Full syllabus

Beginner

Understand the Career First

  1. What Is Machine Learning?
  2. Why Does ML Engineering Exist As A Job?
  3. Where Is ML Actually Used?
  4. What Does an ML Engineer Actually Do, Day To Day?
  5. How Does A Real ML System Work, End To End?

Python for ML

  1. NumPy & Pandas
  2. Statistics & Probability for ML

Classical ML Foundations

  1. Linear & Logistic Regression
  2. Decision Trees & Ensembles

Intermediate

Deep Learning Foundations

  1. Neural Networks from Scratch
  2. CNNs & Computer Vision

Advanced

MLOps & Deployment

  1. Model Serving & APIs
  2. Monitoring & Model Drift