SENATOROVAI / Data-Science-For-Beginners-from-scratch-course
Data science for beginners involves learning to extract insights from data using statistics, programming (Python/R), and visualization. Key steps include data collection, cleaning, analysis, modeling, and communicating findings. Beginners should start with Python, basic math (linear algebra/calculus), and build projects to create a portfolio.
Why this job: name: beginners; topics: from scratch
Get started
No single install command. Read the steps in the README (opens in new tab)
- Maintenance
- Active
- Last commit today
- Stars
- 217
- +4 this week
- Licence
- MIT
- Allows business use
- Downloads for
- None listed
- No release files
- Latest version
- None yet
- No releases
- Built with
- Python
- 100% of the code
Is it looked after?
- Contributors
- 1
- Last 90 days
- Issues
- 89% closed
- 9 still open
- Pull requests
- 38 merged
- 24 waiting
- Releases
- None
- Never published
- Contributing guide (opens in new tab)
- No security policy
- No code of conduct
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| Moataz-Elmesmary / Data-Science-Roadmap | 4,420 | 11 months ago | MIT | No downloads |
More: languages, topics, project record and preview image
Languages
- Python 100%
Topics
- data-science
- mathematics
- python
- senatorov
- ai
- algebra
- calculus
- datascience
- datascience-machinelearning
- machine-learning
- probability
- statistics
Project record
- JobLists and guides
- StatusListed
- Commits601
- Forks164
- Watching2
- Stars in 28 days+11
- CreatedNov 5, 2024
- First seen by usNov 7, 2026
- CheckedNov 12, 2026