MLOps & Model Deployment

CI/CD, monitoring, production ML

Author: AI Learning Club Team · Difficulty: Advanced · Duration: 2 hr 10 min · Modules: 25

Modules

1. Introduction to MLOps (5 min)
2. CI/CD Pipelines for Machine Learning (5 min)
3. Version Control for ML Models (5 min)
4. Feature Engineering and Feature Stores (5 min)
5. Model Training and Hyperparameter Tuning (5 min)
6. Model Registry and Model Serving (5 min)
7. Monitoring Model Performance (5 min)
8. Drift Detection in ML Models (5 min)
9. A/B Testing for Machine Learning (5 min)
10. Introduction to Kubeflow (5 min)
11. Kubeflow Pipelines (5 min)
12. Kubeflow for Model Training and Serving (5 min)
13. Introduction to Amazon SageMaker (5 min)
14. SageMaker for Model Training (5 min)
15. SageMaker for Model Deployment (5 min)
16. SageMaker Experiments and Hyperparameter Tuning (5 min)
17. SageMaker Feature Store (5 min)
18. SageMaker Model Monitoring (5 min)
19. SageMaker Endpoints and Inference (5 min)
20. Advanced Topics in MLOps (5 min)
21. Case Studies in MLOps (5 min)
22. Best Practices for MLOps (5 min)
23. MLOps in Production (5 min)
24. Future Trends in MLOps (5 min)
25. Resources & References (2 min)

Frequently Asked Questions

Related Courses

• Local LLM Architecture — Advanced
• Quantization Engineering — Advanced
• Production Inference — Advanced
• LLM Fine-Tuning — LoRA, QLoRA, PEFT, Instruction Tuning, RLHF, DPO, Evaluation — Advanced

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