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Learn Data Science and Machine Learning with R from A-Z- Level 3

5( 2 REVIEWS )
129 STUDENTS
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Course Curriculum

1. Introduction to Data Science +ML with R from A-Z
1.1. Intro To DS+ML Section Overview FREE 00:03:00
1.2. What is Data Science? FREE 00:10:00
1.3. Machine Learning Overview FREE 00:05:00
1.4. Who is this course for? FREE 00:03:00
1.5. Data Science + Machine Learning Marketplace FREE 00:05:00
1.6. DS+ ML Job Opportunities FREE 00:03:00
1.7. Data Science Job Roles 00:04:00
2. Getting Started with R
2.1. Getting Started 00:11:00
2.2. Basics 00:06:00
2.3. Files 00:11:00
2.4. R Studio 00:07:00
2.5. Tidyverse 00:05:00
2.6. Resources 00:04:00
3. Data Types and Structures in R
3.1. Section Introduction 00:30:00
3.2. Basic Types 00:09:00
3.3. Vectors Part One 00:20:00
3.4. Vectors Part Two 00:25:00
3.5. Vectors: Missing Values 00:16:00
3.6. Vectors: Coercion 00:14:00
3.7. Vectors: Naming 00:10:00
3.8. Vectors: Misc. 00:06:00
3.9. Matrices 00:31:00
3.10. Lists 00:32:00
3.11. Introduction to Data Frames 00:19:00
3.12. Creating Data Frames 00:20:00
3.13. Data Frames: Helper Functions 00:31:00
3.14. Data Frames: Tibbles 00:39:00
4. Intermediate R
4.1. Section Introduction 00:47:00
4.2. Relational Operators 00:11:00
4.3. Logical Operators 00:07:00
4.4. Conditional Statements 00:11:00
4.5. Loops 00:08:00
4.6. Functions 00:14:00
4.7. Packages 00:11:00
4.8. Factors 00:28:00
4.9. Dates & Times 00:30:00
4.10. Functional Programming 00:37:00
4.11. Data Import/Export 00:22:00
4.12. Databases 00:27:00
5. Data Manipulation in R
5.1. Section Introduction 00:36:00
5.2. Tidy Data 00:11:00
5.3. The Pipe Operator 00:15:00
5.4. {dplyr}: The Filter Verb 00:22:00
5.5. {dplyr}: The Select Verb 00:46:00
5.6. {dplyr}: The Mutate Verb 00:32:00
5.7. {dplyr}: The Arrange Verb 00:10:00
5.8. {dplyr}: The Summarize Verb 00:23:00
5.9. Data Pivoting: {tidyr} 00:43:00
5.10. String Manipulation: {stringr} 00:33:00
5.11. Web Scraping: {rvest} 00:59:00
5.12. JSON Parsing: {jsonlite} 00:11:00
6. Data Visualization in R
6.1. Section Introduction 00:17:00
6.2. Getting Started 00:16:00
6.3. Aesthetics Mappings 00:25:00
6.4. Single Variable Plots 00:37:00
6.5. Two-Variable Plots 00:21:00
6.6. Facets, Layering, and Coordinate Systems 00:18:00
6.7. Styling and Saving 00:12:00
7. Creating Reports with R Markdown
7.1. Intro To R Markdown 00:29:00
8. Building Webapps with R Shiny
8.1. Intro to R Shiny 00:26:00
8.2. A Basic Webapp 00:31:00
8.3. Other Examples 00:34:00
9. Introduction to Machine Learning
9.1. Intro to ML Part 1 00:22:00
9.2. Intro to ML Part 2 00:47:00
10. Data Preprocessing
10.1. Section Overview 00:27:00
10.2. Data Preprocessing 00:38:00
11. Linear Regression: A Simple Model
11.1. Section Introduction 00:25:00
11.2. A Simple Model 00:53:00
12. Exploratory Data Analysis
12.1. Section Introduction 00:25:00
12.2. Hands-on Exploratory Data Analysis 01:03:00
13. Linear Regression: A Real Model
13.1. Section Introduction 00:32:00
13.2. Linear Regression in R 00:53:00
14. Logistic Regression
14.1. Logistic Regression Intro 00:38:00
14.2. Logistic Regression in R 00:40:00
15. Starting a Career in Data Science
15.1. Section Overview 00:03:00
15.2. Creating A Data Science Resume 00:04:00
15.3. Getting Started with Freelancing 00:05:00
15.4. Top Freelance Websites 00:05:00
15.5. Personal Branding 00:05:00
15.6. Networking 00:04:00
15.7. Setting Up a Website 00:04:00
Completion Certificate Request
Completion Certificate Request

Students feedback

5

Avarage rating (2)
5
5 Star
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1 Star
    M T

    Mason Taylor

    September 10, 2021
    Thanks

    A well-designed platform to learn data science.

    C R

    Carol Robertson

    August 14, 2021
    Deep

    The information is up-to-date and deep.

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