DataCamp Content Updates: September 2024

On September 19 2024, DataCamp will make some improvements to our content catalog, including renaming, updating, and archiving courses, projects, and tracks.

Course Deprecations

No courses will be deprecated this quarter.

Course Renames

No courses will be renamed this quarter.

Track Renames

# Track ID Track Title New Track Title
1. 16 Data Analyst with Python Data Analyst in Python
2. 5 Data Analyst with R Data Analyst in R
3. 2162 Machine Learning Scientist with Python Machine Learning Scientist in Python
4. 2014 Machine Learning Scientist with R Machine Learning Scientist in R
5. 1946 Statistician with R Statistician in R
6. 20 Quantitative Analyst with R Quantitative Analyst in R
7. 24 Machine Learning Fundamentals with Python Machine Learning Fundamentals in Python
8. 14 Data Manipulation with Python Data Manipulation in Python
9. 9 Data Manipulation with R Data Manipulation in R
10. 1206 Statistics Fundamentals with Python Statistics Fundamentals in Python
11. 10 Statistics Fundamentals with R Statistics Fundamentals in R
12. 1210 Data Visualization with Python Data Visualization in Python
13. 8 Data Visualization with R Data Visualization in R
14. 28 Time Series with Python Time Series in Python
15. 15 Time Series with R Time Series in R
16. 13 Importing & Cleaning Data with Python Importing & Cleaning Data in Python
17. 7 Importing & Cleaning Data with R Importing & Cleaning Data in R
18. 2491 Marketing Analytics with Python Marketing Analytics in Python
19. 1208 Marketing Analytics with R Marketing Analytics in R
20. 1899 Image Processing with Python Image Processing in Python
21. 27 Shiny Fundamentals with R Shiny Fundamentals in R
22. 49 Tidyverse Fundamentals with R Tidyverse Fundamentals in R
23. 30 Big Data with R Big Data in R
24. 1209 Statistical Inference with R Statistical Inference in R
25. 25 Text Mining with R Text Mining in R
26. 506 Network Analysis with R Network Analysis in R

 

Career Track Changes

Machine Learning Engineer

Current Track:

  1. MLOps Concepts
  2. End-to-End Machine Learning
  3. Developing Machine Learning Models for Production
  4. Project: Predictive Modeling for Agriculture
  5. Introduction to Shell
  6. MLOps Deployment and Lifecycling
  7. Introduction to MLflow
  8. Project: Predicting Temperature in London
  9. Fully Automated MLOps
  10. ETL and ELT in Python
  11. Monitoring Machine Learning Concepts
  12. Monitoring Machine Learning in Python
  13. Introduction to Docker
  14. CI/CD for Machine Learning

New Track:

  1. MLOps Concepts
  2. End-to-End Machine Learning
  3. Project: Predictive Modeling for Agriculture
  4. Introduction to Shell
  5. MLOps Deployment and Lifecycling
  6. Introduction to MLflow
  7. Project: Predicting Temperature in London
  8. ETL and ELT in Python
  9. Introduction to Data Versioning with DVC
  10. Monitoring Machine Learning Concepts
  11. Monitoring Machine Learning in Python
  12. Introduction to Docker
  13. CI/CD for Machine Learning

Removed Content

# Content ID Content Title Instructor Name
1. 30380 Developing Machine Learning Models for Production Sinan Ozdemir
2. 30016 Fully Automated MLOps DataCamp

 

Added Content

# Content ID Content Title Instructor Name
1. 35486 Introduction to Data Versioning with DVC DataCamp

 

Professional Data Engineer

Current Track:

  1. Understanding Modern Data Architecture
  2. Introduction to Shell
  3. Containerization and Virtualization Concepts
  4. Introduction to dbt
  5. Introduction to Object-Oriented Programming in Python
  6. Introduction to NoSQL
  7. DevOps Concepts
  8. Introduction to Testing in Python
  9. Project: Debugging a Sales Data Workflow
  10. Introduction to Docker
  11. Chapter: Getting to know PySpark
  12. Chapter: Manipulating data
  13. Chapter: Introduction to Big Data analysis with Spark
  14. Chapter: Programming in PySpark RDD’s
  15. Chapter: PySpark SQL & DataFrames
  16. Project: Cleaning an Orders Dataset with PySpark
  17. Chapter: Downloading Data on the Command Line
  18. Chapter: Data Pipeline on the Command Line
  19. Streaming Concepts
  20. Webinar: Impactful Data Engineering – with Datadog’s Wouter de Bie

New Track:

  1. Understanding Modern Data Architecture
  2. Introduction to Shell
  3. Containerization and Virtualization Concepts
  4. Introduction to dbt
  5. Introduction to Object-Oriented Programming in Python
  6. Introduction to NoSQL
  7. DevOps Concepts
  8. Introduction to Testing in Python
  9. Project: Debugging a Sales Data Workflow
  10. Introduction to Docker
  11. Chapter: Getting to know PySpark
  12. Chapter: Manipulating data
  13. Chapter: Introduction to Big Data analysis with Spark
  14. Chapter: Programming in PySpark RDD’s
  15. Chapter: PySpark SQL & DataFrames
  16. Project: Cleaning an Orders Dataset with PySpark
  17. Chapter: Downloading Data on the Command Line
  18. Chapter: Data Pipeline on the Command Line
  19. Streaming Concepts
  20. Introduction to Kafka
  21. Introduction to Kubernetes
  22. Webinar: Impactful Data Engineering – with Datadog’s Wouter de Bie

Removed Content

N/A

Added Content

# Content ID Content Title Instructor Name
1. 36655 Introduction to Kafka DataCamp
2. 35597 Introduction to Kubernetes DataCamp

 

Data Engineer in Python

Current Track:

  1. Understanding Cloud Computing
  2. Introduction to Python for Developers
  3. Intermediate Python for Developers
  4. Introduction to Importing Data in Python
  5. Intermediate Importing Data in Python
  6. Cleaning Data in Python
  7. Project: Cleaning Bank Marketing Campaign Data
  8. Writing Efficient Python Code
  9. Streamlined Data Ingestion with pandas
  10. Introduction to Git
  11. Software Engineering Principles in Python
  12. Project: Performing a Code Review
  13. ETL and ELT in Python
  14. Introduction to Airflow in Python
  15. Project: Building a Retail Data Pipeline

New Track:

  1. Understanding Cloud Computing
  2. Introduction to Python for Developers
  3. Intermediate Python for Developers
  4. Introduction to Importing Data in Python
  5. Intermediate Importing Data in Python
  6. Cleaning Data in Python
  7. Project: Cleaning Bank Marketing Campaign Data
  8. Writing Efficient Python Code
  9. Streamlined Data Ingestion with pandas
  10. Introduction to Git
  11. Software Engineering Principles in Python
  12. Project: Performing a Code Review
  13. Containerization and Virtualization Concepts
  14. ETL and ELT in Python
  15. Introduction to Airflow in Python
  16. Project: Building a Retail Data Pipeline

Removed Content

N/A

Added Content

# Content ID Content Title Instructor Name
1. 36462 Containerization and Virtualization Concepts DataCamp

 

Python Developer

Current Track:

  1. Introduction to Testing in Python
  2. Writing Efficient Python Code (Chapters 1-3)
  3. Introduction to Git
  4. Developing Python Packages
  5. Web Scraping in Python
  6. Project: Building a Calorie Intake Calculator
  7. Data Structures and Algorithms in Python

New Track:

  1. Introduction to Testing in Python
  2. Writing Efficient Python Code (Chapters 1-3)
  3. Introduction to Git
  4. Intermediate Object-Oriented Programming in Python
  5. Developing Python Packages
  6. Web Scraping in Python
  7. Project: Building a Calorie Intake Calculator
  8. Data Structures and Algorithms in Python

Removed Content

N/A

Added Content

# Content ID Content Title Instructor Name
1. 36306 Intermediate Object-Oriented Programming in Python DataCamp

 

Associate Data Scientist in R

Current Track:

  1. Introduction to R
  2. Intermediate R
  3. Introduction to the Tidyverse
  4. Data Manipulation with dplyr
  5. Project: Dr. Semmelweis and the Importance of Handwashing
  6. Joining Data with dplyr
  7. Introduction to Statistics in R
  8. Introduction to Data Visualization with ggplot2
  9. Intermediate Data Visualization with ggplot2
  10. Assessment: Data Manipulation with R
  11. Data Communication Concepts
  12. Introduction to Importing Data in R
  13. Cleaning Data in R
  14. Project: Exploring Airbnb Market Trends
  15. Working with Dates and Times in R
  16. Assessment: Importing & Cleaning Data with R
  17. Introduction to Writing Functions in R
  18. Assessment: R Programming
  19. Exploratory Data Analysis in R
  20. Introduction to Regression in R
  21. Project: Modeling Car Insurance Claim Outcomes
  22. Intermediate Regression in R
  23. Sampling in R
  24. Hypothesis Testing in R
  25. Project: Hypothesis Testing in Men’s and Women’s Soccer Matches
  26. Experimental Design in R
  27. Assessment: Statistics Fundamentals with R
  28. Supervised Learning in R: Classification
  29. Supervised Learning in R: Regression
  30. Unsupervised Learning in R

New Track:

  1. Introduction to R
  2. Intermediate R
  3. Introduction to the Tidyverse
  4. Data Manipulation with dplyr
  5. Project: Analyze the Popularity of Programming Languages
  6. Joining Data with dplyr
  7. Introduction to Statistics in R
  8. Introduction to Data Visualization with ggplot2
  9. Intermediate Data Visualization with ggplot2
  10. Assessment: Data Manipulation with R
  11. Data Communication Concepts
  12. Introduction to Importing Data in R
  13. Cleaning Data in R
  14. Project: Exploring Airbnb Market Trends
  15. Working with Dates and Times in R
  16. Assessment: Importing & Cleaning Data with R
  17. Introduction to Writing Functions in R
  18. Assessment: R Programming
  19. Exploratory Data Analysis in R
  20. Introduction to Regression in R
  21. Project: Modeling Car Insurance Claim Outcomes
  22. Intermediate Regression in R
  23. Sampling in R
  24. Hypothesis Testing in R
  25. Project: Hypothesis Testing in Men’s and Women’s Soccer Matches
  26. Experimental Design in R
  27. Assessment: Statistics Fundamentals with R
  28. Supervised Learning in R: Classification
  29. Supervised Learning in R: Regression
  30. Unsupervised Learning in R

Removed Content

# Content ID Content Title Instructor Name
1 1991 Dr. Semmelweis and the Importance of Handwashing DataCamp

 

Added Content

# Content ID Content Title Instructor Name
1 2557 Analyze the Popularity of Programming Languages DataCamp

 

Data Analyst with R

Current Track:

  1. Introduction to R
  2. Introduction to the Tidyverse
  3. Data Manipulation with dplyr
  4. Project: Dr. Semmelweis and the Importance of Handwashing
  5. Joining Data with dplyr
  6. Introduction to Statistics in R
  7. Introduction to Data Visualization with ggplot2
  8. Assessment: Data Manipulation with R
  9. Exploratory Data Analysis in R
  10. Sampling in R
  11. Hypothesis Testing in R
  12. Project: Hypothesis Testing in Men’s and Women’s Soccer Matches

New Track:

  1. Introduction to R
  2. Introduction to the Tidyverse
  3. Data Manipulation with dplyr
  4. Project: Analyze the Popularity of Programming Languages
  5. Joining Data with dplyr
  6. Introduction to Statistics in R
  7. Introduction to Data Visualization with ggplot2
  8. Assessment: Data Manipulation with R
  9. Exploratory Data Analysis in R
  10. Sampling in R
  11. Hypothesis Testing in R
  12. Project: Hypothesis Testing in Men’s and Women’s Soccer Matches

Removed Content

# Content ID Content Title Instructor Name
1 1991 Dr. Semmelweis and the Importance of Handwashing DataCamp

 

Added Content

# Content ID Content Title Instructor Name
1 2557 Analyze the Popularity of Programming Languages DataCamp

 

R Developer

Current Track:

  1. Introduction to R
  2. Data Manipulation with dplyr
  3. Project: Dr. Semmelweis and the Importance of Handwashing
  4. Writing Efficient R Code
  5. Working with Dates and Times in R
  6. String Manipulation with stringr in R
  7. Assessment: Data Manipulation with R
  8. Web Scraping in R
  9. Introduction to Writing Functions in R
  10. Introduction to Shell
  11. Introduction to Git
  12. Parallel Programming in R
  13. Defensive R Programming
  14. Developing R Packages
  15. Object-Oriented Programming with S3 and R6 in R
  16. Assessment: R Programming

New Track:

  1. Introduction to R
  2. Data Manipulation with dplyr
  3. Project: Analyze the Popularity of Programming Languages
  4. Writing Efficient R Code
  5. Working with Dates and Times in R
  6. String Manipulation with stringr in R
  7. Assessment: Data Manipulation with R
  8. Web Scraping in R
  9. Introduction to Writing Functions in R
  10. Introduction to Shell
  11. Introduction to Git
  12. Parallel Programming in R
  13. Defensive R Programming
  14. Developing R Packages
  15. Object-Oriented Programming with S3 and R6 in R
  16. Assessment: R Programming

Removed Content

# Content ID Content Title Instructor Name
1 1991 Dr. Semmelweis and the Importance of Handwashing DataCamp

 

Added Content

# Content ID Content Title Instructor Name
1 2557 Analyze the Popularity of Programming Languages DataCamp

 

Skill Track Changes

Python Data Fundamentals

Current Track:

  1. Introduction to Python
  2. Intermediate Python
  3. Project: Investigating Netflix Movies
  4. Introduction to Functions in Python
  5. Python Toolbox
  6. Assessment: Python Programming

New Track:

  1. Introduction to Python
  2. Intermediate Python
  3. Project: Investigating Netflix Movies
  4. Data Manipulation with pandas
  5. Joining Data with pandas
  6. Introduction to Data Visualization with Seaborn
  7. Introduction to Statistics in Python
  8. Exploratory Data Analysis in Python
  9. Project: Analyzing Crime in Los Angeles

Removed Content

# Content ID Content Title Instructor Name
1. 1532 Introduction to Functions in Python DataCamp
2. 1531 Python Toolbox DataCamp
3. 1679 Assessment: Python Programming DataCamp

 

Added Content

# Content ID Content Title Instructor Name
1. 22066 Data Manipulation with pandas DataCamp
2. 22639 Joining Data with pandas DataCamp
3. 15192 Introduction to Data Visualizaton with Seaborn DataCamp
4. 25412 Introduction to Statistics in Python DataCamp
5. 30656 Exploratory Data Analysis in Python DataCamp
6. 1876 Project: Analyzing Crime in Los Angeles DataCamp

 

Tidyverse Fundamentals with R

Current Track:

  1. Introduction to the Tidyverse
  2. Reshaping Data with tidyr
  3. Project: Dr. Semmelweis and the Importance of Handwashing
  4. Modeling with Data in the Tidyverse
  5. Communicating with Data in the Tidyverse
  6. Categorical Data in the Tidyverse

New Track:

  1. Introduction to the Tidyverse
  2. Reshaping Data with tidyr
  3. Project: Analyze the Popularity of Programming Languages
  4. Modeling with Data in the Tidyverse
  5. Communicating with Data in the Tidyverse
  6. Categorical Data in the Tidyverse

Removed Content

# Content ID Content Title Instructor Name
1 1991 Dr. Semmelweis and the Importance of Handwashing DataCamp

 

Added Content

# Content ID Content Title Instructor Name
1 2557 Analyze the Popularity of Programming Languages DataCamp

 

Alteryx Fundamentals

Current Track:

  1. Introduction to Alteryx
  2. Data Preparation in Alteryx
  3. Data Transformation in Alteryx
  4. Data Manipulation in Alteryx
  5. Case Study: Analyzing Sales Data in Alteryx

New Track:

  1. Introduction to Alteryx
  2. Data Preparation in Alteryx
  3. Data Transformation in Alteryx
  4. Data Manipulation in Alteryx
  5. Case Study: Analyzing Sales Data in Alteryx
  6. Case Study: Analyzing Fitness Data in Alteryx

Removed Content

N/A

Added Content

# Content ID Content Title Instructor Name
  36546 Case Study: Analyzing Fitness Data in Alteryx Giniya Gupta

 

Data Skills for Business

Current Track:

  1. Data Science for Business
  2. Introduction to Google Sheets
  3. Machine Learning for Business
  4. Data-Driven Decision-Making for Business
  5. Marketing Analytics for Business
  6. Understanding Artificial Intelligence
  7. Introduction to Data Science in Python

New Track:

  1. Introduction to Data Literacy
  2. Introduction to Data
  3. Data Governance Concepts
  4. Introduction to Data Ethics
  5. Data Management Concepts
  6. Understanding Artificial Intelligence
  7. Data Strategy

Removed Content

# Content ID Content Title Instructor Name
1 17602 Data Science for Business Datacamp
2 29847 Introduction to Google Sheets Datacamp
3 23080 Machine Learning for Business Datacamp
4 25814 Data-Driven decision-making for business Ted Kwartler
5 26720 Marketing analytics for business Sarah DeAtley
6 13371 Introduction to Data Science in Python Datacamp

 

Added Content

# Content ID Content Title Instructor Name
1 29478 Introduction to Data Literacy DataCamp
2 29830 Introduction to Data DataCamp
3 29911 Data Governance Concepts DataCamp
4 31939 Introduction to Data Ethics DataCamp
5 34147 Data Management Concepts DataCamp
6 35244 (not live yet) Data Strategy DataCamp

 

ChatGPT Fundamentals

Current Track:

  1. Introduction to ChatGPT
  2. Understanding Prompt Engineering

New Track:

  1. Introduction to ChatGPT
  2. Understanding Prompt Engineering
  3. Intermediate ChatGPT

Removed Content

N/A

Added Content

# Content ID Content Title Instructor Name
1 36814 Intermediate ChatGPT DataCamp

 

Project Deprecations

Projects with Replacements

# Project ID Project Title Replacement Project(s) Replacement ID(s)
1 10 Exploring the History of Lego Examining the History of Lego Sets 2378
2 20 Dr. Semmelweis and the Discovery of Handwashing (Python)(Guided) Dr. Semmelweis and the Importance of Handwashing (Python) 2526
3 166 Visualizing Inequalities in Life Expectancy Exploring Global Life Expectancy Trends 2079
4 435 Rise and Fall of Programming Languages (Guided) Analyze the Popularity of Programming Languages 2557
5 515 Functions for Food Price Forecasts (Guided) Food Price Forecasting with Functions 2559
6 538 Comparing Search Interest with Google Trends (Guided) Understanding Search Interest with Google Trends 2504
7 684 Analyzing TV Data Extracting TV Data Insights In progress
8 691 TV, Halftime Shows, and the Big Game Analyzing Super Bowl Viewership and Advertising 2531
9 981 Exploring the Evolution of Lego Examining the History of Lego Sets 2378
10 1008 Functions for Food Price Forecasts (Unguided) Food Price Forecasting with Functions 2559
11 1168 What and Where are the World’s Oldest Businesses (Guided)(SQL) Uncovering the World's Oldest Businesses (SQL) 2519
12 1174 Rise and Fall of Programming Languages (Unguided) Analyze the Popularity of Programming Languages 2557
13 1383 What and Where are the World’s Oldest Businesses (Guided)(Python) Uncovering the World's Oldest Businesses (Python) 2510
14 1441 Analyzing American Baby Name Trends Exploring Trends in American Baby Names In progress

 

Projects with Recommended Alternatives

# Project ID Project Title Recommended Alternative Alternative ID
1 76 A Network Analysis of Game of Thrones Social Network Analysis 2479
2 132 Recreating John Snow’s Ghost Map No replacement N/A
3 139 Level Difficulty in Candy Crush Saga Visualizing the History of Nobel Prize Winners 1890
4 184 Mobile Games A/B Testing with Cookie Cats Hypothesis Testing with Men’s and Women’s Soccer Matches 1611
5 449 Classify Song Genres from Audio Data No replacement N/A
6 496 Predict Taxi Fares with Random Forests Predict Energy Consumption 2387
7 504 Which Debts Are Worth the Bank’s Effort? Will this Customer Purchase your Product? 2470
8 619 The Android App Market on Google Play (Guided) Understanding Subscription Behaviors 2474
9 648 Find Movie Similarity from Plot Summaries Reveal Categories Found in Data 2472
10 695 Comparing Cosmetics by Ingredients No replacement N/A
11 727 Analyze Your Runkeeper Fitness Data No replacement N/A
12 738 Modeling the Volatility of US Bond Yields No replacement N/A
13 740 Disney Movies and Box Office Success Modeling Car Insurance Claim Outcomes 1645
14 760 Real-time Insights from Social Media Data  No replacement N/A
15 1197 The Android App Market on Google Play (Unguided)  Understanding Subscription Behaviors 2474
16 1234 Writing Functions for Product Analysis Data-Driven Product Management: Conducting a Market Analysis 1684