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R Programming Hands-on Specialization for Data Science (Lv1)
Introduction
Warm Welcome! (3:21)
Why you should learn R? (10:26)
What you will learn in this course? (7:29)
R Fundamentals
Installing R (console) and RStudio (IDE) (7:26)
Getting to know R - Setting Context (2:19)
R Basics - Working Directory, Environment Variables and more! (13:13)
R Basics - Loading and Executing R scripts from local file system (5:47)
R Data Types
R Atomic Data Types Intro - What you must know about Numeric and Integers in R? (9:45)
Complex and Character Data Types (Atomic) (5:43)
Character Data Type (Atomic) + Important Data Transformation Functions (1) (4:55)
Character Data Type (Atomic) + Important Data Transformation Functions (2) (3:52)
Character Data Type (Atomic) + Important Data Transformation Functions (3) (7:55)
Logical Data Type (Atomic) and Its known Implications (4:30)
Atomic Data Types and Nuances in Coercioning (Explicit/Implicit) (9:33)
R Data Structure - Vectors
Vectors - Creation, Homogeneity, Coercion Implications and Important Functions! (12:47)
Vectors - Comparing different ways to create vectors in R! (5:36)
Vectors - Understanding Indexing like never before! (10:12)
Vectors - Indexing (Out of Bound scenarios) and How Pros use it! (10:25)
Vectors - Flatness property and its critical implications in Indexing! (5:45)
Vectors - Labels and their Advanced Usage in Indexing (8:53)
Vectors - Assigning Attributes and its use-case as Metadata (5:33)
R Data Structure - Matrices
Matrices - Getting Acquainted, Creation and its operational functions! (11:21)
Matrices - Creation and Implications related to its Dimensions (6:51)
Matrices - Creation from Vectors + Naming Dimensions (Explicit, Implicit) (14:29)
Matrices - Dimensions (Advanced) and Intro to Indexing (4:25)
Matrices - Indexing Continued (3:46)
Matrices - Advanced Indexing using DimensionNames (4:47)
Matrices - Even more Advanced Indexing! (7:40)
Matrices - Operations! (6:48)
R Data Structure - Lists
Lists - Getting Introduced to one of the most powerful data structures in R (6:52)
Lists - Comparing with Vectors w.r.t Heterogeneity and Introducing Indexing (5:11)
Lists - Comprehending their Recursive Nature in comparison with Vectors (3:49)
Lists - Converting to and from Vectors and implications (coercion, flatness) (5:14)
Lists - Nuances in Determining Length in the context of Recursiveness (4:21)
Lists - Nuances in Determining Length and Class of Elements (6:37)
List - Advanced Indexing also using Labels (9:04)
List - Comparison of Indexing ways and Implications (5:41)
R Data Structure - Data Frames
Data Frames - Introducing The holy grail of processing Structured Data (9:41)
Data Frames - Creation and important functions for Basic Exploratory Analysis (13:40)
Data Frames - More Important Functions for Basic Exploratory Analysis (9:35)
Data Frames - Creation from Lists (2:18)
Data Frames - Creation from Lists, Matrices and Vectors (3:28)
Data Frames - Everything you need to know about Subsetting (15:43)
Data Frames - Handling Missing Values like Pros! (10:27)
Data Frames - Imputing Missing Values like Pros! (14:01)
Data Frames - Advanced Subsetting Techniques for robust analytics (12:42)
R Control Structures
While Loops in R (5:33)
For Loops in R - Intro and Practical Use-Cases (11:48)
If Else Structures in R (4:45)
If Else Structures in R (2) (3:29)
If Else Structures in R (3) (10:25)
Data Science Application in R - Automated Web Scraping Bot
Web Scraping - Setting Context + Highlighting Use-Cases (13:16)
Web Scraping - One Simple yet Powerful Way to do so! (12:14)
Web Scraping - Use Case: Custom Churn Analysis (8:56)
Use Case: Custom Churn - Performing Data Munging and Transformations (8:49)
Use Case: Custom Churn - Performing Data Munging and Transformations (12:57)
Use Case: Custom Churn - Performing Data Cleansing (11:18)
Web Scraping - Contextual understanding of HTML (3:17)
Web Scraping - Contextual Understanding of HTML Tags (11:04)
Web Scraping - How to exploit the Structure of Web Page for Efficient Scraping (6:17)
Web Scraping - Contextual Understanding of HTML Document Object Model (DOM) (6:17)
Web Scraping on Steroids - XPath in R! (8:29)
Web Scraping on Steroids - XPath in R (2) (1:00)
Web Scraping using XPath - Programmatic Extraction of Data from HTML Tags (5:19)
Web Scraping using XPath - Programmatic Extraction of Data from HTML Tags (2) (3:11)
Automating Web Scraping - RSelenium! (5:21)
Automated Web Scraping - Contextual Understanding of Selenium Components (6:10)
Automated Web Scraping - installing RSelenium in R (5:01)
Automated Web Scraping - Initialising RSelenium Server (5:40)
Automated Web Scraping - Connecting to RSelenium Server using Reference Class (9:07)
Automated Web Scraping - Navigating and Sending Key Strokes in Web Pages (11:13)
Web Scraping Use Case Context Setting (6:20)
Web Scraping Pipeline - Deep dive of workflow pattern (7:42)
Systematic analysis of website for efficient Scraping (5:55)
Installing and Loading RSelenium (4:36)
Starting Selenium Server - The right way! (5:40)
Handling RSelenium's Driver Issues (1:48)
Launching Selenium Server jar with correct Driver Settings (1:29)
Launching Selenium Server jar with correct driver settings (part 2) (3:50)
Web Scraper Program Initialisation and Remote Driver Object Instantiation (6:34)
Navigating web pages using RSelenium and Using Xpath for data extraction (10:01)
Using R's Apply Family of Functions for Data Extraction from RSelenium Objects (5:49)
Advanced Data Munging using R Regex and String Processing Functions (8:13)
Advanced Data Munging using R Regex and String processing functions (II) (3:39)
Advanced Data Munging - Discretizing Continuous Values (9:07)
Advanced Data Frames Manipulation (11:54)
Orchestrating Automation of Web Scraping Routine (7:41)
Advanced Statistical Analysis and Visualisation for Informed Decision Making (16:01)
Lists - Converting to and from Vectors and implications (coercion, flatness)
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