On March 20, DataCamp will make some improvements to our content catalog, including renaming, updating, and archiving courses and tracks.
Course Changes
Course Deprecations
| Course Title | Recommended Alternative |
| Designing and Analyzing Clinical Trials in R | Analyzing Survey Data in R |
| Data Privacy and Anonymization in R | Introduction to Data Privacy |
| Introduction to Statistical Modeling in R | Supervised Learning in R: Regression |
| Intermediate Statistical Modeling in R | Experimental Design in R |
| Network Analysis in the Tidyverse | Network Analysis in R |
| Practicing Machine Learning Interview Questions in R | Machine Learning with caret in R; Unsupervised Learning in R |
| Topic Modeling in R | Introduction to Text Analysis in R |
| Survey and Measurement Development in R | Factor Analysis in R |
| Spatial Statistics in R | Visualizing Geospatial Data in R |
| Natural Language Generation in Python | Building Chatbots in Python |
| Spatial Analysis with sf and raster in R | Visualizing Geospatial Data in R |
| Introduction to TensorFlow in R | Machine Learning with caret in R |
| Analyzing Election and Polling Data in R | Data Manipulation with dplyr |
Archived Courses
| Course Title | Recommended Alternatives |
| DAX in Power BI | Intermediate DAX and DAX Functions in Power BI |
| Data Analysis in Power BI | Exploratory Data Analysis and Trend Analysis in Power BI |
Renamed Courses
Starting March 20 the following courses will have new names. Please note that the content of these courses is otherwise unchanged.
| Current Course Title | New Course Title |
| Introduction to Spreadsheets | Spreadsheets Foundations |
| Spreadsheets Foundations | Introduction to Spreadsheets |
| Data Analysis in Spreadsheets | Analyzing Data in Spreadsheets |
| Analyzing Data in Spreadsheets | Data Analysis in Spreadsheets |
| Exploratory Data Analysis in Python | Exploring and Analyzing Data in Python |
| Exploring and Analyzing Data in Python | Exploratory Data Analysis in Python |
| Introduction to Git | Introduction to Version Control with Git |
| Introduction to Version Control with Git | Introduction to Git |
| Foundations of Inference | Foundations of Inference in R |
Track Changes
Track Deprecations
Spatial Data with R
Track Renames
| Current Track Title | New Track Title |
| Data Engineer with Python | Data Engineer |
Skill Track Changes
Spreadsheet Fundamentals
| Current Track | New Track |
| Data Analysis in Spreadsheets | Introduction to Spreadsheets |
| Intermediate Spreadsheets | Data Analysis in Spreadsheets |
| Pivot Table in Spreadsheets | Intermediate Spreadsheets |
| Data Visualization in Spreadsheets | Pivot Table in Spreadsheets |
| Data Visualization in Spreadsheets |
Data Manipulation in R
| Removed Courses | Added Courses |
| Data Manipulation with data.table in R | Reshaping Data with tidyr |
| Joining Data with data.table in R |
Data Manipulation in Python
| Removed Courses | Added Courses |
| Analyzing Police Activity with pandas | Reshaping Data with pandas |
| Introduction to Databases in Python | Introduction to NumPy |
Power BI Fundamentals
| Removed Courses | Added Courses |
| Case Study: Analyzing Job Market Data in Power BI | Case Study: Analyzing Customer Churn in Power BI |
Career Track Changes
Data Scientist with Python
| Removed Content | Added Content |
| Introduction to NumPy | What and Where are the World’s Oldest Businesses? |
| The GitHub History of the Scala Language | Working with Categorical Data in Python |
| Analyzing Police Activity with pandas | Exploratory Data Analysis in Python |
| Exploratory Data Analysis in Python | |
| Intermediate Importing Data in Python |
Data Analyst with Python
| Removed Content | Added Content |
| Introduction to Data Science in Python | Introduction to Python |
| Exploratory Data Analysis in Python | Exploratory Data Analysis in Python |
Data Scientist with R
| Removed Content | Added Content |
| Reporting with R Markdown | Experimental Design in R |
| Intermediate Importing Data in R | |
| Case Study: Exploratory Data Analysis in R |
R Programmer
| Removed Content | Added Content |
| Data Manipulation with R | Introduction to Git |
Python Programmer
| Removed Content | Added Content |
| Introduction to Data Science in Python | Introduction to Python |
| Intermediate Python | |
| Introduction to Git |
Data Engineer with Python
| Removed Content | Added Content |
| Introduction to Data Engineering | Introduction to SQL |
| Writing Functions in Python | Intermediate SQL |
| Introduction to Shell | Joining Data in SQL |
| Data Processing in Shell | Introduction to Python |
| Introduction to Bash Scripting | Intermediate Python |
| Unit Testing for Data Science in Python | Introduction to Importing Data in Python |
| Object-Oriented Programming in Python | Intermediate Importing Data in Python |
| Introduction to Airflow in Python | Understanding Cloud Computing |
| Introduction to PySpark | Cleaning Data in Python |
| Introduction to AWS Boto in Python | Designing a Bank Marketing Database (Project) |
| Introduction to Scala | Understanding Data Visualization |
| Big Data Fundamentals with PySpark | Introduction to Git |
| Cleaning Data with PySpark | Software Engineering for Data Scientist in Python |
| Introduction to MongoDB in Python |
Next Steps for Learners and Admins
- DataCamp learners can choose to switch to the updated track. Alternatively, you can continue to make progress on the original track. Don’t worry; you will not have to repeat any chapters you’ve already completed whatever option you choose. Read the following article to learn more: How do I switch to an updated track version?
- Your custom tracks and assignments will automatically update to reflect the new content and members already enrolled in these tracks can choose to switch to the updated version. If you would like to edit your existing assignments, please read the following article to learn more: Editing and managing an assignment