Week 02 — Machine Learning and Career Readiness

Week 02 turns the Week 01 foundation into practical machine learning workflows.

Roadmap

Day	Focus	Start
Day 01 Part 1	Machine Learning Basics	Agenda
Day 01 Part 2	Regression Algorithms	Agenda
Day 02 Part 1	Classification Algorithms	Agenda
Day 02 Part 2	Clustering Techniques	Agenda
Day 03 Part 1	Feature Engineering	Agenda
Day 03 Part 2	Model Evaluation	Agenda
Day 04 Part 1	Intro to Deep Learning	Agenda
Day 04 Part 2	NLP Basics	Agenda
Day 05 Part 1	End-to-End Mini Project	Agenda
Day 05 Part 2	Mock Interview and Resume Review	Agenda

How to Study Week 02

1. Keep Week 01 notes nearby, especially Pandas, EDA, statistics, and SQL.
2. For every model, write down the target, features, metric, and leakage risks.
3. Compare every real model against a baseline.
4. Prefer pipelines over loose preprocessing code.
5. End each section by explaining the model in plain English.

Final Outcome

By the end of Week 02, you should have:

• a working ML vocabulary
• regression and classification baselines
• clustering intuition
• feature engineering patterns
• evaluation discipline
• a mini project story
• interview-ready explanations