Most people who want to move into data don't need another list of resources. They need a path that starts where they are, tells them what to do next, and proves what they learned. That is what the free academy at magnimindacademy.com/academy is built to do.
What is inside
The free tier is called Data Science Essentials. It follows the first half of our full-stack curriculum, the same order we teach in the mentor-led programs:
- Foundations — what data science actually is, the tools, and how a project moves from question to answer.
- Python for data — variables to pandas, with a browser-based Python runner so you never install anything.
- SQL and analytics — joins, aggregations, window functions and the queries analysts write every day.
- Statistics and math — distributions, sampling, hypothesis tests and just enough linear algebra to read a model.
- Data exploration — cleaning, visualising and telling the story in the data.
- Machine learning basics — regression, classification, evaluation and the mistakes that leak into production.
Every lesson is short (10–25 minutes), ends with a practice task, and most have a graded assignment. The Python runner and the AI tutor sit right inside the lesson, so you can try the code, break it, and ask why.
Quizzes, badges and the certificate
Each module ends with a quiz. You need 70% to pass, and every answer comes back with an explanation, right or wrong. Pass a module and you earn its badge. Three badges unlock the Data Science Essentials certificate, a PDF with a public verification code that recruiters can check at /academy/verify.
A realistic ten-week plan
The dashboard has a pace planner, but here is the plan most working learners follow:
- Weeks 1–2: Foundations and Python. Aim for four lessons a week.
- Weeks 3–4: SQL. Do every practice query twice — once with hints, once without.
- Weeks 5–6: Statistics and math. Slow down here; this is where interviews probe.
- Weeks 7–8: Data exploration. Finish the graded assignments — they become portfolio material.
- Weeks 9–10: Machine learning basics, then the remaining quizzes and your certificate.
Five to six hours a week is enough. The dashboard shows what you finished, what is next, and how your quiz scores are trending, so you never have to reconstruct where you left off.
What comes after
If you want the second half of the curriculum — deep learning, NLP, MLOps, big data and experimentation — the Applied Data Science & AI track adds those modules, graded assignments with a full grade book, and a verified final exam. And if you want a mentor, real client projects and interview practice, that is what the Mentor-Led Internship is for.
Sign in with Google or email at /academy and start with Foundations. It is free, and it stays free.