Download
This project lays out a 12-week plan to go from basics to a portfolio-ready understanding of data science. It breaks the journey into clear stages: Python fundamentals, data wrangling, visualization, statistics, machine learning, and end-to-end projects. The schedule mixes learning and doing, encouraging you to build small deliverables each week—like notebooks, dashboards, and model demos—to reinforce skills. It also includes suggestions for datasets and problem domains so you aren’t stuck wondering what to analyze next. The plan is intentionally opinionated but flexible: you can swap resources while keeping the weekly objectives intact. By the end, you’re expected to have tangible artifacts to show employers or collaborators, not just notes and bookmarks.
Features
- Week-by-week syllabus from Python and pandas to modeling and deployment
- Balanced mix of lectures, readings, coding exercises, and mini-projects
- Guidance on finding datasets and framing problems with business value
- Recommended tooling stack for notebooks, visualization, and experimentation
- Portfolio focus with suggested project ideas and presentation tips
- Flexible resource substitutions while preserving the overall trajectory
Project Samples
