Basics of Data Science

Your Data Science Notes PDF is ready! 🎉

Here's what's packed inside across 16 colour-coded chapters:

ChapterTopics Covered1–2What is Data Science + Lifecycle3–4Types of Data + Statistics Fundamentals5–6Central Tendency + Dispersion (with solved examples)7–8Probability Rules + Distributions9Linear Algebra (matrices, eigenvectors)10–12ML intro, Supervised & Unsupervised Learning13Model Evaluation (Accuracy, F1, ROC-AUC, RMSE)14Data Preprocessing pipeline15Python automation code examples (NumPy, Pandas, Sklearn)16Quick Revision — all formulas + career roadmap