Autoplay
Autocomplete
Previous Lesson
Complete and Continue
Learn Data Science & Machine Learning with R from A-Z Course
Training Overview
Description of Training
Video Overview (3:44)
Section 1: Data Science and Machine Learning Course Intro
Intro To DS+ML Section Overview (2:30)
What is Data Science? (9:47)
Machine Learning Overview (5:26)
Data Science + Machine Learning Marketplace (4:38)
Who is this course for? (2:57)
DS+ ML Job Opportunities (2:37)
Data Science Job Roles (4:04)
Section 2: Getting Started with R
Getting Started (10:58)
Basics (6:24)
Files (11:08)
R Studio (6:58)
Tidyverse (5:19)
Resources (4:02)
Section 3: Data Types and Structures in R
Section Introduction (30:03)
Basic Types (8:46)
Vectors Part One (19:40)
Vectors Part Two (24:51)
Vectors: Missing Values (15:36)
Vectors: Coercion (14:07)
Vectors: Naming (10:16)
Vectors: Misc. (5:59)
Matrices (31:27)
Lists (31:41)
Introduction to Data Frames (19:20)
Creating Data Frames (19:50)
Data Frames: Helper Functions (31:12)
Data Frames: Tibbles (39:03)
Section 4: Intermediate R
Relational Operators (11:06)
Section Introduction (46:31)
Logical Operators (7:04)
Conditional Statements (11:20)
Loops (7:56)
Functions (14:19)
Packages (11:29)
Factors (28:14)
Dates & Times (30:10)
Functional Programming (36:41)
Data Import/Export (22:06)
Databases (27:08)
Section 5: Data Manipulation in R
Section Introduction (36:29)
Tidy Data (10:53)
The Pipe Operator (14:50)
{dplyr}: The Filter Verb (21:34)
{dplyr}: The Select Verb (46:03)
{dplyr}: The Mutate Verb (31:57)
{dplyr}: The Arrange Verb (10:03)
{dplyr}: The Summarize Verb (23:05)
Data Pivoting: {tidyr} (42:41)
String Manipulation: {stringr} (32:38)
Web Scraping: {rvest} (58:53)
JSON Parsing: {jsonlite} (10:46)
Section 6: Data Visualization in R
Section Introduction (17:13)
Getting Started (15:37)
Aesthetics Mappings (24:45)
Single Variable Plots (36:50)
Two-Variable Plots (20:34)
Facets, Layering, and Coordinate Systems (17:56)
Styling and Saving (11:33)
Section 7: Creating Reports with R Markdown
Intro To R Markdown (28:54)
Section 8: Building Webapps with R Shiny
Intro to R Shiny (26:05)
A Basic Webapp (31:18)
Other Examples (34:05)
Section 9: Introduction to Machine Learning
Intro to ML Part 2 (46:45)
Intro to ML Part 1 (21:48)
Section 10: Data Preprocessing
Section Overview (27:03)
Data Preprocessing (37:47)
Section 11: Linear Regression: A Simple Model
Section Introduction (25:09)
A Simple Model (53:05)
Section 12: Exploratory Data Analysis
Section Introduction (25:03)
Hands-on Exploratory Data Analysis (62:57)
Section 13: Linear Regression - A Real Model
Section Introduction (32:04)
Linear Regression in R (52:48)
Section 14: Logistic Regression
Logistic Regression in R (39:37)
Logistic Regression Intro (37:48)
Section 15: Starting a Career in Data Science
Section Overview (2:54)
Creating A Data Science Resume (3:43)
Getting Started with Freelancing (4:44)
Top Freelance Websites (5:18)
Personal Branding (5:27)
Networking (3:50)
Setting Up a Website (3:42)
Audio Version of the Training
Audio Download
Intro to R Shiny
Lesson content locked
If you're already enrolled,
you'll need to login
.
Enroll in Course to Unlock