements of Document Control Environment</li><li>Module 03: Document Control Lifecycle</li><li>Module 04: Document Control Strategies and Instruments</li><li>Module 05: Document Management</li><li>Module 06: Quality Assurance and Controlling Quality of Documents</li><li>Module 07: Project Document Control</li><li>Module 08: Electronic Document Management Systems and Soft Copy Documentation</li></ul><p><strong>Virtual Assistant</strong></p><ul><li>Module 01: Introduction to Virtual Assistant</li><li>Module 02: Different Types of Virtual Assistants</li><li>Module 03: Be a Virtual Assistant</li><li>Module 04: Must-Have Skills for Virtual Assistants</li><li>Module 05: Essential Tools for a Virtual Assistant</li><li>Module 06: Finding Your Niche</li><li>Module 07: Get Hired for VA Jobs</li><li>Module 08: How to Set VA Business</li><li>Module 09: Admin Support- a Vital Part of VA</li><li>Module 10: How to Manage Clients</li><li>Module 11: Working with a Virtual Team</li><li>Module 12: Data Security Measures</li></ul><p><strong>Accreditation</strong></p><p>These courses are fully CPD QS accredited, providing you with up-to-date skills and knowledge and helping you to become more competent and effective in your chosen field.</p><p><strong>Certification</strong></p><p>Once you've successfully completed your course, you will immediately be sent a digital certificate. Also, you can have your printed certificate delivered by post (shipping cost £3.99).</p><p><strong>Assessment</strong></p><p>At the end of the course, there will be an online assessment, which you will need to pass to complete the course.</p><h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        40 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 looking to improve their Data Entry, Document Control &amp; Virtual Assistant skills.</p>
                        </div><h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <ul><li>Virtual Assistant</li><li>Admin, secretarial &amp; PA</li><li>Document Control Analyst</li><li>Data Analytics Manager</li><li>Python &amp; Data Scientist</li><li>Data Analyst</li><li>Data Entry Clerk</li><li>Data Entry Operator</li><li>Data Entry Specialist</li><li>Data Entry Administrator</li><li>Data Entry Analyst</li></ul>
                        </div><h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4> Digital certificate</h4>
        <p>
            Digital certificate -
            Included
        </p>
        <h4> Hard copy certificate</h4>
        <p>
            Hard copy certificate -
            Included
        </p>
            <div><p>You will get the hard copy certificates for Free! The delivery charge of the hard copy certificate inside the UK is £3.99 each.</p></div>

                        </div>

Level 3 Data Entry, Data Analytics, Document Control & Virtual Assistant Diploma Course

<strong>A knowledge of Windows PowerShell is a must for IT professionals and this course is a one-stop-shop for gaining this necessary and in-demand skill.

This course is designed to take system administrators to an advanced level in PowerShell scripting. You will find ways to automate your daily work using the advantages of PowerShell scripting.</strong>
        <p>PowerShell is a task automation and configuration management program from Microsoft, consisting of a command-line shell and the associated scripting language. Professionals who want to start with PowerShell and have some basic idea of the command line will find it extremely easy to understand the underlying concepts of PowerShell and will be able to integrate PowerShell with non-Microsoft products as well.

Here, you will look at the PowerShell logging module, installing software with PowerShell, automation solution for daily validation reports, database interaction using PowerShell, automation for Web/App Service status, Windows Task Scheduler and scheduling PowerShell scripts to run, pulling reports from Windows event viewer using this PowerShell, looking at PowerShell advanced functions and modules, building validation, PowerShell with Windows Event Viewer, PowerShell for programming, and using PowerShell as an automation tool.

You will be working on a project where you will develop a robust automation solution for 'Application and System Validation', which generates a consolidated HTML report in the end, displaying all different test case results.

By the end of this course, you will have learned advanced-level knowledge of PowerShell scripting. You will easily automate your daily repetitive work using PowerShell scripting.

All the resource files are added to the GitHub repository at: https://github.com/PacktPublishing/PowerShell-for-Automating-Administration</p>
        <h2>What You Will Learn</h2><p>Learn automation of administration work with Windows PowerShell<br>Develop application and server validation mechanism<br>Develop file purge and archive mechanism from scratch<br>Learn an important skill for Windows Server Administration<br>Learn the concepts of Windows PowerShell scripting<br>Write your own automation scripts for complex scenarios with ease</p>
        <h2>Audience</h2><p>This course is designed for students/IT professionals who desire to automate their or their team's day-to-day manual work, system administrators, and aspirants seeking a career in IT automation. Application support analysts and cloud consultants will also gain a lot from this course.<br><br>To get the most out of this course, you should have some basic understanding of the command line (Win CMD/Unix Shell), and a PC/laptop installed with Windows OS.</p>
        <h2>Approach</h2><p>This is a comprehensive, easy-to-understand, to-the-point, and well-balanced course on automating tasks using PowerShell scripts. There will be a brief introduction to what you will be learning/implementing/executing at the start of each video to set the right expectations. You will be learning by working on practical projects and assignments.</p>
        <h2>Key Features</h2><p>Learn and implement advanced concepts such as file backup, archival, and purge solution * Comes bundled with all the resource files, PPTs, and assignment questions to leverage your learning * A well-balanced, application-based, and complete course to use PowerShell for automating tasks</p>
        <h2>Github Repo</h2><p>https://github.com/PacktPublishing/PowerShell-for-Automating-Administration</p>
        <h2>About the Author</h2><h3>Vijay Saini</h3><p>Vijay Saini is an accomplished IT professional who brings a wealth of expertise to the table. With a diversified background across multiple domains, Vijay has proven himself a valuable asset to his current role as a leading cloud service provider. His strong focus on automation has resulted in significant cost savings for the business, making him a valuable asset to the team.

Vijay is highly knowledgeable in the areas of Microsoft Azure, cloud technologies, DBMS, and Python, and is a specialist in automation using PowerShell. With a passion for teaching, Vijay has leveraged e-learning platforms to share his expertise with others, helping them develop their own skills and knowledge.</p>
        <h2>Course Outline</h2><h4>1. PowerShell to Install Software on Multiple Remote Computers</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Software Installations with PowerShell - Part 1</p><p style='margin: 0'>This video explains PowerShell and helps you understand ways to install and download the applications/tools with the help of PowerShell.</p></td></tr><tr><td style='padding: 15px;'><p>2. Software Installations with PowerShell - Part 2</p><p style='margin: 0'>This video will help you develop a super powerful PowerShell script that takes care of end-to-end software installation for us. Here, you will successfully download and install the WinRAR and Notepad++ applications.</p></td></tr></tbody></table><br><h4>2. PowerShell Automation Concepts</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. How to Hide Date Time Using PowerShell</p><p style='margin: 0'>This video will help you hide date and time in the taskbar using PowerShell in a Windows 11 machine.</p></td></tr><tr><td style='padding: 15px;'><p>2. Learn PowerShell Logging Module</p><p style='margin: 0'>This video explains automating systems and the application validation process. Here, you will be using the PowerShell Logging module, which helps automate complex operations that run error-free.</p></td></tr></tbody></table><br><h4>3. CSV File Handling with PowerShell</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. CSV File Handling with PowerShell</p><p style='margin: 0'>This video will help you with the handling or actually doing some sort of operations on the CSV file using PowerShell. Here, you will use the live structured data in a CSV file and perform various operations on it.</p></td></tr></tbody></table><br><h4>4. Administering Planned Service Restarts</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Manage Windows Services Using PowerShell - 1</p><p style='margin: 0'>This is the first of the two-part video where you will learn the commandlet Get-Service that helps fetch the services.</p></td></tr><tr><td style='padding: 15px;'><p>2. Manage Windows Services Using PowerShell - 2</p><p style='margin: 0'>This is the second of the two-part video where you will learn the other commandlets such as Set-Service, Restart-Service, Start-Service, and Stop-Service.</p></td></tr><tr><td style='padding: 15px;'><p>3. Automation of Planned Service Restarts - Version 1</p><p style='margin: 0'>This is the first of the two-part video where you will work on a PowerShell script for a centralized solution to deal with restarting fixed services on multiple servers.</p></td></tr><tr><td style='padding: 15px;'><p>4. Automation of Planned Service Restarts - Version 2</p><p style='margin: 0'>This is the second of the two-part video where you will work on a PowerShell script for a centralized solution to deal with restarting different services on different servers.</p></td></tr></tbody></table><br><h4>5. Project Introduction</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction</p><p style='margin: 0'>This video provides an introduction to the project that you will be working on in this section.</p></td></tr><tr><td style='padding: 15px;'><p>2. Project Directory and File Structure</p><p style='margin: 0'>This video demonstrates the project directory and file structure that will help you give an upper hand in customizing the automation part as per your requirement.</p></td></tr><tr><td style='padding: 15px;'><p>3. XML Configuration File</p><p style='margin: 0'>This video explains the XML configuration file that is used to configure the parameters and initial settings for our computer programs.</p></td></tr></tbody></table><br><h4>6. Lab Setup</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Lab Setup Guide</p><p style='margin: 0'>This video is a guide to the lab setup where you will understand the architecture of the simple application.</p></td></tr><tr><td style='padding: 15px;'><p>2. Lab Setup: Deploying the Resources in Cloud</p><p style='margin: 0'>This is a lab setup video where you will be deploying the resources in Cloud.</p></td></tr><tr><td style='padding: 15px;'><p>3. Lab Setup: Deploying the Validation Scripts</p><p style='margin: 0'>This is a lab setup video where you will be deploying the Validation Scripts.</p></td></tr><tr><td style='padding: 15px;'><p>4. Lab Setup: Script Execution</p><p style='margin: 0'>This is a lab setup video where you will be looking at the execution of the script.</p></td></tr></tbody></table><br><h4>7. Server Validation Script</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Overview of Server Validation Script</p><p style='margin: 0'>This video provides an Overview of Server Validation Script.</p></td></tr><tr><td style='padding: 15px;'><p>2. Validation Functions Overview</p><p style='margin: 0'>This video provides an overview of the validation functions.</p></td></tr><tr><td style='padding: 15px;'><p>3. Validation Functions Discussion - Part 1</p><p style='margin: 0'>This is the first of the two-part video that focuses on the validation functions. Here, you will be studying these functions: Validate-SysInfo, Validate-URL, Validate-TopMemoryConsumingProcesses, Validate-DisktHealth, and Validate-SQLConnection.</p></td></tr><tr><td style='padding: 15px;'><p>4. Validation Functions Discussion - Part 2</p><p style='margin: 0'>This is the second of the two-part video that focuses on the validation functions. Here, you will be studying these functions: Validate-WebService, Validate-AppService, Validate-IIS, Validate-SQLDatabase, and Validate-AppVersion.</p></td></tr></tbody></table><br><h4>8. Report Consolidation and Code Enhancement</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Report Consolidation - Template Overview</p><p style='margin: 0'>This video explains the report consolidation script. Here, you will be looking at an overview of the template.</p></td></tr><tr><td style='padding: 15px;'><p>2. Report Consolidation - Script Overview</p><p style='margin: 0'>This video explains the report consolidation script. Here, you will be looking at implementing the script using PowerShell.</p></td></tr><tr><td style='padding: 15px;'><p>3. Code Enhancements - Logging</p><p style='margin: 0'>This video demonstrates code enhancements. Here, you will be using the logging module using PowerShell.</p></td></tr></tbody></table><br><h4>9. Productionization of the Application Validation Tool</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Code Changes to be able to execute Scripts Centrally</p><p style='margin: 0'>In this video, you will see what changes we can make in our application and system validation scripts to be able to put the scripts on a remote server; and we never have to login into the remote server at all, be it for executing the script or looking at the result.</p></td></tr><tr><td style='padding: 15px;'><p>2. Preparing Pull_Repos_and_Execute Script</p><p style='margin: 0'>This video demonstrates remote script execution architecture. If you don't want to copy the scripts to the server each time and want to fully automate it using PowerShell, then this video will be of great help.</p></td></tr><tr><td style='padding: 15px;'><p>3. Remote Execution of the Script from Terminal Server</p><p style='margin: 0'>In this video, you will be executing the script remotely from the terminal server.</p></td></tr></tbody></table>

Shell Scripting

A knowledge of Windows PowerShell is a must for IT professionals and this course is a one-stop-shop for gaining this necessary and in-demand skill.

This course is designed to take system administrators to an advanced level in PowerShell scripting. You will find ways to automate your daily work using the advantages of PowerShell scripting.

PowerShell for Automating Administration

<p><strong> 3-</strong><strong>in-1 Exclusive Bundle </strong></p> <p>Our extensive <strong>C++</strong> course is developed thoroughly for you to indulge and learn all the topics with utmost clarity and thorough explanation.</p> <p>This course includes not only one course but <strong>THREE</strong> courses within the bundle. So you are getting two extra courses for the price of one, no extra money! Our course aims to provide detailed insight into the C++ with full support from our teachers. So if you are looking for a convenient way to boost your knowledge further of the C++ topic but are too busy to go to a class, then enrol in this course and you are sorted!</p> <p>Our in-depth course has no time limit and can be accessed from anywhere in the world.</p> <p>You'll pick up a ton of fresh information, whether you're a novice or an advanced. The mega course's sheer size and breadth speak for itself! <strong>So, do not delay any further; we are excited and looking forward to letting you in our CPD Accredited course as much as you are!</strong></p> <p><strong>The following courses will not only fast-track your career but also make it even more rewarding:</strong></p> <ul> <li><strong>Course 01: </strong>C++ Programming Certificate Course</li><li><strong>Course 02: </strong>C++ Development: The Complete Coding Guide</li><li><strong>Course 03: </strong>Computer Vision By Using C++ and OpenCV with GPU support</li></ul> <p><strong><strong>Learning Outcome</strong></strong></p> <p>From this interactive course, you will be able to:</p> <ul> <li>Deep dive into the basics of C++.</li><li>Learn how to improve your skills in general.</li><li>Increase your ability to reason and solve problems.</li><li>Utilise the C++ to boost output.</li><li>Gain confidence and clarity in your communication.</li><li>Explore different career routes in this field.</li></ul><p>This comprehensive three-in-one<strong> C++ </strong>course equips you with critical guidance, methods, and strategies for increasing both employee and professional development. The C++ course from Next Generation's easy-to-digest and deliverable modules will provide you with the most essential and useful knowledge for growing your profession, from setting personal development goals to forming a cross-functional team.</p> <p><strong>Course Curriculum: </strong></p> <ul> <li>Starter Examples</li><li>Learning C Concepts</li><li>Data Types and Inference</li><li>Constants L and R Values</li><li>Increment &amp; Decrement Operators</li><li>Conditional Ternary Operator</li><li>Range-Based For Loop</li><li>Function Arguments Passed By Value</li><li>Multidimensional Arrays</li><li>Preprocessor Conditional Directives</li><li>Optical flow with Nvidia Flownet2 (Python)</li></ul> <p>And many more.....</p> <p><strong>Show off your new skills with a certificate of completion</strong></p> <p>Once you complete the <strong>C++ </strong>course, you will be eligible to request a digital certificate for free. For Printed Transcript &amp; Hardcopy Certificate-</p> <ul> <li><strong>4.99 GBP</strong> (Inside the UK Postal Fee)</li><li><strong>8.99 GBP</strong> (International Delivery Fee)</li></ul><h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        30 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>This comprehensive<strong> three-in-one </strong>bundled <strong>C++</strong> course has no restrictions for people registering for it. Anyone between the age of above sixteen can apply for the course. So whether you are an eager learner to explore the deeper unknown facts of the subject or a skilled individual in this field who wishes to enhance their career prospects further can take this course.</p> 
                        </div><h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                             <p>No previous knowledge is required to enrol in this training.</p> 
                        </div><h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                             <p>The aim of this exclusive bundle<strong> C++</strong> course is to help you toward your dream career. So, complete this course and enhance your skills to explore opportunities in relevant areas.</p> 
                        </div>

Certified Cryptocurrency Investigator Course (CCI)

Certificate in Teaching Program (CTP)

Certificate in Education & Training (CET)

Professional Skills Course (PSC)

Trainers Course

Continuous Professional Development (CPD)

Professional C++ Coder

JavaScript

Automation Testing

Node.js

Cypress

Python

This course is perfect for quality assurance professionals who want to step into automation testing with Cypress. You will learn Cypress from scratch and become a specialist in building a solid Cypress automation framework to test any real-world web application.

Cypress - Modern Automation Testing from Scratch + Framework

<div id="course-pills-1">Duration<p>5 Days</p><p>30 CPD hours</p>This course is intended for<p></p><p>Students in this course are interested in Azure development or in passing the Microsoft Azure Developer Associate certification exam.</p><p></p><p></p><p>This course teaches developers how to create end-to-end solutions in Microsoft Azure. Students will learn how to implement Azure compute solutions, create Azure Functions, implement and manage web apps, develop solutions utilizing Azure storage, implement authentication and authorization, and secure their solutions by using KeyVault and Managed Identities. Students will also learn how to connect to and consume Azure services and third-party services, and include event- and message-based models in their solutions. The course also covers monitoring, troubleshooting, and optimizing Azure solutions.</p><p></p>Prerequisites<p>To be successful in this course, learners should have the following: Hands-on experience with Azure IaaS and PaaS solutions, and the Azure Portal. Experience writing in an Azure supported language at the intermediate level. (C#, JavaScript, Python, or Java) Ability to write code to connect and perform operations on, a SQL or NoSQL database product. (SQL Server, Oracle, MongoDB, Cassandra or similar) Experience writing code to handle authentication, authorization, and other security principles at the intermediate level. A general understanding of HTML, the HTTP protocol and REST API interfaces.</p></div><div id="course-pills-2"><h3>1 - Explore Azure App Service</h3> <ul> <li>Examine Azure App Service</li> <li>Examine Azure App Service plans</li> <li>Deploy to App Service</li> <li>Explore authentication and authorization in App Service</li> <li>Discover App Service networking features</li> </ul> <h3>2 - Configure web app settings</h3> <ul> <li>Configure application settings</li> <li>Configure general settings</li> <li>Configure path mappings</li> <li>Enable diagnostic logging</li> <li>Configure security certificates</li> </ul> <h3>3 - Scale apps in Azure App Service</h3> <ul> <li>Examine autoscale factors</li> <li>Identify autoscale factors</li> <li>Enable autoscale in App Service</li> <li>Explore autoscale best practices</li> </ul> <h3>4 - Explore Azure App Service deployment slots</h3> <ul> <li>Explore staging environments</li> <li>Examine slot swapping</li> <li>Swap deployment slots</li> <li>Route traffic in App Service</li> </ul> <h3>5 - Explore Azure Functions</h3> <ul> <li>Discover Azure Functions</li> <li>Compare Azure Functions hosting options</li> <li>Scale Azure Functions</li> </ul> <h3>6 - Develop Azure Functions</h3> <ul> <li>Explore Azure Functions development</li> <li>Create triggers and bindings</li> <li>Connect functions to Azure services</li> </ul> <h3>7 - Explore Azure Blob storage</h3> <ul> <li>Explore Azure Blob storage</li> <li>Discover Azure Blob storage resource types</li> <li>Explore Azure Storage security features</li> <li>Discover static website hosting in Azure Storage</li> </ul> <h3>8 - Manage the Azure Blob storage lifecycle</h3> <ul> <li>Explore the Azure Blob storage lifecycle</li> <li>Discover Blob storage lifecycle policies</li> <li>Implement Blob storage lifecycle policies</li> <li>Rehydrate blob data from the archive tier</li> </ul> <h3>9 - Work with Azure Blob storage</h3> <ul> <li>Explore Azure Blob storage client library</li> <li>Create a client object</li> <li>Manage container properties and metadata by using .NET</li> <li>Set and retrieve properties and metadata for blob resources by using REST</li> </ul> <h3>10 - Explore Azure Cosmos DB</h3> <ul> <li>Identify key benefits of Azure Cosmos DB</li> <li>Explore the resource hierarchy</li> <li>Explore consistency levels</li> <li>Choose the right consistency level</li> <li>Explore supported APIs</li> <li>Discover request units</li> </ul> <h3>11 - Work with Azure Cosmos DB</h3> <ul> <li>Explore Microsoft .NET SDK v3 for Azure Cosmos DB</li> <li>Create stored procedures</li> <li>Create triggers and user-defined functions</li> <li>Explore change feed in Azure Cosmos DB</li> </ul> <h3>12 - Manage container images in Azure Container Registry</h3> <ul> <li>Discover the Azure Container Registry</li> <li>Explore storage capabilities</li> <li>Build and manage containers with tasks</li> <li>Explore elements of a Dockerfile</li> </ul> <h3>13 - Run container images in Azure Container Instances</h3> <ul> <li>Explore Azure Container Instances</li> <li>Run containerized tasks with restart policies</li> <li>Set environment variables in container instances</li> <li>Mount an Azure file share in Azure Container Instances</li> </ul> <h3>14 - Implement Azure Container Apps</h3> <ul> <li>Explore Azure Container Apps</li> <li>Explore containers in Azure Container Apps</li> <li>Implement authentication and authorization in Azure Container Apps</li> <li>Manage revisions and secrets in Azure Container Apps</li> <li>Explore Dapr integration with Azure Container Apps</li> </ul> <h3>15 - Explore the Microsoft identity platform</h3> <ul> <li>Explore the Microsoft identity platform</li> <li>Explore service principals</li> <li>Discover permissions and consent</li> <li>Discover conditional access</li> </ul> <h3>16 - Implement authentication by using the Microsoft Authentication Library</h3> <ul> <li>Explore the Microsoft Authentication Library</li> <li>Initialize client applications</li> </ul> <h3>17 - Implement shared access signatures</h3> <ul> <li>Discover shared access signatures</li> <li>Choose when to use shared access signatures</li> <li>Explore stored access policies</li> </ul> <h3>18 - Explore Microsoft Graph</h3> <ul> <li>Discover Microsoft Graph</li> <li>Query Microsoft Graph by using REST</li> <li>Query Microsoft Graph by using SDKs</li> <li>Apply best practices to Microsoft Graph</li> </ul> <h3>19 - Implement Azure Key Vault</h3> <ul> <li>Explore Azure Key Vault</li> <li>Discover Azure Key Vault best practices</li> <li>Authenticate to Azure Key Vault</li> </ul> <h3>20 - Implement managed identities</h3> <ul> <li>Explore managed identities</li> <li>Discover the managed identities authentication flow</li> <li>Configure managed identities</li> <li>Acquire an access token</li> </ul> <h3>21 - Implement Azure App Configuration</h3> <ul> <li>Explore the Azure App Configuration service</li> <li>Create paired keys and values</li> <li>Manage application features</li> <li>Secure app configuration data</li> </ul> <h3>22 - Explore API Management</h3> <ul> <li>Discover the API Management service</li> <li>Explore API gateways</li> <li>Explore API Management policies</li> <li>Create advanced policies</li> <li>Secure APIs by using subscriptions</li> <li>Secure APIs by using certificates</li> </ul> <h3>23 - Explore Azure Event Grid</h3> <ul> <li>Explore Azure Event Grid</li> <li>Discover event schemas</li> <li>Explore event delivery durability</li> <li>Control access to events</li> <li>Receive events by using webhooks</li> <li>Filter events</li> </ul> <h3>24 - Explore Azure Event Hubs</h3> <ul> <li>Discover Azure Event Hubs</li> <li>Explore Event Hubs Capture</li> <li>Scale your processing application</li> <li>Control access to events</li> <li>Perform common operations with the Event Hubs client library</li> </ul> <h3>25 - Discover Azure message queues</h3> <ul> <li>Choose a message queue solution</li> <li>Explore Azure Service Bus</li> <li>Discover Service Bus queues, topics, and subscriptions</li> <li>Explore Service Bus message payloads and serialization</li> <li>Explore Azure Queue Storage</li> <li>Create and manage Azure Queue Storage and messages by using .NET</li> </ul> <h3>26 - Monitor app performance</h3> <ul> <li>Explore Application Insights</li> <li>Discover log-based metrics</li> <li>Instrument an app for monitoring</li> <li>Select an availability test</li> <li>Troubleshoot app performance by using Application Map</li> </ul> <h3>27 - Develop for Azure Cache for Redis</h3> <ul> <li>Explore Azure Cache for Redis</li> <li>Configure Azure Cache for Redis</li> <li>Interact with Azure Cache for Redis by using .NET</li> </ul> <h3>28 - Develop for storage on CDNs</h3> <ul> <li>Explore Azure Content Delivery Networks</li> <li>Control cache behavior on Azure Content Delivery Networks</li> <li>Interact with Azure Content Delivery Networks by using .NET</li> </ul></div>

Microsoft AZ-900

Microsoft AZ-104

Microsoft AZ-303

Microsoft AZ-700

AWS Certified Solutions Architect

AZ-204T00 Developing Solutions for Microsoft Azure

<div id="course-pills-1">Duration<p>4 Days</p><p>24 CPD hours</p>This course is intended for<p></p><p>Software engineers concerned with building, managing and deploying AI solutions that leverage Azure AI Services, Azure AI Search, and Azure OpenAI. They are familiar with C# or Python and have knowledge on using REST-based APIs to build computer vision, language analysis, knowledge mining, intelligent search, and generative AI solutions on Azure.</p><p></p><p></p><p>AI-102 Designing and Implementing an Azure AI Solution is intended for software developers wanting to build AI infused applications that leverage?Azure AI Services,?Azure AI Search, and?Azure OpenAI. The course will use C# or Python as the programming language.</p><p></p>Prerequisites<p>Before attending this course, students must have:  </p><li>Knowledge of Microsoft Azure and ability to navigate the Azure portal  </li><li>Knowledge of either C# or Python  </li><li>Familiarity with JSON and REST programming semantics  <br />  Recommended course prerequisites  </li><li>AI-900T00: Microsoft Azure AI Fundamentals course<p></p></li></div><div id="course-pills-2"><h3>1 - Prepare to develop AI solutions on Azure</h3> <ul> <li>Define artificial intelligence</li> <li>Understand AI-related terms</li> <li>Understand considerations for AI Engineers</li> <li>Understand considerations for responsible AI</li> <li>Understand capabilities of Azure Machine Learning</li> <li>Understand capabilities of Azure AI Services</li> <li>Understand capabilities of the Azure Bot Service</li> <li>Understand capabilities of Azure Cognitive Search</li> </ul> <h3>2 - Create and consume Azure AI services</h3> <ul> <li>Provision an Azure AI services resource</li> <li>Identify endpoints and keys</li> <li>Use a REST API</li> <li>Use an SDK</li> </ul> <h3>3 - Secure Azure AI services</h3> <ul> <li>Consider authentication</li> <li>Implement network security</li> </ul> <h3>4 - Monitor Azure AI services</h3> <ul> <li>Monitor cost</li> <li>Create alerts</li> <li>View metrics</li> <li>Manage diagnostic logging</li> </ul> <h3>5 - Deploy Azure AI services in containers</h3> <ul> <li>Understand containers</li> <li>Use Azure AI services containers</li> </ul> <h3>6 - Analyze images</h3> <ul> <li>Provision an Azure AI Vision resource</li> <li>Analyze an image</li> <li>Generate a smart-cropped thumbnail</li> </ul> <h3>7 - Classify images</h3> <ul> <li>Provision Azure resources for Azure AI Custom Vision</li> <li>Understand image classification</li> <li>Train an image classifier</li> </ul> <h3>8 - Detect, analyze, and recognize faces</h3> <ul> <li>Identify options for face detection analysis and identification</li> <li>Understand considerations for face analysis</li> <li>Detect faces with the Azure AI Vision service</li> <li>Understand capabilities of the face service</li> <li>Compare and match detected faces</li> <li>Implement facial recognition</li> </ul> <h3>9 - Read Text in images and documents with the Azure AI Vision Service</h3> <ul> <li>Explore Azure AI Vision options for reading text</li> <li>Use the Read API</li> </ul> <h3>10 - Analyze video</h3> <ul> <li>Understand Azure Video Indexer capabilities</li> <li>Extract custom insights</li> <li>Use Video Analyzer widgets and APIs</li> </ul> <h3>11 - Analyze text with Azure AI Language</h3> <ul> <li>Provision an Azure AI Language resource</li> <li>Detect language</li> <li>Extract key phrases</li> <li>Analyze sentiment</li> <li>Extract entities</li> <li>Extract linked entities</li> </ul> <h3>12 - Build a question answering solution</h3> <ul> <li>Understand question answering</li> <li>Compare question answering to Azure AI Language understanding</li> <li>Create a knowledge base</li> <li>Implement multi-turn conversation</li> <li>Test and publish a knowledge base</li> <li>Use a knowledge base</li> <li>Improve question answering performance</li> </ul> <h3>13 - Build a conversational language understanding model</h3> <ul> <li>Understand prebuilt capabilities of the Azure AI Language service</li> <li>Understand resources for building a conversational language understanding model</li> <li>Define intents, utterances, and entities</li> <li>Use patterns to differentiate similar utterances</li> <li>Use pre-built entity components</li> <li>Train, test, publish, and review a conversational language understanding model</li> </ul> <h3>14 - Create a custom text classification solution</h3> <ul> <li>Understand types of classification projects</li> <li>Understand how to build text classification projects</li> </ul> <h3>15 - Create a custom named entity extraction solution</h3> <ul> <li>Understand custom named entity recognition</li> <li>Label your data</li> <li>Train and evaluate your model</li> </ul> <h3>16 - Translate text with Azure AI Translator service</h3> <ul> <li>Provision an Azure AI Translator resource</li> <li>Specify translation options</li> <li>Define custom translations</li> </ul> <h3>17 - Create speech-enabled apps with Azure AI services</h3> <ul> <li>Provision an Azure resource for speech</li> <li>Use the Azure AI Speech to Text API</li> <li>Use the text to speech API</li> <li>Configure audio format and voices</li> <li>Use Speech Synthesis Markup Language</li> </ul> <h3>18 - Translate speech with the Azure AI Speech service</h3> <ul> <li>Provision an Azure resource for speech translation</li> <li>Translate speech to text</li> <li>Synthesize translations</li> </ul> <h3>19 - Create an Azure AI Search solution</h3> <ul> <li>Manage capacity</li> <li>Understand search components</li> <li>Understand the indexing process</li> <li>Search an index</li> <li>Apply filtering and sorting</li> <li>Enhance the index</li> </ul> <h3>20 - Create a custom skill for Azure AI Search</h3> <ul> <li>Create a custom skill</li> <li>Add a custom skill to a skillset</li> </ul> <h3>21 - Create a knowledge store with Azure AI Search</h3> <ul> <li>Define projections</li> <li>Define a knowledge store</li> </ul> <h3>22 - Plan an Azure AI Document Intelligence solution</h3> <ul> <li>Understand AI Document Intelligence</li> <li>Plan Azure AI Document Intelligence resources</li> <li>Choose a model type</li> </ul> <h3>23 - Use prebuilt Azure AI Document Intelligence models</h3> <ul> <li>Understand prebuilt models</li> <li>Use the General Document, Read, and Layout models</li> <li>Use financial, ID, and tax models</li> </ul> <h3>24 - Extract data from forms with Azure Document Intelligence</h3> <ul> <li>What is Azure Document Intelligence?</li> <li>Get started with Azure Document Intelligence</li> <li>Train custom models</li> <li>Use Azure Document Intelligence models</li> <li>Use the Azure Document Intelligence Studio</li> </ul> <h3>25 - Get started with Azure OpenAI Service</h3> <ul> <li>Access Azure OpenAI Service</li> <li>Use Azure OpenAI Studio</li> <li>Explore types of generative AI models</li> <li>Deploy generative AI models</li> <li>Use prompts to get completions from models</li> <li>Test models in Azure OpenAI Studio's playgrounds</li> </ul> <h3>26 - Build natural language solutions with Azure OpenAI Service</h3> <ul> <li>Integrate Azure OpenAI into your app</li> <li>Use Azure OpenAI REST API</li> <li>Use Azure OpenAI SDK</li> </ul> <h3>27 - Apply prompt engineering with Azure OpenAI Service</h3> <ul> <li>Understand prompt engineering</li> <li>Write more effective prompts</li> <li>Provide context to improve accuracy</li> </ul> <h3>28 - Generate code with Azure OpenAI Service</h3> <ul> <li>Construct code from natural language</li> <li>Complete code and assist the development process</li> <li>Fix bugs and improve your code</li> </ul> <h3>29 - Generate images with Azure OpenAI Service</h3> <ul> <li>What is DALL-E?</li> <li>Explore DALL-E in Azure OpenAI Studio</li> <li>Use the Azure OpenAI REST API to consume DALL-E models</li> </ul> <h3>30 - Use your own data with Azure OpenAI Service</h3> <ul> <li>Understand how to use your own data</li> <li>Add your own data source</li> <li>Chat with your model using your own data</li> </ul> <h3>31 - Fundamentals of Responsible Generative AI</h3> <ul> <li>Plan a responsible generative AI solution</li> <li>Identify potential harms</li> <li>Measure potential harms</li> <li>Mitigate potential harms</li> <li>Operate a responsible generative AI solution</li> </ul></div>

Azure Machine Learning

Microsoft AI-900

Azure Cognitive Services

AI-102T00 Designing and Implementing an Azure AI Solution

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 CPD 
100 CPD hours / points  Accredited by CPD Quality Standards
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 Requirements 
No experience required. Just enrol & start learning python.
 Career path 
Upon completion of our Program, the potential career paths include:
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 Certificates 
CPD Accredited e-Certificate
 Digital certificate - Included 
CPD Accredited Framed (Hardcopy) Certificate
 Hard copy certificate - Included 
Enrolment Letter
 Digital certificate - Included 
QLS Endorsed Hard Copy Certificate
 Hard copy certificate - Included 
Student ID Card
 Digital certificate - Included 

Academy for Health and Fitness

Programming Fundamentals

Career Development

IT Certifications

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

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

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

Python for Beginners: Learn Python Programming (Python 3)

<p><strong>Start your career as a Data Analyst and earn upto £35,000/ Month </strong></p><p>Have you ever imagined commanding a six-figure salary with the power of Python? Welcome to the "Data Analyst with Python - Job Ready Program with Career Support", where the world of big data is at your fingertips, and the only limit is your own curiosity. Explore the revolutionary journey that is geared towards turning raw data into insightful decisions. Our comprehensive program paves the way to becoming a sought-after Data Analyst, unlocking the door to a thriving career field as Python continues to spearhead the data revolution.</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 Analysts with Python expertise, 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 Analyst with Python - Job Ready Program today and start your journey to becoming a successful Data Analyst!</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 Analyst with Python Job Ready Program:</p><ul><li><strong>Personalised Guidance:</strong> Our experienced mentors will provide one-on-one counselling sessions tailored to your specific needs. Whether you're a beginner or have some experience, we will guide you towards honing your skills and developing a strong foundation in Data Analysis with Python.<br /><br /></li><li><strong>One-On-One Consultation Sessions with Experts:</strong> Gain invaluable insights and guidance from seasoned professionals who have thrived in the Data Analyst 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 IT Helpdesk Support. 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> 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 100% money-back guarantee.<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>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>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 from Scratch</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: Python Level 1 Crash Course</li><li>Course 17: Python Programming from Scratch with My SQL Database</li></ul><p>These courses will help you to develop your knowledge and skills to become a <strong>successful Data Analyst</strong>.</p><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 Data Analyst with Python 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 Data Analyst with Python 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 17 premium courses related to Data Analysis with Python. These courses will teach you the knowledge and skills required to become a successful Data Analyst with Python Programmer. 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 Finance 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 Analysis 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 Analysis 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">
                            <p>This course is tailored to suit a broad spectrum of learners, including:</p><ul><li>Aspiring Data Analysts who want to launch a new career in data analytics.</li><li>Current analysts or professionals from similar fields looking to hone their Python skills and modernise their toolset.</li><li>Business and IT students or recent graduates desiring a competitive edge in the job market.</li><li>Career shifters interested in a more dynamic and high-paying field.</li><li>Any individual who loves working with numbers, solving problems, and has a curiosity for uncovering insights in data.</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><strong>Data Analyst</strong>: £27,000 - £60,000</li><li><strong>Senior Data Analyst</strong>: £40,000 - £75,000</li><li><strong>Data Scientist</strong>: £50,000 - £100,000</li><li><strong>Data Engineer</strong>: £45,000 - £90,000</li><li><strong>Analytics Manager</strong>: £60,000 - £120,000</li><li><strong>Director of Data Science</strong>: £90,000 - £150,000</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 as a Data Analyst and earn upto £35,000/ Month 
Have you ever imagined commanding a six-figure salary with the power of Python? Welcome to the "Data Analyst with Python - Job Ready Program with Career Support", where the world of big data is at your fingertips, and the only limit is your own curiosity. Explore the revolutionary journey that is geared towards turning raw data into insightful decisions. Our comprehensive program paves the way to becoming a sought-after Data Analyst, unlocking the door to a thriving career field as Python continues to spearhead the data revolution.
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 Analysts with Python expertise, 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 Analyst with Python - Job Ready Program today and start your journey to becoming a successful Data Analyst!
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 Analyst with Python Job Ready Program:
Personalised Guidance: Our experienced mentors will provide one-on-one counselling sessions tailored to your specific needs. Whether you're a beginner or have some experience, we will guide you towards honing your skills and developing a strong foundation in Data Analysis with Python.
One-On-One Consultation Sessions with Experts: Gain invaluable insights and guidance from seasoned professionals who have thrived in the Data Analyst 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 IT Helpdesk Support. Through our network, we'll connect you with exclusive job openings that are not easily accessible elsewhere.
Interview Preparation: 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.
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. .
If you have any questions, you can contact us. We will be happy to provide you with all the information you need.
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 from Scratch
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: Python Level 1 Crash Course
Course 17: Python Programming from Scratch with My SQL Database
These courses will help you to develop your knowledge and skills to become a successful Data Analyst.
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 Analyst 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 Analyst with Python 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 17 premium courses related to Data Analysis with Python. These courses will teach you the knowledge and skills required to become a successful Data Analyst with Python Programmer. 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 Finance 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 Analysis 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 Analysis with Python begins with us.
 CPD 
100 CPD hours / points  Accredited by CPD Quality Standards
 Who is this course for? 
This course is tailored to suit a broad spectrum of learners, including:
Aspiring Data Analysts who want to launch a new career in data analytics.
Current analysts or professionals from similar fields looking to hone their Python skills and modernise their toolset.
Business and IT students or recent graduates desiring a competitive edge in the job market.
Career shifters interested in a more dynamic and high-paying field.
Any individual who loves working with numbers, solving problems, and has a curiosity for uncovering insights in data.
 Requirements 
No experience required. Just enrol & start learning.
 Career path 
Data Analyst: £27,000 - £60,000
Senior Data Analyst: £40,000 - £75,000
Data Scientist: £50,000 - £100,000
Data Engineer: £45,000 - £90,000
Analytics Manager: £60,000 - £120,000
Director of Data Science: £90,000 - £150,000
 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 

Business Analytics & Intelligence

Data Analyst

Data Analyst with Python Job Ready Program with Career Support & Money Back Guarantee

<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 

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

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

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

Python Programming

Demand for data analysts, data scientists and data engineers tripled over the past five years, rising 231%. That's much faster than job postings overall in the UK, which grew 36%. Hence, the demand for skilled data analysts has skyrocketed in the UK and worldwide! On average, salaries for these data analysts' roles are £64,376 and keep rising.
With a broader overview of the data analyst's responsibility, data chart, and presentation tools, the bundle describes how to filter, improve and handle data to present various information. You'll learn process management, how to analyse data and how to make vital business decisions. The data analyst bundle will buckle you up to perform simple to complex business analysis tasks effectively and efficiently.
Furthermore, the data analyst course accentuates developing your programming skills for a data analyst, such as Python, SQL, and R. What's more? Besides strengthening Microsoft Excel skills for a data analyst, you can improve your expertise in Tableau, Google Data Studio and business analysis ability from this Data Analyst (Data Analytics) Bundle course. Hence, you can be an efficient data analyst and a competent candidate for a challenging position.
Learning Outcomes of Data Analyst (Data Analytics)
Upon completion of the Data Analyst (Data Analytics) program, you will have acquired:
Acquire a big-picture understanding of the data analyst role
Fundamentals of data analysis (data analysis), including process management, tools for data analysis, various charts
Ability to conduct thorough research and turn raw data into presentable information
Perform many data operations in Python's famous "pandas" library, including grouping, pivoting, joining and more!
Learn about NLP, Machine Learning (ML), data visualisation using Matplotlib, Seaborn and much more
Knowledge of all the essential SQL commands and become proficient in SQL tools like GROUP BY, JOINS, and Subqueries
Become competent in using sorting and filtering commands in SQL
Learn general cloud computing concepts and gain a solid understanding of the fundamental systems on which the cloud is based
Learn how to use the R programming language for data science, machine learning, and data visualisation
Learn data analytics with Tableau, business intelligence and data mining masterclass, basic Google Data studio
This Data Analyst (Data Analytics) Bundle Consists of the following Premium courses:
Course 01: Introduction to Data Analysis
Course 02: Python for Data Analysis
Course 03: SQL Programming Masterclass
Course 04: Data Science & Machine Learning with R
Course 05: Data Analytics with Tableau
Course 06: Basic Google Data Studio
Course 07: Business Intelligence and Data Mining Masterclass
Course 08: Business Analysis Level 3
Course 09: Microsoft Excel: Automated Dashboard Using Advanced Formula, VBA, Power Query
Course 10: Cloud Computing / CompTIA Cloud+ (CV0-002)
Course 11: GDPR Data Protection Level 5
Course 12: ChatGPT Crash Course
Upon finishing this 12-course Data Analyst (Data Analytics) bundle, you will acquire the necessary skills for a thriving career in this rapidly expanding industry. Waste no more time - enrol today and commence your path towards a promising future!
The Curriculum of the Data Analyst Bundle:
Course 1: Introduction to Data Analysis
Introduction
Agenda and Principles of Process Management
The Voice of the Process
Working as One Team for Improvement
Exercise: The Voice of the Customer
Tools for Data Analysis
The Pareto Chart
The Histogram
The Run Chart
Exercise: Presenting Performance Data
Understanding Variation
The Control Chart
Control Chart Example
Control Chart Special Cases
Interpreting the Control Chart
Control Chart Exercise
Strategies to Deal with Variation
Using Data to Drive Improvement
A Structure for Performance Measurement
Exercise
Course Project
Test your Understanding
Course 2: Python for Data Analysis
Welcome, Course Introduction & overview, and
Environment set-up
Python Essentials
Python for Data Analysis using NumPy
Python for Data Analysis using Pandas
Python for Data Visualization using mat plotlib
Python for Data Visualization using Seaborn
Python for Data Visualization using pandas
Python for interactive & geographical plotting using Plotly
and Cufflinks
Capstone Project - Python for Data Analysis &
Visualisation
Python for Machine Learning (ML) - sci-kit-learn - Linear
Regression Model
Python for Machine Learning - scikit-learn - Logistic
Regression Model
Python for Machine Learning - scikit-learn - K Nearest
Neighbours
Python for Machine Learning - scikit-learn - Decision Tree
and Random Forests
Python for Machine Learning - scikit-learn -Support Vector
Machines (SVMs)
Python for Machine Learning - scikit-learn - K Means
Clustering
Python for Machine Learning - scikit-learn - Principal
Component Analysis (PCA)
Recommender Systems with Python - (Additional Topic)
Python for Natural Language Processing (NLP) - NLTK -
(Additional Topic)
Course 3: SQL Programming Masterclass
Introduction
Setting up Course Tools
Browsing & Filtering Data
Filter Data with AND, OR, NOT Operators
Math Operations
String Concatenation
Tidy Up Your Results: Sorting, Alias Names, Limit
Records
NULL, DISTINCT & CASE Statements
Functions in SQL: Multiple-Row Functions
Functions in SQL: Single-Row Functions
Nested Queries
Casting & Data Conversion
Combination Relationships
Joins in SQL
Data Manipulation (DML)
SQL Data Definition Language (DDL)
Course 4: Data Science & Machine Learning with R
Data Science and Machine Learning Course Intro
Data Types and Structures in R
Data Types and Structures in R
Intermediate R
Data Manipulation in R
Data Visualisation in R
Creating Reports with R Markdown
Building WebApps with R Shiny
Introduction to Machine Learning
Starting A Career in Data Science
Course 5: Data Analytics with Tableau
Introduction to the Course
Project 1: Discount Mart (Sales and Profit Analytics)
Project 2: Green Destinations (HR Analytics)
Project 3: Superstore (Sales Agent Tracker)
Northwind Trade (Shipping Analytics)
Project 5: Tesla (Stock Price Analytics)
Bonus: Introduction to Database Concepts
Tableau Stories
Course 6: Basic Google Data Studio
Introduction to GDS
Data Visualisation
Geo-visualisation
A Socio-Economic Case Study
Course 7: Business Intelligence and Data Mining Masterclass
What is Business Intelligence?
Starting Case in understanding BI needs in diff phases
of business
Decision-Making Process and Need for IT Systems
Problem Structure and Decision Support System
Introduction to BI Applications
Dashboard presentation systems
Different Types of Charts used in 131 Dashboards
Good Dashboard and BSC
Examples of Bad Dashboards
Process of KPI Development
Overview of Data Warehouse
More explanation of the data warehouse and steps in
processing
Data Warehouse Architecture -Tiers
Data Warehouse - components
Approach to developing data structure and Models of
database
Basics of Data Mining - Meaning
Basics of Data Mining - Stages of DM
Data Mining Technique - Classification
Data mining - Clustering
Data Mining - Association Rules
Data Mining Applications - Banking
Data Mining Applications - CRM
Data Mining Applications - other industries
Course 8: Business Analysis Level 3
Introduction to Business Analysis
Business Processes
Business Analysis Planning and Monitoring
Strategic Analysis and Product Scope
Solution Evaluation
Investigation Techniques
Ratio Analysis
Stakeholder Analysis & Management
Process Improvement with Gap Analysis
Documenting & Managing Requirements
Career Prospect as a Business Analyst in the UK
Course 9: Microsoft Excel: Automated Dashboard Using Advanced Formula, VBA, Power Query
Introduction
Prepaid Expenses Models: Resources Download
Accounting for Prepaid Expenses
Excel Formulas Detailed: Introduction to three Excel
Models
Formula-Based Prepaid Expenses Model
Calculate Prepaid Expenses Amortisation from Exact
Start Date
Prepaid Expenses Summary with Power Query & Pivot
Table
Advanced VBA Prepaid Expenses Amortisation Model
BONUS: Dynamic Dashboard for Divisional Profit &
Loss statements: Easy Way
Power Query & Pivot Tables based Dashboard without any Formulas, Fully Dynamic
Course 10: Cloud Computing CompTIA Cloud+ (CV0-002)
What You Need to Know
Introducing the Cloud
System Requirements for Cloud Deployments
Cloud Storage
Cloud Compute
Cloud Networking
Cloud Security
Migrating to the Cloud
Maintaining Cloud Solutions
Troubleshooting Cloud Solutions
Course 11: GDPR Data Protection
GDPR Basics
GDPR Explained
Lawful Basis for Preparation
Rights and Breaches
Course 12: ChatGPT Crash Course
Sign up for an OpenAI Account
What can ChatGPT do for you?
ChatGPT for Business
ChatGPT for Teaching
ChatGPT for Research
Limitations of ChatGPT
Additional Videos
 CPD 
130 CPD hours/points  Accredited by CPD Quality Standards
 Who is this course for? 
Anyone from any background can enrol in this Data Analyst (Data Analytics) bundle. Persons with similar professions can also refresh or strengthen their skills by enrolling in this Data Analyst (Data Analytics) bundle course. Students can take this course to gather professional knowledge besides their studies or for the future. 
Aspiring data analysts
Business analyst professionals who want to improve their skills
Anyone who desires to develop their data analysis skills
 
 Career path 
This Data Analyst (Data Analytics) Bundle is ideal for those who want to take their development to the next level and fast-track their career in any of the following roles:
Data Analyst: £30,000 - £50,000
Senior Data Analyst: £50,000 - £70,000
Data Scientist: £70,000 - £100,000
Business Intelligence Manager: £60,000 - £80,000
Machine Learning Engineer: £60,000 - £90,000
 Certificates 
Certificate of Completion
Digital certificate - Included
PDF certificate - Free (Previously, it was £6*12 = £72)
Certificate of Completion
Hard Copy certificate - Included
Hard Copy Certificate - Free (For The Title Course: Previously, it was £10)
Other Hard Copy certificates are available for £10 each
Please Note: The delivery charge inside the UK is £3.99, and the international students must pay a £9.99 shipping cost.

Apex Learning

Google Data Studio

GDPR

Data Mining

Tableau

Business Intelligence (BI)

ChatGPT

12 in 1 Career Guided Programme | Python, Data Science, ML, Tableau, SQL Programming, Data Mining, Business Analysis | 130 CPD Points | Tutor Support | Lifetime Access

Data Analyst (Data Analytics) Diploma - CPD Certified

Master Python 3.10 from the experts with this course and demonstrate programming wizardry in Python. Go from a geek to a wizard in no time with this well-structured video course and write Python code like a pro. Learn about the often-forgotten basics and special features of programming and Python in general.

The Ultimate Guide to Python Programming with Python 3.10

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

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

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

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

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

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

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

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