Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
17 Hour(s) 45 Minute(s)
Language
English
Rating
1 views
Course Overview
Learn how to use the R programming language for data science and machine learning and data visualization!
Data Scientist has been ranked the number one job on Glassdoor and the average salary of a data scientist is over $120,000 in the United States according to Indeed! Data Science is a rewarding career that allows you to solve some of the world's most interesting problems!
This course is designed for both complete beginners with no programming experience or experienced developers looking to make the jump to Data Science!
This comprehensive course is comparable to other Data Science bootcamps that usually cost thousands of dollars, but now you can learn all that information at a fraction of the cost! With over 100 HD video lectures and detailed code notebooks for every lecture this is one of the most comprehensive course for data science and machine learning on Udemy!
We'll teach you how to program with R, how to create amazing data visualizations, and how to use Machine Learning with R! Here a just a few of the topics we will be learning:
- Programming with R
- Advanced R Features
- Using R Data Frames to solve complex tasks
- Use R to handle Excel Files
- Web scraping with R
- Connect R to SQL
- Use ggplot2 for data visualizations
- Use plotly for interactive visualizations
- Machine Learning with R, including:
- Linear Regression
- K Nearest Neighbors
- K Means Clustering
- Decision Trees
- Random Forests
- Data Mining Twitter
- Neural Nets and Deep Learning
- Support Vectore Machines
- and much, much more!
Enroll in the course and become a data scientist today!
Course Content
- 35 section(s)
- 128 lecture(s)
- Section 1 Course Introduction
- Section 2 Course Best Practices
- Section 3 Windows Installation Set-Up
- Section 4 Mac OS Installation Set-Up
- Section 5 Linux Installation
- Section 6 Development Environment Overview
- Section 7 Introduction to R Basics
- Section 8 R Matrices
- Section 9 R Data Frames
- Section 10 R Lists
- Section 11 Data Input and Output with R
- Section 12 R Programming Basics
- Section 13 Advanced R Programming
- Section 14 Data Manipulation with R
- Section 15 Data Visualization with R
- Section 16 Data Visualization Project
- Section 17 Interactive Visualizations with Plotly
- Section 18 Capstone Data Project
- Section 19 Introduction to Machine Learning with R
- Section 20 Machine Learning with R - Linear Regression
- Section 21 Machine Learning Project - Linear Regression
- Section 22 Machine Learning with R - Logistic Regression
- Section 23 Machine Learning Project - Logistic Regression
- Section 24 Machine Learning with R - K Nearest Neighbors
- Section 25 Machine Learning Project - K Nearest Neighbors
- Section 26 Machine Learning with R - Decision Trees and Random Forests
- Section 27 Machine Learning Project - Decision Trees and Random Forests
- Section 28 Machine Learning with R - Support Vector Machines
- Section 29 Machine Learning Project - Support Vector Machines
- Section 30 Machine Learning with R - K-means Clustering
- Section 31 Machine Learning Project - K-means Clustering
- Section 32 Machine Learning with R - Natural Language Processing
- Section 33 Machine Learning with R - Neural Nets
- Section 34 Machine Learning Project - Neural Nets
- Section 35 Bonus Section
What You’ll Learn
- Program in R, Use R for Data Analysis, Create Data Visualizations, Use R to handle csv,excel,SQL files or web scraping, Use R to manipulate data easily, Use R for Machine Learning Algorithms, Use R for Data Science
Skills covered in this course
Reviews
-
PPercy Manuel Huancoillo Ticona
Excellent
-
MMarkus Riskumäki
Very clear instructions, and a hands on experience that, I think, actually made me learn the topics quicker than a equivalent course in my university. Only thing I wish there were more course-material about was the natural language processing section. But, all in all a huge recommendation!
-
JJIHYUN NOH
since it's 2026 now, I can feel there's some code to be updated! but generally, I highly recommend you to take this course! everyting is well structured and clear!
-
MMangesh Kotkar
Very well explained with examples and assignments.
