awesome-learn-datascience
github.com/siboehm/awesome-learn-datascience ↗:chart_with_upwards_trend: Curated list of resources to help you get started with Data Science
Use this list with your AI agent
Add the Context Awesome MCP server to Claude, Cursor, or any MCP client, then ask:
"Show me various other helpful tools and resources resources from awesome-learn-datascience"
Installation instructions →What's inside
Common Algorithms and Procedures
- 9 important Data Science algorithms and their implementation
- Cross validation
Evaluate the performance of your algorithm/model.
- Feature engineering
Modifying the data to better model predictions.
- Model ensemble: Explanation
Combine multiple models into one for better performance.
- Scientific introduction to 10 important Data Science algorithms
- Supervised vs unsupervised learning
The two most common types of Machine Learning algorithms.
Data Science using Python
- Amazon AWSVarious other helpful tools and resources
Rent cloud servers for more timeconsuming calculations (r4.xlarge server is a good place to start).
- Anaconda Python distributionVarious other helpful tools and resources
Contains most of the important Python packages for Data Science.
- Coursera Applied Data ScienceGeneral
Online Course using Python that covers most of the relevant toolkits.
- DataCamp pandas foundationspandas
Paid course, but 30 free days upon account creation (enough to complete course).
- Downloading and running first Jupyter notebookJupyter Notebook
- Example notebook for data explorationJupyter Notebook
More advanced resources and lists
Data Science Challenges for Beginners
- Blood Donation Challenge
Predict if a donor will donate again.
- Titanic Challenge
Predict survival on the Titanic.
- Walkthrough: House prices challenge
Walkthrough through a simple challenge on house prices.
- Water Pump Challenge
Predict the operating condition of water pumps in Africa.
What is Data Science?
- Data Science for Business (Book)
An introduction to Data Science and its use as a business asset.
- Data Science Process: A Beginner’s Comprehensive Guide
Technical Skills for the Data Science: This emphasizes the practical skills needed throughout the data science process.
- Explanation of important vocabulary
Differentiation of Big Data, Machine Learning, Data Science.
- 'What is Data Science?' on Quora
Showing a sample of 37 resources. View the full list on GitHub →