Data Scientist: Complete Course Book
Data Scientist: Complete Course Book by Chetna Sharma is a 142-page handwritten PDF in 22 chapters. It covers the CRISP-DM lifecycle, data preparation and feature engineering, the linear algebra, calculus and probability behind ML, supervised and unsupervised learning, deep learning, GenAI, deployment and MLOps.
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What is data science, and what do these notes teach?
Data science uses statistics, programming and machine learning to build models that predict or explain outcomes from data. This course book follows a full project lifecycle, from framing the problem to deploying and monitoring a model.
What is inside
- 22 chapters, 142 illustrated A4 pages
- The CRISP-DM lifecycle, data preparation and feature engineering
- Linear algebra, calculus and probability for machine learning
- Supervised and unsupervised ML with step-by-step intuition
- Deep learning and generative AI foundations
- Model deployment and MLOps
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Who it is for
- Data analysts moving up to machine learning
- Students taking data science or ML courses
- Self-learners who want the maths explained visually
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