4115 Software courses in Edinburgh delivered On Demand

Course Overview Ethical hacking, (or penetration testing) involves exploiting computer networks and systems to detect vulnerabilities that could be exposed to dangerous hackers. Many organisations use ethical hackers to test the security of their website or web applications, which is where the role of the Penetration Tester comes in. If you're looking to become a certified Penetration Tester or Ethical Hacker, then this is the course for you. It covers everything you need to know about security testing, including how to use Linux operating systems and SQL programming language.  Learn how to reduce the risk of a cyber attack with this step-by-step training course, designed to equip you with the skills to detect weaknesses in computer systems quickly and easily. It will familiarise you with a range of cyber attacks and techniques for securing systems, from how to create a fake WiFi network and even spy on your clients. Learn ethical hacking from scratch and enrol in this introductory training course today! What You Will Learn In this Ethical Hacking training course, you will learn how to exploit IT systems to detect vulnerabilities that attackers could take advantage of. It will provide you with the fundamental skills to become a qualified Penetration Tester. How to Hack a Windows 10 Computer & Access Their Webcam Installing Kali 2019 As a Virtual Machine A Basic Overview of Kali Linux and Linux Commands An Introduction to Network Penetration Testing Network Hacking - Pre Connection Attacks Website Hacking and Information Gathering Tips & Tricks An Introduction to SQL and SQLmap What is XSS or Cross-Site Scripting? How to Scan a Target Website For Vulnerabilities Extracting Sensitive Data Such As Passwords Why You Should Choose This Course From iStudy Study at your own pace Full Tutor support on weekdays (Monday - Friday) Fully compatible with any device Free Printable PDF Certificate immediately after completion No prior qualifications are needed to take this course No hidden fees or exam charges CPD Qualification Standards and IAO accredited Efficient exam system, assessment, and instant results Our customer support team is always ready to help you Gain professional skills and better earning potential Certification After completing the course you'll receive a free printable CPD accredited PDF certificate. Hard Copy certificate is also available, and you can get one for just £9! Accreditation This course is accredited by Continuing Professional Development (CPD). It is a recognised independent accreditation service. Enrol today and learn something new with iStudy. You'll find a full breakdown of the course curriculum down below, take a look and see just how much this course offers. We're sure you'll be satisfied with this course.

Make iBeacon Mobile Apps - Without Coding course teaches you to develop an app using iBeacon - Apple's implementation of Bluetooth low-energy (BLE) wireless technology. Throughout the course, you will learn how to make iBeacon apps without the knowledge of coding. The concepts of iBeacon, its definition and different types, its uses, costing, services provided by the various Beacon makers, essential programs to build iBeacon apps, and where to download these programs, etc. will be focused in the course. The course also provides discussion on the advanced editing strategies and distribution of your app. Upon completion, you will be able to make and ready an app for submitting it to the app stores (Google and Apple). You will also learn how to test the app or give your customers to test the app. What Will I Learn? By the end of the course you will be able to build an iBeacon enabled mobile app ready to be submitted to the app stores (Apple and Google Play) You will understand what an iBeacon is and what are some of the potential uses. You will understand what programs are needed to build beacon apps and where to download them (for free). You will understand the different types of beacons, what are the costs involved, what services are provided by the various beacon makers. You will know how to build an app for testing and giving to your clients for testing. Requirements You need to have a MAC computer to build the apps - currently PC is not supported. It is also possible to do this on a Windows machine if you install a Virtual machine and run the MAC OS in a window on your PC. Take a look at this for an overview: https://blog.udemy.com/xcode-on-windows/ For testing iBeacon functionality you will need 2 things. 1) a device to act as a beacon, and 2) an i Device or an Andoid Device (details in the course). A desire to learn! This is not difficult, it only takes following instructions and havign a desire to learn. Who is the target audience? Web and Mobile designers, marketing people, and business ownvers who want to learn how to leverage the next level of mobile interactions by incorporating iBeacons. No programming background needed - this is really a course for anyone - you really do not need to have any coding background. Marketing and retial people are also encouraged to take this course to understand the potential for greater customer interactions made possible with iBeacons. Mobile phone app makers who want to learn how to incorporate iBeacons into existing apps the easy and fast way. Introduction to iBeacons How iBeacons Work FREE 00:04:00 A simple Demo 00:01:00 Creating a Virtual Beacon With Estimote 00:02:00 Building Your Own App Setting up the Design Environment 00:12:00 Using the designer to add iBeacons 00:12:00 Testing your App 00:04:00 Using the Viewer to Test Your App 00:01:00 Using iBeacons to Open External Web Pages and Videos 00:02:00 Advanced Editing Creating a wish list shopping cart 00:13:00 Triggering Facebook and Twitter Sharing with an iBeacon 00:07:00 Adding a Bar Code and QR Code Reader 00:03:00 Adding Mapping Functonality with Google Maps 00:07:00 Customizing the App - Beacon Messages, Icons and Splash pages 00:14:00 Custom iBeacon Triggered Sounds 00:05:00 Eddystone - The New Beacon Protocal by Google Eddystone Introduction 00:03:00 Course Certification

What Will I Learn? Be up and running managing and editing your own WordPress hosted website Create and edit posts and pages, format text, add images, add categories and tags, and publish or schedule your website's content. Manage subscribers, contributors, authors, editors, and administrators for your website. Develop a solid beginner's foundation in WordPress that you can use as a springboard towards more advanced web training or paid opportunities helping others get started editing and managing websites. Understand key settings, tools, and features of WordPress to enable you to control the look, feel, and function of your website. Easily create and manage menus and external links. Harness the power of the most useful plugins and widgets to extend your website's capabilties. Requirements Students should already have their WordPress login information and a WordPress hosted website set up before taking this course. (* I still provide information and external resources in a text lecture if you need to still get set up.) Description If you're new to WordPress, start at the beginning and work through this WordPress for Beginners. This extensive course helps you get started easily with editing and managing your own WordPress website in 60 minutes or less. These step-by-step arranged and easy-to-follow modules will be ideal for complete beginners. Even if you already know a thing or two about WordPress, you can quickly jump to any topic you need help with this course. This course shows you the most essential and important features of the WordPress dashboard and interface including making posts, pages, and managing all aspects of your WordPress hosted website. Also, learn to plan and organize websites, create online graphics and animations, HTML and CSS, adding Javascript, and making beautiful websites from scratch. What Students Are Saying: 'If you haven't started using WordPress for your site but would like to write content for it by yourself you should take this course. Excellent, no fluff explanations and perfectly presented.' -Matt S. Rinc -- I'm a tenured Associate Professor of Digital Media and the Program Director of Film & Digital Media at The American University of Rome and a practicing award-winning multimedia artist. I have over 16 years of experience teaching students all over the world using my tried and true custom approach (turning complex information into something simple, memorable, easy-to-understand in as short amount of time as possible) to ensure that you get the most important, relevant, and useful information that can be applied immediately to your art, work, and everyday life. New bonus lectures and resources will continue to be added and timely design advice will be provided in the discussion forum. I love to help and always respond to inquiries and discussions ASAP. Please Note: All students who enroll in this course also will receive periodic free and discounted access to my other top-rated current and upcoming courses. You have a 30-day, 100% money-back guarantee with no questions asked so you have nothing to lose. I make myself available so you will have access to me if you have questions or need specific feedback along the way.Empower yourself now by enrolling in this easy to follow WordPress course and join our growing learning community! Click the 'Take This Course' button in the upper right corner and let's get started building your web design and content management skills today. Who is the target audience? This course is ideal for complete beginners. This course is ideal for people who have a website that someone else made for them who would like to know how to begin to edit and manage it themselves. This course is ideal for those who have been tasked with editing their organization's WordPress hosted website and don't know where to start. Please note this is NOT an in-depth WordPress course. Students looking for intermediate to advanced WordPress training would be better off taking a longer, comprehensive course. (*Do please have a look at my other course offerings to see if I have a different course that is a better fit.) Introduction to the Course and WordPress Starter Essentials Introduction to WordPress in 1 Hour: Quick and Easy Essentials for Beginners FREE 00:02:00 WordPress.com vs. WordPress.org? How to Get Set Up and What You Need FREE 00:02:00 Have a WordPress Account and All Set Up? Let's Start the Tour Have Your WordPress Login Information? Let's Get Started! FREE 00:02:00 Tour the WordPress Dashboard FREE 00:02:00 How to Make (or Edit) a Post in WordPress 00:08:00 How to Make a Page in WordPress ( & The Difference Between a Page and a Post) 00:02:00 The Rundown on WordPress Plugins 00:07:00 All About WordPress Themes 00:05:00 Fun With WordPress Widgets 00:04:00 Setting Up or Editing Menus in WordPress 00:03:00 How to Use Your Tools in WordPress 00:01:00 How to Be the Boss of Your WordPress Settings 00:04:00 Adding or Editing Links in WordPress 00:03:00 Managing Users and Permissions in WordPress 00:04:00 Conclusion Conclusion 00:03:00 New Case Study: How to Use Color Psychology to Boost Your Website 00:12:00

Overview This Using Webpack course will unlock your full potential and will show you how to excel in a career in Using Webpack. So upskill now and reach your full potential. Everything you need to get started in Using Webpack is available in this course. Learning and progressing are the hallmarks of personal development. This Using Webpack will quickly teach you the must-have skills needed to start in the relevant industry. In This Using Webpack Course, You Will: Learn strategies to boost your workplace efficiency. Hone your Using Webpack skills to help you advance your career. Acquire a comprehensive understanding of variousUsing Webpack topics and tips from industry experts. Learn in-demand Using Webpack skills that are in high demand among UK employers, which will help you to kickstart your career. This Using Webpack course covers everything you must know to stand against the tough competition in the Using Webpack field.  The future is truly yours to seize with this Using Webpack. Enrol today and complete the course to achieve a Using Webpack certificate that can change your professional career forever. Additional Perks of Buying a Course From Institute of Mental Health Study online - whenever and wherever you want. One-to-one support from a dedicated tutor throughout your course. Certificate immediately upon course completion 100% Money back guarantee Exclusive discounts on your next course purchase from Institute of Mental Health Enrolling in the Using Webpack course can assist you in getting into your desired career quicker than you ever imagined. So without further ado, start now. Process of Evaluation After studying the Using Webpack course, your skills and knowledge will be tested with a MCQ exam or assignment. You must get a score of 60% to pass the test and get your certificate.  Certificate of Achievement Upon successfully completing the Using Webpack course, you will get your CPD accredited digital certificate immediately. And you can also claim the hardcopy certificate completely free of charge. All you have to do is pay a shipping charge of just £3.99. Who Is This Course for? This Using Webpack is suitable for anyone aspiring to start a career in Using Webpack; even if you are new to this and have no prior knowledge on Using Webpack, this course is going to be very easy for you to understand.  And if you are already working in the Using Webpack field, this course will be a great source of knowledge for you to improve your existing skills and take them to the next level.  Taking this Using Webpack course is a win-win for you in all aspects.  This course has been developed with maximum flexibility and accessibility, making it ideal for people who don't have the time to devote to traditional education. Requirements This Using Webpack course has no prerequisite.  You don't need any educational qualification or experience to enrol in the Using Webpack course. Do note: you must be at least 16 years old to enrol. Any internet-connected device, such as a computer, tablet, or smartphone, can access this online Using Webpack course. Moreover, this course allows you to learn at your own pace while developing transferable and marketable skills. Course Curriculum Section 01: Introduction to Webpack What You Ought To Expect From This Course 00:01:00 Why Webpack? 00:01:00 Course Roadmap 00:01:00 How Does Webpack Work? 00:03:00 How Does Webpack Work? 00:03:00 Webpack Versions 00:06:00 Summary 00:01:00 Section 02: Installing and Configuring Webpack Installing Webpack 00:01:00 Demo: Installing Webpack 00:05:00 Configuring Webpack 00:05:00 Demo: Configuring Webpack 00:06:00 Webpack Dev Server 00:01:00 Demo: Using Webpack Dev Server 00:05:00 Transforming JSX with Webpack 00:05:00 Demo: Transforming JSX with Webpack 00:10:00 Bundling Styles 00:03:00 Demo: Bundling Styles with CSS and Webpack 00:04:00 Loading Additional Filetypes with Webpack 00:01:00 Demo: Loading YAML Files with Webpack 00:05:00 Section 03: Building an Application with Webpack Creating an Interactive Application 00:01:00 Demo: Putting It All Together: Creating an Interactive Application 00:21:00 Summary + Continue Developing the App + Q&A 00:06:00

Description: Have you ever wanted to start a new career by becoming a web developer? If yes, then join this course and learn how to design your website using Joomla from scratch. A decade ago, having a web page was super cool. Today, not having a page is practically primitive. Through a blog or a wiki or a page, everybody nowadays is available on the web, one way or the other. Does that mean everybody who needs to be on the web must be a nerd? No. All you need is a Content Management System. Well, not any CMS would do. What you need is Joomla! It's a progressive open-source framework that is similarly as cool to work with as it sounds. If that you have a page that needs some chipping away constantly, Joomla! is your friend. Download it and disregard coding, programming, planning. Kick back and let Joomla! do all the hard work. In this course, we have attempted to pack in as much information as we could about Joomla! what's more, the wonders it can work for you. Read on and explore more. Who is the course for? Beginners. Students. Web Developers. Web Designers. Graphic Designers. Anyone interested in learning about joomla. Individuals who don't have money to create a website. Individuals who want to start their own development company and earn money. Entry Requirement: This course is available to all learners, of all academic backgrounds. Learners should be aged 16 or over to undertake the qualification. Good understanding of English language, numeracy and ICT are required to attend this course. Assessment:  At the end of the course, you will be required to sit an online multiple-choice test. Your test will be assessed automatically and immediately so that you will instantly know whether you have been successful. Before sitting for your final exam you will have the opportunity to test your proficiency with a mock exam. Certification: After you have successfully passed the test, you will be able to obtain an Accredited Certificate of Achievement. You can however also obtain a Course Completion Certificate following the course completion without sitting for the test. Certificates can be obtained either in hard copy at a cost of £39 or in PDF format at a cost of £24. PDF certificate's turnaround time is 24 hours and for the hardcopy certificate, it is 3-9 working days. Why choose us? Affordable, engaging & high-quality e-learning study materials; Tutorial videos/materials from the industry leading experts; Study in a user-friendly, advanced online learning platform; Efficient exam systems for the assessment and instant result; The UK & internationally recognised accredited qualification; Access to course content on mobile, tablet or desktop from anywhere anytime; The benefit of career advancement opportunities; 24/7 student support via email. Career Path: Advanced Joomla Course is a useful qualification to possess, and would be beneficial for the following careers: Web designer. Graphic designer. Web developer. Web marketers. Freelancers. Chapter-01 INTRODUCTION TO JOOMLA 00:30:00 Chapter-02 SCOPE OF JOOMLA 00:30:00 Chapter-03 BENEFITS OF JOOMLA 00:30:00 Chapter-04 COMPARISON WITH OTHER CONTENT MANAGEMENT SYSTEMS 01:00:00 Chapter-05 WHY DEVELOPERS DRAWS TO JOOMLA? 00:30:00 Chapter-06 How do I in install Joomla? 03:00:00 Mock Exam Mock Exam- Joomla for Beginners 00:20:00 Final Exam Final Exam- Joomla for Beginners 00:20:00 Certificate and Transcript Order Your Certificates and Transcripts 00:00:00

Description Learn the methods, techniques, and vivid functions of hacking tools practically and theoretically doing the Network Hacking Diploma Level 3 course. Its precise contents guide you on your quest to become efficient in this field. If you are a network and system engineer, security officer, or IT passionate, this course is very effective for you. The course is designed in such a way that will assist you to become an ethical hacker knowing the facts about how to scan a network to identify its strength and weakness and perform in system hacking. The lab-based practical approaches of this course will assist you to know some vivid activities of Virus and Worms, Trojans, and Backdoors along with how to penetrate on the wireless network. At the end of the course, knowing the penetration system, you can mastery of hacking techniques and methods efficiently. Assessment: This course does not involve any MCQ test. Students need to answer assignment questions to complete the course, the answers will be in the form of written work in pdf or word. Students can write the answers in their own time. Once the answers are submitted, the instructor will check and assess the work. Certification: After completing and passing the course successfully, you will be able to obtain an Accredited Certificate of Achievement. Certificates can be obtained either in hard copy at a cost of £39 or in PDF format at a cost of £24. Who is this Course for? Network Hacking Diploma Level 3 is certified by CPD Qualifications Standards and CiQ. This makes it perfect for anyone trying to learn potential professional skills. As there is no experience and qualification required for this course, it is available for all students from any academic background. Requirements Our Network Hacking Diploma Level 3 is fully compatible with any kind of device. Whether you are using Windows computer, Mac, smartphones or tablets, you will get the same experience while learning. Besides that, you will be able to access the course with any kind of internet connection from anywhere at any time without any kind of limitation. Career Path After completing this course you will be able to build up accurate knowledge and skills with proper confidence to enrich yourself and brighten up your career in the relevant job market. Introduction Introduction 00:01:00 Introduction to Ethical Hacking. Footprinting and Reconnaissance Introduction to Ethical Hacking. Footprinting and Reconnaissance 00:25:00 Demo - Information Gathering using Google Dorks and DNS Queris 00:04:00 Demo - Scanning and Enumeration 00:08:00 Scanning Networks, Enumeration and Discovering Vulnearbilities Scanning and enumeration 00:09:00 Vulnerabilties Identification 00:08:00 Demo - Installing Nessus Scanner 00:04:00 Demo - Use Nessus to Discover Vulnerabilities 00:05:00 Demo - Using Nikto to discover Web Vulnerabilities 00:05:00 Demo - Using Paros for Vulnerability Discovery 00:05:00 Demo - Use Dirbuster to brute force sub-directories and filenames 00:03:00 System Hacking and Vulnerability Exploitation System hacking - vulnerability exploitation 00:06:00 Passwords 00:12:00 Authentication 00:07:00 Basics of Sniffing Sniffing 00:15:00 Metasploit Metasploit 00:17:00 Demo - Exploiting FTP Server Vulnerability using Metasploit 00:12:00 Demo - Post Exploitation Example 00:01:00 Demo - Exploiting NFS Vulnerability and exporting SSH Keys to the 00:10:00 Demo - Eploiting Samba Service on Linux using Metasploit 00:03:00 Demo - Windows backdoor using Metasploit 00:14:00 Trojans, Backdoors, Viruses and Worms Trojans and Backdoors 00:05:00 Computer viruses and worms 00:09:00 Cryptography Cryptography concepts 00:05:00 Cryptographic Algorithms 00:11:00 Cryptography and cryptanalysis tools. Cryptography attacks 00:03:00 Demo - Hack SSH passwords using Medusa 00:05:00 Hack the SSH Password using Hydra 00:05:00 Hack Linux Passwords using John the Ripper 00:03:00 Penetration Testing on Wireless Networks Penetration Testing on Wireless Networks 00:07:00 Case Study - Windows Hosted Network Bug or Feature 00:11:00 Penetration Testing Overview. Final words Penetration Testing Overview. Final Words 00:06:00 Bonus - OWASP Top 10 Vulnerabilities 00:18:00 (Bonus) Attacking the users trough websites - XSS and Beef-XSS Introduction to Cross-Site Scripting and Beef-XSS 00:08:00 XSS example - reflected 00:10:00 XSS example - stored 00:07:00 Beef-XSS Demo 00:16:00 Certificate and Transcript Order Your Certificates and Transcripts 00:00:00

Are you ready to be at the helm, steering the ship into a realm where data is the new gold? In the infinite world of data, where information spirals at breakneck speed, lies a universe rich in potential and discovery: the domain of Data Science and Visualisation. This 'Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3' course unravels the wonders of extracting meaningful insights using Python, the worldwide leading language of data experts. Harnessing the strength of Python, you'll delve deep into data analysis, experience the finesse of visualisation tools, and master the art of Machine Learning. The need to understand, interpret, and act on this data has become paramount, with vast amounts of data increasing the digital sphere. Envision a canvas where raw numbers are transformed into visually compelling stories, and machine learning models foretell future trends. This course provides a meticulous pathway for anyone eager to learn the data representation paradigms backed by Python's robust libraries. Dive into a curriculum rich with analytical explorations, visual artistry, and machine learning predictions. Learning Outcomes Understanding the foundations and functionalities of Python, focusing on its application in data science. Applying various Python libraries like NumPy and Pandas for effective data analysis. Demonstrating proficiency in creating detailed visual narratives using tools like matplotlib, Seaborn, and Plotly. Implementing Machine Learning algorithms in Python using scikit-learn, ranging from regression models to clustering techniques. Designing and executing a holistic data analysis and visualisation project, encapsulating all learned techniques. Exploring advanced topics, encompassing recommender systems and natural language processing with Python. Attaining the confidence to independently analyse complex data sets and translate them into actionable insights.   Video Playerhttps://studyhub.org.uk/wp-content/uploads/2021/03/Data-Science-and-Visualisation-with-Machine-Learning.mp400:0000:0000:00Use Up/Down Arrow keys to increase or decrease volume. Why buy this Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments are designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Who is this Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 course for? Aspiring data scientists aiming to harness the power of Python. Researchers keen to enrich their analytical and visualisation skills. Analysts aiming to add machine learning to their toolkit. Developers striving to integrate data analytics into applications. Business professionals desiring data-driven decision-making capabilities. Career path Data Scientist: £55,000 - £85,000 Per Annum Machine Learning Engineer: £60,000 - £90,000 Per Annum Data Analyst: £30,000 - £50,000 Per Annum Data Visualisation Specialist: £45,000 - £70,000 Per Annum Natural Language Processing Specialist: £65,000 - £95,000 Per Annum Business Intelligence Developer: £40,000 - £65,000 Per Annum Prerequisites This Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 does not require you to have any prior qualifications or experience. You can just enrol and start learning. This Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Certification After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. Endorsed Certificate of Achievement from the Quality Licence Scheme Learners will be able to achieve an endorsed certificate after completing the course as proof of their achievement. You can order the endorsed certificate for only £85 to be delivered to your home by post. For international students, there is an additional postage charge of £10. Endorsement The Quality Licence Scheme (QLS) has endorsed this course for its high-quality, non-regulated provision and training programmes. The QLS is a UK-based organisation that sets standards for non-regulated training and learning. This endorsement means that the course has been reviewed and approved by the QLS and meets the highest quality standards. Please Note: Studyhub is a Compliance Central approved resale partner for Quality Licence Scheme Endorsed courses. Course Curriculum Welcome, Course Introduction & overview, and Environment set-up Welcome & Course Overview 00:07:00 Set-up the Environment for the Course (lecture 1) 00:09:00 Set-up the Environment for the Course (lecture 2) 00:25:00 Two other options to setup environment 00:04:00 Python Essentials Python data types Part 1 00:21:00 Python Data Types Part 2 00:15:00 Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 1) 00:16:00 Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 2) 00:20:00 Python Essentials Exercises Overview 00:02:00 Python Essentials Exercises Solutions 00:22:00 Python for Data Analysis using NumPy What is Numpy? A brief introduction and installation instructions. 00:03:00 NumPy Essentials - NumPy arrays, built-in methods, array methods and attributes. 00:28:00 NumPy Essentials - Indexing, slicing, broadcasting & boolean masking 00:26:00 NumPy Essentials - Arithmetic Operations & Universal Functions 00:07:00 NumPy Essentials Exercises Overview 00:02:00 NumPy Essentials Exercises Solutions 00:25:00 Python for Data Analysis using Pandas What is pandas? A brief introduction and installation instructions. 00:02:00 Pandas Introduction 00:02:00 Pandas Essentials - Pandas Data Structures - Series 00:20:00 Pandas Essentials - Pandas Data Structures - DataFrame 00:30:00 Pandas Essentials - Handling Missing Data 00:12:00 Pandas Essentials - Data Wrangling - Combining, merging, joining 00:20:00 Pandas Essentials - Groupby 00:10:00 Pandas Essentials - Useful Methods and Operations 00:26:00 Pandas Essentials - Project 1 (Overview) Customer Purchases Data 00:08:00 Pandas Essentials - Project 1 (Solutions) Customer Purchases Data 00:31:00 Pandas Essentials - Project 2 (Overview) Chicago Payroll Data 00:04:00 Pandas Essentials - Project 2 (Solutions Part 1) Chicago Payroll Data 00:18:00 Python for Data Visualization using matplotlib Matplotlib Essentials (Part 1) - Basic Plotting & Object Oriented Approach 00:13:00 Matplotlib Essentials (Part 2) - Basic Plotting & Object Oriented Approach 00:22:00 Matplotlib Essentials (Part 3) - Basic Plotting & Object Oriented Approach 00:22:00 Matplotlib Essentials - Exercises Overview 00:06:00 Matplotlib Essentials - Exercises Solutions 00:21:00 Python for Data Visualization using Seaborn Seaborn - Introduction & Installation 00:04:00 Seaborn - Distribution Plots 00:25:00 Seaborn - Categorical Plots (Part 1) 00:21:00 Seaborn - Categorical Plots (Part 2) 00:16:00 Seborn-Axis Grids 00:25:00 Seaborn - Matrix Plots 00:13:00 Seaborn - Regression Plots 00:11:00 Seaborn - Controlling Figure Aesthetics 00:10:00 Seaborn - Exercises Overview 00:04:00 Seaborn - Exercise Solutions 00:19:00 Python for Data Visualization using pandas Pandas Built-in Data Visualization 00:34:00 Pandas Data Visualization Exercises Overview 00:03:00 Panda Data Visualization Exercises Solutions 00:13:00 Python for interactive & geographical plotting using Plotly and Cufflinks Plotly & Cufflinks - Interactive & Geographical Plotting (Part 1) 00:19:00 Plotly & Cufflinks - Interactive & Geographical Plotting (Part 2) 00:14:00 Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Overview) 00:11:00 Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Solutions) 00:37:00 Capstone Project - Python for Data Analysis & Visualization Project 1 - Oil vs Banks Stock Price during recession (Overview) 00:15:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 1) 00:18:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 2) 00:18:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 3) 00:17:00 Project 2 (Optional) - Emergency Calls from Montgomery County, PA (Overview) 00:03:00 Python for Machine Learning (ML) - scikit-learn - Linear Regression Model Introduction to ML - What, Why and Types.. 00:15:00 Theory Lecture on Linear Regression Model, No Free Lunch, Bias Variance Tradeoff 00:15:00 scikit-learn - Linear Regression Model - Hands-on (Part 1) 00:17:00 scikit-learn - Linear Regression Model Hands-on (Part 2) 00:19:00 Good to know! How to save and load your trained Machine Learning Model! 00:01:00 scikit-learn - Linear Regression Model (Insurance Data Project Overview) 00:08:00 scikit-learn - Linear Regression Model (Insurance Data Project Solutions) 00:30:00 Python for Machine Learning - scikit-learn - Logistic Regression Model Theory: Logistic Regression, conf. mat., TP, TN, Accuracy, Specificityetc. 00:10:00 scikit-learn - Logistic Regression Model - Hands-on (Part 1) 00:17:00 scikit-learn - Logistic Regression Model - Hands-on (Part 2) 00:20:00 scikit-learn - Logistic Regression Model - Hands-on (Part 3) 00:11:00 scikit-learn - Logistic Regression Model - Hands-on (Project Overview) 00:05:00 scikit-learn - Logistic Regression Model - Hands-on (Project Solutions) 00:15:00 Python for Machine Learning - scikit-learn - K Nearest Neighbors Theory: K Nearest Neighbors, Curse of dimensionality . 00:08:00 scikit-learn - K Nearest Neighbors - Hands-on 00:25:00 scikt-learn - K Nearest Neighbors (Project Overview) 00:04:00 scikit-learn - K Nearest Neighbors (Project Solutions) 00:14:00 Python for Machine Learning - scikit-learn - Decision Tree and Random Forests Theory: D-Tree & Random Forests, splitting, Entropy, IG, Bootstrap, Bagging. 00:18:00 scikit-learn - Decision Tree and Random Forests - Hands-on (Part 1) 00:19:00 scikit-learn - Decision Tree and Random Forests (Project Overview) 00:05:00 scikit-learn - Decision Tree and Random Forests (Project Solutions) 00:15:00 Python for Machine Learning - scikit-learn -Support Vector Machines (SVMs) Support Vector Machines (SVMs) - (Theory Lecture) 00:07:00 scikit-learn - Support Vector Machines - Hands-on (SVMs) 00:30:00 scikit-learn - Support Vector Machines (Project 1 Overview) 00:07:00 scikit-learn - Support Vector Machines (Project 1 Solutions) 00:20:00 scikit-learn - Support Vector Machines (Optional Project 2 - Overview) 00:02:00 Python for Machine Learning - scikit-learn - K Means Clustering Theory: K Means Clustering, Elbow method .. 00:11:00 scikit-learn - K Means Clustering - Hands-on 00:23:00 scikit-learn - K Means Clustering (Project Overview) 00:07:00 scikit-learn - K Means Clustering (Project Solutions) 00:22:00 Python for Machine Learning - scikit-learn - Principal Component Analysis (PCA) Theory: Principal Component Analysis (PCA) 00:09:00 scikit-learn - Principal Component Analysis (PCA) - Hands-on 00:22:00 scikit-learn - Principal Component Analysis (PCA) - (Project Overview) 00:02:00 scikit-learn - Principal Component Analysis (PCA) - (Project Solutions) 00:17:00 Recommender Systems with Python - (Additional Topic) Theory: Recommender Systems their Types and Importance 00:06:00 Python for Recommender Systems - Hands-on (Part 1) 00:18:00 Python for Recommender Systems - - Hands-on (Part 2) 00:19:00 Python for Natural Language Processing (NLP) - NLTK - (Additional Topic) Natural Language Processing (NLP) - (Theory Lecture) 00:13:00 NLTK - NLP-Challenges, Data Sources, Data Processing .. 00:13:00 NLTK - Feature Engineering and Text Preprocessing in Natural Language Processing 00:19:00 NLTK - NLP - Tokenization, Text Normalization, Vectorization, BoW. 00:19:00 NLTK - BoW, TF-IDF, Machine Learning, Training & Evaluation, Naive Bayes 00:13:00 NLTK - NLP - Pipeline feature to assemble several steps for cross-validation 00:09:00 Resources Resources - Data Science and Visualisation with Machine Learning 00:00:00 Order your QLS Endorsed Certificate Order your QLS Endorsed Certificate 00:00:00

Quick Data Science Approach from Scratch is an innovatively structured course designed to introduce learners to the fascinating world of data science. The course commences with an enlightening introduction, setting the stage for a deep dive into the essence and significance of data science in the modern era. Learners are guided through a landscape of insights, where misconceptions about data science are addressed and clarified, paving the way for a clear and accurate understanding of the field. In the second section, the course shifts its focus to pivotal data science concepts. Beginning with an exploration of data types and variables, learners gain a solid foundation in handling various data formats. The journey then leads to mastering descriptive analysis, a critical skill for interpreting and understanding data trends. Learners will also navigate through the intricate processes of data cleaning and feature engineering, essential skills for refining and optimizing data for analysis. The concept of 'Data Thinking Development' is introduced, fostering a mindset that is crucial for effective data science practice. The final section offers an immersive experience in applying these skills to a real-world scenario. Here, learners engage in defining a problem, choosing suitable algorithms, and developing predictive models. This practical application is designed to cement the theoretical knowledge acquired and enhance problem-solving skills in data science. Learning Outcomes Build a foundational understanding of data science and its practical relevance. Develop proficiency in managing various data types and conducting descriptive analysis. Learn and implement effective data cleaning and feature engineering techniques. Cultivate a 'data thinking' approach for insightful data analysis. Apply data science methodologies to real-life problems using algorithmic and predictive techniques. Why choose this Quick Data Science Approach from Scratch course? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards and CIQ after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Unlock career resources for CV improvement, interview readiness, and job success. Who is this Quick Data Science Approach from Scratch course for? Novices aiming to enter the data science field. Sector professionals integrating data science into their expertise. Academicians and learners incorporating data science in academic pursuits. Business strategists utilizing data science for enhanced decision-making. Statisticians and analysts broadening their expertise into the data science domain. Career path Entry-Level Data Scientist: £25,000 - £40,000 Beginner Data Analyst: £22,000 - £35,000 Emerging Business Intelligence Specialist: £28,000 - £45,000 Data-Focused Research Scientist: £30,000 - £50,000 Novice Machine Learning Practitioner: £32,000 - £55,000 Data System Developer (Starter): £26,000 - £42,000 Prerequisites This Quick Data Science Approach from Scratch does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Quick Data Science Approach from Scratch was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Certification After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. Course Curriculum Section 01: Course Overview & Introduction to Data Science Introduction 00:02:00 Data Science Explanation 00:05:00 Need of Data Science 00:02:00 8 Common mistakes by Aspiring Data Scientists/Data Science Enthusiasts 00:08:00 Myths about Data Science 00:03:00 Section 02: Data Science Concepts Data Types and Variables 00:04:00 Descriptive Analysis 00:02:00 Data Cleaning 00:02:00 Feature Engineering 00:02:00 Data Thinking Development 00:03:00 Section 03: A Real Life Problem Problem Definition 00:05:00 Algorithms 00:14:00 Prediction 00:03:00 Learning Methods 00:05:00 Assignment Assignment - Quick Data Science Approach from Scratch 00:00:00

Overview In the era where information is abundant and decisions are driven by data, have you ever pondered, 'what is machine learning?' or 'what is data science?' Dive into the realm of 'Data Science & Machine Learning with R from A-Z,' a comprehensive guide to unravel these complexities. This course effortlessly blends the foundational aspects of data science with the intricate depths of machine learning algorithms, all through the versatile medium of R. As the digital economy booms, the demand for machine learning jobs continues to surge. Equip yourself with the proficiency to navigate this dynamic field and transition from being an inquisitive mind to a sought-after professional in the space of data science and machine learning with R. Learning Outcomes: Understand the foundational concepts of data science and machine learning. Familiarise oneself with the R environment and its functionalities. Master data types, structures, and advanced techniques in R. Acquire proficiency in data manipulation and visual representation using R. Generate comprehensive reports using R Markdown and design web applications with R Shiny. Gain a thorough understanding of machine learning methodologies and their applications. Gain insights into initiating a successful career in the data science sector. Why buy this Data Science & Machine Learning with R from A-Z course? Unlimited access to the course for forever Digital Certificate, Transcript, student ID all included in the price Absolutely no hidden fees Directly receive CPD accredited qualifications after course completion Receive one to one assistance on every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the Data Science & Machine Learning with R from A-Z there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Who is this Data Science & Machine Learning with R from A-Z course for? This course is ideal for Individuals keen on exploring the intricacies of machine learning and data science. Aspiring data analysts and scientists looking to specialise in Machine Learning with R. IT professionals aiming to diversify their skill set in the emerging data-driven market. Researchers seeking to harness the power of R for data representation and analysis. Academics and students aiming to bolster their understanding of modern data practices with R. Prerequisites This Data Science & Machine Learning with R from A-Z does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Data Science & Machine Learning with R from A-Z was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Career path Data Scientist - Average salary range: £35,000 - £70,000 Per Annum Machine Learning Engineer - Average salary range: £50,000 - £80,000 Per Annum Data Analyst - Average salary range: £28,000 - £55,000 Per Annum R Developer - Average salary range: £30,000 - £60,000 Per Annum R Shiny Web Developer - Average salary range: £32,000 - £65,000 Per Annum Machine Learning Researcher - Average salary range: £40,000 - £75,000 Per Annum Course Curriculum Data Science and Machine Learning Course Intro Data Science and Machine Learning Introduction 00:03:00 What is Data Science 00:10:00 Machine Learning Overview 00:05:00 Who is This Course for 00:03:00 Data Science and Machine Learning Marketplace 00:05:00 Data Science and Machine Learning Job Opportunities 00:03:00 Getting Started with R Getting Started 00:11:00 Basics 00:06:00 Files 00:11:00 RStudio 00:07:00 Tidyverse 00:05:00 Resources 00:04:00 Data Types and Structures in R Unit Introduction 00:30:00 Basic Type 00:09:00 Vector Part One 00:20:00 Vectors Part Two 00:25:00 Vectors - Missing Values 00:16:00 Vectors - Coercion 00:14:00 Vectors - Naming 00:10:00 Vectors - Misc 00:06:00 Creating Matrics 00:31:00 List 00:32:00 Introduction to Data Frames 00:19:00 Creating Data Frames 00:20:00 Data Frames: Helper Functions 00:31:00 Data Frames Tibbles 00:39:00 Intermediate R Intermediate Introduction 00:47:00 Relational Operations 00:11:00 Conditional Statements 00:11:00 Loops 00:08:00 Functions 00:14:00 Packages 00:11:00 Factors 00:28:00 Dates and Times 00:30:00 Functional Programming 00:37:00 Data Import or Export 00:22:00 Database 00:27:00 Data Manipulation in R Data Manipulation in R Introduction 00:36:00 Tidy Data 00:11:00 The Pipe Operator 00:15:00 The Filter Verb 00:22:00 The Select Verb 00:46:00 The Mutate Verb 00:32:00 The Arrange Verb 00:10:00 The Summarize Verb 00:23:00 Data Pivoting 00:43:00 JSON Parsing 00:11:00 String Manipulation 00:33:00 Web Scraping 00:59:00 Data Visualization in R Data Visualization in R Section Intro 00:17:00 Getting Started 00:16:00 Aesthetics Mappings 00:25:00 Single Variable Plots 00:37:00 Two Variable Plots 00:21:00 Facets, Layering, and Coordinate Systems 00:18:00 Styling and Saving 00:12:00 Creating Reports with R Markdown Creating with R Markdown 00:29:00 Building Webapps with R Shiny Introduction to R Shiny 00:26:00 A Basic R Shiny App 00:31:00 Other Examples with R Shiny 00:34:00 Introduction to Machine Learning Machine Learning Part 1 00:22:00 Machine Learning Part 2 00:47:00 Starting A Career in Data Science Starting a Data Science Career Section Overview 00:03:00 Data Science Resume 00:04:00 Getting Started with Freelancing 00:05:00 Top Freelance Websites 00:05:00 Personal Branding 00:05:00 Importance of Website and Blo 00:04:00 Networking Do's and Don'ts 00:04:00 Assignment Assignment - Data Science & Machine Learning with R 00:00:00

Delve into the world of data analysis with 'R Programming for Data Science,' a course designed to guide learners through the intricacies of R, a premier programming language in the data science domain. The course opens with a broad perspective on data science, illuminating the pivotal role of R in this field. Learners are then introduced to R and RStudio, equipping them with the foundational tools and interfaces essential for R programming. The curriculum progresses with an introduction to the basics of R, ensuring learners grasp the core principles that underpin more complex operations. A highlight of this course is its in-depth exploration of R's versatile data structures, including vectors, matrices, factors, and data frames. Each unit is crafted to provide learners with a comprehensive understanding of these structures, pivotal for effective data handling and manipulation. The course also emphasizes the importance of relational and logical operators in R, key elements for executing data operations. As the course advances, learners will engage with the nuances of conditional statements and loops, essential for writing efficient and dynamic R scripts. Moving into more advanced territories, the course delves into the creation and usage of functions, an integral part of R programming, and the exploration of various R packages that extend the language's capabilities. Learners will also gain expertise in the 'apply' family of functions, crucial for streamlined data processing. Further units cover regular expressions and effective strategies for managing dates and times in data sets. The course concludes with practical applications in data acquisition, cleaning, visualization, and manipulation, ensuring learners are well-prepared to tackle real-world data science challenges using R. Learning Outcomes Develop a foundational understanding of R's role in data science and proficiency in RStudio. Gain fluency in R programming basics, enabling the handling of complex data tasks. Acquire skills in managing various R data structures for efficient data analysis. Master relational and logical operations for advanced data manipulation in R. Learn to create functions and utilize R packages for expanded analytical capabilities. Why choose this R Programming for Data Science course? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards and CIQ after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Unlock career resources for CV improvement, interview readiness, and job success. Who is this R Programming for Data Science course for? Beginners in data science eager to learn R programming. Data analysts and scientists looking to enhance their skills in R. Researchers in various fields requiring advanced data analysis tools. Statisticians seeking to adopt R for more sophisticated data manipulations. Professionals in finance, healthcare, and other sectors needing data-driven insights. Career path Data Scientist (R Expertise): £30,000 - £70,000 Data Analyst (R Programming Skills): £27,000 - £55,000 Bioinformatics Scientist (R Proficiency): £35,000 - £60,000 Quantitative Analyst (R Knowledge): £40,000 - £80,000 Research Analyst (R Usage): £25,000 - £50,000 Business Intelligence Developer (R Familiarity): £32,000 - £65,000 Prerequisites This R Programming for Data Science does not require you to have any prior qualifications or experience. You can just enrol and start learning.This R Programming for Data Science was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Certification After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. Course Curriculum Unit 01: Data Science Overview Introduction to Data Science 00:01:00 Data Science: Career of the Future 00:04:00 What is Data Science? 00:02:00 Data Science as a Process 00:02:00 Data Science Toolbox 00:03:00 Data Science Process Explained 00:05:00 What's next? 00:02:00 Unit 02: R and RStudio Engine and coding environment 00:03:00 Installing R and RStudio 00:04:00 RStudio: A quick tour 00:04:00 Unit 03: Introduction to Basics Arithmetic with R 00:03:00 Variable assignment 00:04:00 Basic data types in R 00:03:00 Unit 04: Vectors Creating a vector 00:05:00 Naming a vector 00:04:00 Arithmetic calculations on vectors 00:07:00 Vector selection 00:06:00 Selection by comparison 00:04:00 Unit 05: Matrices What's a Matrix? 00:02:00 Analyzing Matrices 00:03:00 Naming a Matrix 00:05:00 Adding columns and rows to a matrix 00:06:00 Selection of matrix elements 00:03:00 Arithmetic with matrices 00:07:00 Additional Materials 00:00:00 Unit 06: Factors What's a Factor? 00:02:00 Categorical Variables and Factor Levels 00:04:00 Summarizing a Factor 00:01:00 Ordered Factors 00:05:00 Unit 07: Data Frames What's a Data Frame? 00:03:00 Creating Data Frames 00:20:00 Selection of Data Frame elements 00:03:00 Conditional selection 00:03:00 Sorting a Data Frame 00:03:00 Additional Materials 00:00:00 Unit 08: Lists Why would you need lists? 00:01:00 Creating a List 00:06:00 Selecting elements from a list 00:03:00 Adding more data to the list 00:02:00 Additional Materials 00:00:00 Unit 09: Relational Operators Equality 00:03:00 Greater and Less Than 00:03:00 Compare Vectors 00:03:00 Compare Matrices 00:02:00 Additional Materials 00:00:00 Unit 10: Logical Operators AND, OR, NOT Operators 00:04:00 Logical operators with vectors and matrices 00:04:00 Reverse the result: (!) 00:01:00 Relational and Logical Operators together 00:06:00 Additional Materials 00:00:00 Unit 11: Conditional Statements The IF statement 00:04:00 IFELSE 00:03:00 The ELSEIF statement 00:05:00 Full Exercise 00:03:00 Additional Materials 00:00:00 Unit 12: Loops Write a While loop 00:04:00 Looping with more conditions 00:04:00 Break: stop the While Loop 00:04:00 What's a For loop? 00:02:00 Loop over a vector 00:02:00 Loop over a list 00:03:00 Loop over a matrix 00:04:00 For loop with conditionals 00:01:00 Using Next and Break with For loop 00:03:00 Additional Materials 00:00:00 Unit 13: Functions What is a Function? 00:02:00 Arguments matching 00:03:00 Required and Optional Arguments 00:03:00 Nested functions 00:02:00 Writing own functions 00:03:00 Functions with no arguments 00:02:00 Defining default arguments in functions 00:04:00 Function scoping 00:02:00 Control flow in functions 00:03:00 Additional Materials 00:00:00 Unit 14: R Packages Installing R Packages 00:01:00 Loading R Packages 00:04:00 Different ways to load a package 00:02:00 Additional Materials 00:00:00 Unit 15: The Apply Family - lapply What is lapply and when is used? 00:04:00 Use lapply with user-defined functions 00:03:00 lapply and anonymous functions 00:01:00 Use lapply with additional arguments 00:04:00 Additional Materials 00:00:00 Unit 16: The apply Family - sapply & vapply What is sapply? 00:02:00 How to use sapply 00:02:00 sapply with your own function 00:02:00 sapply with a function returning a vector 00:02:00 When can't sapply simplify? 00:02:00 What is vapply and why is it used? 00:04:00 Additional Materials 00:00:00 Unit 17: Useful Functions Mathematical functions 00:05:00 Data Utilities 00:08:00 Additional Materials 00:00:00 Unit 18: Regular Expressions grepl & grep 00:04:00 Metacharacters 00:05:00 sub & gsub 00:02:00 More metacharacters 00:04:00 Additional Materials 00:00:00 Unit 19: Dates and Times Today and Now 00:02:00 Create and format dates 00:06:00 Create and format times 00:03:00 Calculations with Dates 00:03:00 Calculations with Times 00:07:00 Additional Materials 00:00:00 Unit 20: Getting and Cleaning Data Get and set current directory 00:04:00 Get data from the web 00:04:00 Loading flat files 00:03:00 Loading Excel files 00:05:00 Additional Materials 00:00:00 Unit 21: Plotting Data in R Base plotting system 00:03:00 Base plots: Histograms 00:03:00 Base plots: Scatterplots 00:05:00 Base plots: Regression Line 00:03:00 Base plots: Boxplot 00:03:00 Unit 22: Data Manipulation with dplyr Introduction to dplyr package 00:04:00 Using the pipe operator (%>%) 00:02:00 Columns component: select() 00:05:00 Columns component: rename() and rename_with() 00:02:00 Columns component: mutate() 00:02:00 Columns component: relocate() 00:02:00 Rows component: filter() 00:01:00 Rows component: slice() 00:04:00 Rows component: arrange() 00:01:00 Rows component: rowwise() 00:02:00 Grouping of rows: summarise() 00:03:00 Grouping of rows: across() 00:02:00 COVID-19 Analysis Task 00:08:00 Additional Materials 00:00:00 Assignment Assignment - R Programming for Data Science 00:00:00