MLOps course

Topics:

1. MLOps introduction - dependency management, code quality, Git, FastAPI, Docker
2. Databases & file formats - PostgreSQL, DuckDB, Parquet
3. Data processing - Polars
4. Vector databases - pgvectorscale, SQLAlchemy, Milvus
5. Versioning - DVC, MLFlow
6. ML testing & data-centric AI - CleanLab, Giskard, Captum, SHAP
7. Model optimization for inference - PyTorch optimization, ONNX, ONNX Runtime
8. Monitoring & drift detection - Evidently, NannyML
9. Introduction to cloud computing - AWS services
10. Infrastructure as Code (IaC) - Terraform
11. Deployment & CI/CD - GitHub Actions
12. ML pipelines - Apache Airflow
13. LLMOps - vLLM, Model Context Protocol (MCP), guardrails