awesome-datascience
This repository is a comprehensive list of resources that structure the data science learning process. Algorithms offer a wide range of content, such as machine learning packages, educational materials, and community resources. It serves as a roadmap for theoretical and practical knowledge of solving real-world problems.
AW
academic · Analytics & Business Intelligence
STARS30.3K
FORKS6.7K
COMMITS1.4K
CONTRIBUTORS310
VERSIONv2026.09.09.1
UPDATED3 days ago
Data ScienceMakine ÖğrenmesiEducationDeep LearningMIT
Common commercial products in this category: Tableau, Power BI, Looker
What can it do?
- You can follow the basic concepts and work steps that need to be learned in the field of data science.
- You can access technical resources on machine learning algorithms and deep learning libraries.
- You can explore tools, data sets, and community channels that you can use in data science projects.
Verified against README · Oct 26, 2026 · source
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