Here are the courses I’ve completed, currently taking, or plan to take:
🧠
Google 5-Day Gen AI Intensive Course
A comprehensive 5-day intensive covering foundational LLMs, prompt engineering, embeddings and vector stores, generative AI agents, domain-specific LLMs, and MLOps for Gen AI. Each day came with whitepapers, Kaggle notebooks, and companion podcast episodes. One of those courses that gives you a solid, structured foundation across the Gen AI landscape.
#InProgress
🎓
Stanford CME295: Transformers & LLMs
A 9-lecture university course covering transformer architecture, LLM training, tuning, reasoning, agentic LLMs, evaluation, and current trends. Having access to Stanford-level content on transformers and LLMs — from the architecture all the way to agentic applications — felt like a privilege. The depth and rigour here is something you don't easily find in shorter courses.
#InProgress
🤖
Multi AI Agent Systems with CrewAI
A hands-on course on building multi-agent systems — covering the 6 key components, agent creation, task definition, tools and cooperation, memory and guardrails. The practical projects (event planning, financial analysis, job application automation) made the concepts click. This was my first proper deep dive into AI agents and it set the foundation for everything that followed.
#Completed
🤖
Practical Multi AI Agents and Advanced Use Cases with crewAI
The follow-up to Multi AI Agent Systems — this one goes deeper into production-level use cases: automated project planning, project monitoring, lead qualification, support data analysis, and building agentic sales pipelines with CrewAI Flow. Loved seeing how agents can be orchestrated for real business workflows.
#InProgress
🔌
MCP: Build Rich-Context AI Apps with Anthropic
A 9-lesson course on the Model Context Protocol (MCP) — its architecture, client-server communication, tools, resources, and prompts. MCP is becoming the standard for connecting AI models to external data and tools, and this course helped me understand the protocol from fundamentals to production deployment.
#InProgress
⚡
Agent Skills with Anthropic
A 9-lesson course on agent skills — progressive disclosure, the distinction between skills vs. tools vs. MCP vs. subagents, and how to create custom skills. Understanding the layered architecture of how agents acquire and use capabilities was eye-opening.
#InProgress
🔗
Functions, Tools and Agents with LangChain
A 6-lesson course covering OpenAI functions, LangChain Expression Language (LCEL), function calling with Pydantic, tagging and extraction, tools routing and APIs, and functional conversation. A solid primer on the LangChain ecosystem and how to build tool-using agents.
#InProgress
🔧
How to Fine-tune LLMs with Unsloth
A comprehensive video guide on fine-tuning LLMs — covering LoRA, QLoRA, SFT, RLHF, GRPO, model saving, and deployment. The hands-on approach with actual code and implementations made the abstract concepts of fine-tuning much more tangible and practical.
#Completed
☁️
AWS Certification Plan
A multi-phase AWS certification strategy covering three certifications: AWS Certified Machine Learning Engineer - Associate, AWS Certified Solutions Architect - Associate, and a Professional or Data Engineer certification. Building a structured cloud foundation to complement the AI/ML skills.
#ToStart