AI Agents Course
A Practical Deep Dive Into Memory Optimization for Agentic Systems (Part B)
AI Agents Crash Course—Part 16 (with implementation).
Archive
Latest
MLOps/LLMOps Course
Foundations of AI Engineering and LLMs
LLMOps Part 1: An overview of AI engineering and LLMOps, and the core dimensions that define modern AI systems.
LLM and Fine-tuning
A Practical Guide to Integrate Evaluation and Observability into LLM Apps
A comprehensive guide to Opik, an open-source LLM evaluation and observability framework.
MLOps/LLMOps Course
CI/CD Workflows
MLOps Part 18: A hands-on guide to CI/CD in MLOps with DVC, Docker, GitHub Actions, and GitOps-based Kubernetes delivery on Amazon EKS.
MLOps/LLMOps Course
Monitoring and Observability: Practical Tooling with Evidently, Prometheus, and Grafana
MLOps Part 17: ML monitoring in practice with Evidently, Prometheus and Grafana, stitched into a FastAPI inference service with drift reports, metrics scraping, and dashboards.
AI Agents Course
A Practical Deep Dive Into Memory Optimization for Agentic Systems (Part A)
AI Agents Crash Course—Part 15 (with implementation).
LLMs
Verbalized Sampling in LLMs
...explained with usage.
MLOps/LLMOps Course
Monitoring and Observability: Core Fundamentals
MLOps Part 16: A comprehensive overview of drift detection using statistical techniques, and how logging and observability keep ML systems healthy.
