About This Course
Course Curriculum
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Intro To DS+ML Section Overview
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 + Machine Learning Marketplace
00:05:00 -
DS + ML Job Opportunities
00:03:00 -
Data Science Job Roles
00:03:00
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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
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Section Introduction
00:30:00 -
Basic Type
00:09:00 -
Vectors 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 -
Matrices
00:31:00 -
Lists
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
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Section Introduction
00:47:00 -
Relational Operations
00:11:00 -
Logical Operators
00:07:00 -
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
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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 -
String Manipulation
00:33:00 -
Web Scraping
00:59:00 -
JSON Parsing
00:11:00
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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
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Creating with R Markdown
00:29:00
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Introduction to R Shiny
00:26:00 -
A Basic R Shiny App
00:31:00 -
Other Examples with R Shiny
00:34:00
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Machine Learning Part 1
00:22:00 -
Machine Learning Part 2
00:47:00
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Data Preprocessing Overview
00:27:00 -
Data Preprocessing
00:38:00
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Section Introduction
00:25:00 -
A Simple Model
00:53:00
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Section Introduction
00:25:00 -
Hands-on Exploratory Data Analysis
01:03:00
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Section Introduction
00:32:00 -
Linear Regression in R
00:53:00
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Logistic Regression Intro
00:38:00 -
Logistic Regression in R
00:40:00
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Starting a Data Science Career Section Overview
00:03:00 -
Creating A 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
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Resources – Data Science & Machine Learning with R
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Assignment – Data Science & Machine Learning with R
10:00:00
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