Awesome Data Analysis collects more than 500 resources for data analysis and data science.
The Best Awesome DataScience Alternatives in 2026
Looking for something like Awesome DataScience? Here are 24 alternatives, ranked by how closely they match it on purpose, features and platforms. Of these, 6 are open source.
This Awesome DataScience repository collects learning material and resources about data science.
Top picks at a glance
Quick comparison
| # | Alternative | Pricing | Open source | Platforms |
|---|---|---|---|---|
| 1 | Awesome Data Analysis | — | Yes | — |
| 2 | Data Science Ipython Notebooks | — | Not stated | — |
| 3 | Codecademy's Data Science | — | Not stated | Web |
| 4 | Virgilio | — | Not stated | — |
| 5 | Coding Questions | — | Not stated | Web |
| 6 | Deep ML | — | Not stated | Web |
| 7 | Virgilio | — | Not stated | Web |
| 8 | ML YouTube Courses | — | Yes | — |
| 9 | ML Course Notes | — | Not stated | — |
| 10 | Lost at SQL | — | Not stated | Web |
All Awesome DataScience alternatives
Data Science Ipython Notebooks
github.com/donnemartin/data-science-ipython-no…Data Science IPython Notebooks collects notebooks about data science, including TensorFlow deep learning.
Codecademy's Data Science
codecademy.com/learn/paths/data-scienceCodecademy’s Machine Learning Specialist path covers Python, SQL, pandas, scikit-learn, Matplotlib, and TensorFlow.
Virgilio
github.com/virgili0/VirgilioAn open-source initiative, Virgilio guides learners through data science resources and skill development.
Coding Questions
platform.stratascratch.com/codingStrataScratch offers over 1,000 data science interview questions across SQL, Python, statistics, machine learning, and data projects.
Deep ML
deep-ml.comDeep-ML provides hands-on exercises in machine learning and data science fundamentals.
Virgilio
virgili0.github.io/VirgilioVirgilio organizes data science e-learning resources in a structured project overview.
A curated repository helps readers discover machine learning and AI courses published on YouTube.
ML Course Notes
github.com/dair-ai/ML-Course-NotesA collaborative collection shares course and lecture notes on machine learning, natural language processing, and AI.
Lost at SQL
lost-at-sql.therobinlord.comLost at SQL teaches SQL concepts through a text-based game designed for data scientists and marketers.
OSSU Data Science
github.com/ossu/data-scienceOSSU Data Science provides a free study path based on an undergraduate data science curriculum.
R for Data Science
r4ds.had.co.nzThe first edition of R for Data Science teaches data import, transformation, visualization, and modeling with R.
Awesome YouTubers collects channels that teach a range of subjects through video.
ML Visualized
ml-visualized.comMachine Learning Visualized organizes its material as a collection of visual learning resources in a repository.
Visualization.info
visualization.infoVisualization.info describes educational resources for data visualization, including lecture videos, tutorials, textbooks, and notes.
Algorithms Cheatsheet Resources collects reference material for programming and algorithms.
ML Engineering
github.com/stas00/ml-engineeringThis open book collects methods, tools, and instructions for training, fine-tuning, and running machine learning models.
The Zasper project describes an IDE for working with Jupyter notebooks.
rasbt/LLMs-from-scratch
github.com/rasbt/LLMs-from-scratchThis repository walks through implementing a ChatGPT like language model in PyTorch, step by step.
cs-video-courses
github.com/Developer-Y/cs-video-coursesThe cs-video-courses list links to computer science courses that include video lectures for learners.
Deep Learning Drizzle
deep-learning-drizzle.github.ioDeep Learning Drizzle collects readings and notes about deep learning for study.
Scipy Lectures
lectures.scientific-python.orgScientific Python Lectures is a set of learning materials about Python for scientific computing.
IAILab
iailab.kaist.ac.kr/teaching/deep-learningThe iAI KAIST page shares deep learning materials that visitors are permitted to use, modify, and distribute.
Jupyter notebooks implement and derive machine learning algorithms from first principles using NumPy.
Alternatives to similar tools
What is the best alternative to Awesome DataScience?
Are there open-source alternatives to Awesome DataScience?
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