Description : Data Scientist with R Career Track on DataCamp. Gain the career-building R skills you need to succeed as a data scientist. No prior coding experience required. In this track,you’ll learn how this versatile language allows you to import, clean, manipulate, and visualize data—all integral skills for any aspiring data professional or researcher. Through interactive exercises, you’ll get hands-on with some of the most popular R packages, including ggplot2 and tidyverse packages like dplyr and readr. You’ll then work with real-world datasets to learn the statistical and machine learning techniques you need to write your own functions and perform cluster analysis. Start this track, grow your R skills, and begin your journey to becoming a confident data scientist.
Sr. No | Course | Status | Featured |
---|---|---|---|
01. | Introduction to R | ✅ | 🌟 |
02. | Intermediate R | ✅ | 🌟 |
03. | Introduction to the Tidyverse | ✅ | |
04. | Data Manipulation with dplyr | ✅ | 🌟 |
05. | Joining Data with dplyr | ✅ | 🌟 |
06. | Introduction to Data Visualization with ggplot2 | ✅ | |
07. | Intermediate Data Visualization with ggplot2 | ✅ | |
08. | Data Manipulation with R | ✅ | |
09. | Reporting with R Markdown | ✅ | 🌟 |
10. | Introduction to Importing Data in R | ✅ | 🌟 |
11. | Intermediate Importing Data in R | ✅ | |
12. | Cleaning Data in R | ✅ | 🌟 |
13. | Working with Dates and Times in R | ✅ | |
14. | Importing & Cleaning Data with R | ✅ | |
15. | Introduction to Writing Functions in R | ✅ | 🌟 |
16. | R Programming | ✅ | 🌟 |
17. | Exploratory Data Analysis in R | ✅ | |
18. | Case Study: Exploratory Data Analysis in R | ✅ | 🌟 |
19. | Introduction to Statistics in R | ✅ | 🌟 |
20. | Introduction to Regression in R | ✅ | |
21. | Intermediate Regression in R | ✅ | |
22. | Supervised Learning in R: Classification | ✅ | 🌟 |
23. | Supervised Learning in R: Regression | ✅ | |
24. | Unsupervised Learning in R | ✅ | |
25. | Cluster Analysis in R | ✅ | 🌟 |
26. | Hypothesis Testing in R | ✅ | 🌟 |