Learn to build, deploy, and fine-tune intelligent AI Agents using LangChain, OpenAI, GPT-2, Ollama, MCP Anthropic Agents
Welcome to “Build Powerful AI Agents: From LangChain to Local LLMs”, your all-in-one course to become a complete AI Agent Engineer. Whether you’re a developer, data scientist, or AI enthusiast, this course will guide you step-by-step through building intelligent, multimodal, and voice-based AI systems — from the cloud (OpenAI) to local environments (Ollama & MCP).
What you’ll learn
- Build AI agents step by step using LangChain.
- Understand hands on practice of fine-tuning large language models.
- Integrate external tools and APIs to enhance agent capabilities.
- Develop real-world AI workflows and deploy agents in under 30 minutes.
- Deploy Agents using Cloud Frameworks and utilize MCP Local Servers.
Course Content
- Introduction to MCP –> 3 lectures • 37min.
- Developing AI Agents with Ollama ( Local LLM’s ) –> 4 lectures • 1hr 12min.
- Developing AI Agents with Langchain & OpenAI –> 6 lectures • 1hr 21min.
- Introduction to Huggingface & GPT Models –> 4 lectures • 33min.
- Introduction to Pytorch –> 1 lecture • 15min.
- Introduction to LlamaIndex –> 1 lecture • 7min.
- Fine-Tuning LLMs Made Simple: From Concepts to Hands-On Implementation –> 3 lectures • 42min.
- Build & Deploy Local LLM’s Using Colab Notebook –> 1 lecture • 20min.
Requirements
Welcome to “Build Powerful AI Agents: From LangChain to Local LLMs”, your all-in-one course to become a complete AI Agent Engineer. Whether you’re a developer, data scientist, or AI enthusiast, this course will guide you step-by-step through building intelligent, multimodal, and voice-based AI systems — from the cloud (OpenAI) to local environments (Ollama & MCP).
By the end of this course, you’ll gain hands-on experience developing smart, interactive, and deployable AI agents that can think, talk, reason, and adapt — the same way top AI startups do it today.
What You’ll Learn
- Understand how LangChain Agents work and how to integrate them with OpenAI APIs.
- Build Voice-based Emotion and Wellness Companions using Whisper & TTS.
- Create Virtual AI Talking Agents and Copilot Systems that perform autonomous tasks.
- Implement RAG-powered assistants using LLaMA 3.1 and Pinecone.
- Learn the basics of PyTorch for deep learning and model training.
- Explore Hugging Face and GPT models for NLP and dataset customization.
- Understand MCP (Model Context Protocol) and use FastMCP to connect LLMs with databases.
- Master Fine-Tuning techniques and understand the difference between Fine-Tuning vs RAG.
- Deploy Local LLMs (like Gemma and Qwen) using Google Colab + Ngrok for free hosting.
- Hands-on Labs and Implementations
Enroll now and become the expert of Generative AI.