Agentic AI Internals: Build an Agent from Scratch

<div>This course contains the use of artificial intelligence :)</div><div><br></div><div><span style="font-size: 1rem;">Please note that this is not a course for beginners. This course assumes that you have a background in software</span></div><div><br></div><div>engineering and are proficient in Python. I will be using Pycharm IDE but you can use any editor you'd like</div><div><br></div><div>since we only use basic feature of the IDE like debugging and running scripts .</div><div><br></div><div>Who this is for: Software developers, data scientists, and AI/ML engineers proficient in Python. This is not a beginner course.</div><div><span style="font-size: 1rem;"><br></span></div><div><span style="font-size: 1rem;">Welcome to AI Agents with LangChain. This course teaches you how AI agents actually work — then you build them from scratch.</span></div><div><span style="font-size: 1rem;"><br></span></div><div><span style="font-size: 1rem;">You'll go deep into agent internals: how LLMs make decisions, how function calling works, how prompts drive</span></div><div><br></div><div>agent behavior, and how to build&nbsp; agents with LangChain.</div><div><br></div><div>What you'll learn:</div><div><ul><li><span style="font-size: 1rem;">LLM and GenAI foundations</span></li><li><span style="font-size: 1rem;">Prompt engineering, Context engineering</span></li><li><span style="font-size: 1rem;">Tool calling and function calling</span></li><li><span style="font-size: 1rem;">Agent tracing with LangSmith</span></li><li><span style="font-size: 1rem;">Deep agents with LangGraph</span></li><li><span style="font-size: 1rem;">Open source models</span></li><li><span style="font-size: 1rem;">Output parsers and structured output</span></li></ul></div><div><span style="font-size: 1rem;">Everything is hands-on — real code, real projects. Uses PyCharm but any Python IDE works.</span></div><div><br></div><div>DISCLAIMERS</div><div><ul><li>Please note that this is not a course for beginners. This course assumes that you have a background in software engineering and are proficient in Python.</li><li>I will be using Pycharm IDE but you can use any editor you'd like since we only use basic feature of the IDE like debugging and running scripts.</li></ul></div>

What you'll learn:

• Become proficient in LangChain
• Have end to end working LangChain based generative AI agents
• Prompt Engineering Theory: Chain of Thought, ReAct, Few Shot prompting and understand how LangChain is build under the hood
• Context Engineering
• Understand how to navigate inside the LangChain opensource codebase
• Large Language Models theory for software engineers
• LangChain: Lots of chains Chains, Agents, DocumentLoader, TextSplitter, OutputParser, Memory
• RAG, Vectorestores/ Vector Databases (Pinecone, FAISS)
• Model Context Protocol (MCP)
• LangGraph