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Advanced ML Engineering with Python

Advanced ML Engineering with Python

intermediate4 levels14 stages75 lessons

This is the path structure only. Once you sign up, MICHi builds your own version, measures real mastery through review gateways and spaced repetition, and ends with a verifiable certificate.

Level 1 — Foundational Python for ML Engineering

  1. 1.Core Python for Data Science Refresher4 lessons
  2. 2.Numerical Computation with NumPy & Pandas5 lessons
  3. 3.Introduction to Machine Learning Workflows (Scikit-learn Project)6 lessons

Level 2 — Building Robust ML Models & Pipelines

  1. 1.Optimizing Model Performance with Advanced Scikit-learn4 lessons
  2. 2.Introduction to Deep Learning with TensorFlow/Keras5 lessons
  3. 3.Containerization for ML with Docker4 lessons
  4. 4.End-to-End ML Pipeline Development (Dockerized Model Project)6 lessons

Level 3 — Deployment, Monitoring & Scalability

  1. 1.ML Model Deployment with Flask/FastAPI5 lessons
  2. 2.Cloud ML Platforms (AWS Sagemaker/Azure ML)6 lessons
  3. 3.ML Model Monitoring & Observability5 lessons
  4. 4.Real-time Prediction Service Deployment Project7 lessons

Level 4 — Advanced MLOps & Production Readiness

  1. 1.ML Workflow Orchestration with Apache Airflow/Kubeflow6 lessons
  2. 2.Scalable Data Processing for ML (Spark/Dask Basics)5 lessons
  3. 3.Continuous Integration/Continuous Delivery (CI/CD) for ML Project7 lessons

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