Introduction
  • Warm Welcome!
  • Why you should learn R?
  • What you will learn in this course?
R Fundamentals
  • Installing R (console) and RStudio (IDE)
  • Getting to know R - Setting Context
  • R Basics - Working Directory, Environment Variables and more!
  • R Basics - Loading and Executing R scripts from local file system
  • Handling Working Directory
R Data Types
  • R Atomic Data Types Intro - What you must know about Numeric and Integers in R?
  • Complex and Character Data Types (Atomic)
  • Character Data Type (Atomic) + Important Data Transformation Functions (1)
  • Character Data Type (Atomic) + Important Data Transformation Functions (2)
  • Character Data Type (Atomic) + Important Data Transformation Functions (3)
  • Logical Data Type (Atomic) and Its known Implications
  • Atomic Data Types and Nuances in Coercioning (Explicit/Implicit)
  • Data Types Coercions
R Data Structure - Vectors
  • Vectors - Creation, Homogeneity, Coercion Implications and Important Functions!
  • Vectors - Comparing different ways to create vectors in R!
  • Vectors - Understanding Indexing like never before!
  • Vectors - Indexing (Out of Bound scenarios) and How Pros use it!
  • Vectors - Flatness property and its critical implications in Indexing!
  • Vectors - Labels and their Advanced Usage in Indexing
  • Vectors - Assigning Attributes and its use-case as Metadata
  • Indexing Vectors
R Data Structure - Matrices
  • Matrices - Getting Acquainted, Creation and its operational functions!
  • Matrices - Creation and Implications related to its Dimensions
  • Matrices - Creation from Vectors + Naming Dimensions (Explicit, Implicit)
  • Matrices - Dimensions (Advanced) and Intro to Indexing
  • Matrices - Indexing Continued
  • Matrices - Advanced Indexing using DimensionNames
  • Matrices - Even more Advanced Indexing!
  • Matrices - Operations!
R Data Structure - Lists
  • Lists - Getting Introduced to one of the most powerful data structures in R
  • Lists - Comparing with Vectors w.r.t Heterogeneity and Introducing Indexing
  • Lists - Comprehending their Recursive Nature in comparison with Vectors
  • Lists - Converting to and from Vectors and implications (coercion, flatness)
  • Lists - Nuances in Determining Length in the context of Recursiveness
  • Lists - Nuances in Determining Length and Class of Elements
  • List - Advanced Indexing also using Labels
  • List - Comparison of Indexing ways and Implications
R Data Structure - Data Frames
  • Data Frames - Introducing The holy grail of processing Structured Data
  • Data Frames - Creation and important functions for Basic Exploratory Analysis
  • Data Frames - More Important Functions for Basic Exploratory Analysis
  • Data Frames - Creation from Lists
  • Data Frames - Creation from Lists, Matrices and Vectors
  • Data Frames - Everything you need to know about Subsetting
  • Data Frames - Handling Missing Values like Pros!
  • Data Frames - Imputing Missing Values like Pros!
  • Data Frames - Advanced Subsetting Techniques for robust analytics
R Control Structures
  • While Loops in R
  • For Loops in R - Intro and Practical Use-Cases
  • If Else Structures in R
  • If Else Structures in R (2)
  • If Else Structures in R (3)
Data Science Application in R - Automated Web Scraping Bot
  • Web Scraping - Setting Context + Highlighting Use-Cases
  • Web Scraping - One Simple yet Powerful Way to do so!
  • Web Scraping - Use Case: Custom Churn Analysis
  • Use Case: Custom Churn - Performing Data Munging and Transformations
  • Use Case: Custom Churn - Performing Data Munging and Transformations
  • Use Case: Custom Churn - Performing Data Cleansing
  • Web Scraping - Contextual understanding of HTML
  • Web Scraping - Contextual Understanding of HTML Tags
  • Web Scraping - How to exploit the Structure of Web Page for Efficient Scraping
  • Web Scraping - Contextual Understanding of HTML Document Object Model (DOM)
  • Web Scraping on Steroids - XPath in R!
  • Web Scraping on Steroids - XPath in R (2)
  • Web Scraping using XPath - Programmatic Extraction of Data from HTML Tags
  • Web Scraping using XPath - Programmatic Extraction of Data from HTML Tags (2)
  • Automating Web Scraping - RSelenium!
  • Automated Web Scraping - Contextual Understanding of Selenium Components
  • Automated Web Scraping - installing RSelenium in R
  • Automated Web Scraping - Initialising RSelenium Server
  • Automated Web Scraping - Connecting to RSelenium Server using Reference Class
  • Automated Web Scraping - Navigating and Sending Key Strokes in Web Pages
  • Web Scraping Use Case Context Setting
  • Web Scraping Pipeline - Deep dive of workflow pattern
  • Systematic analysis of website for efficient Scraping
  • Installing and Loading RSelenium
  • Starting Selenium Server - The right way!
  • Handling RSelenium's Driver Issues
  • Launching Selenium Server jar with correct driver settings (part 2)
  • Web Scraper Program Initialisation and Remote Driver Object Instantiation
  • Navigating web pages using RSelenium and Using Xpath for data extraction
  • Using R's Apply Family of Functions for Data Extraction from RSelenium Objects
  • Advanced Data Munging using R Regex and String Processing Functions
  • Advanced Data Munging using R Regex and String processing functions (II)
  • Advanced Data Munging - Discretizing Continuous Values
  • Advanced Data Frames Manipulation
  • Orchestrating Automation of Web Scraping Routine
  • Advanced Statistical Analysis and Visualisation for Informed Decision Making