Architect multi-agent teams with CrewAI, advanced RAG with Pinecone, and fine-tune open-source models locally with Ollama.
Master the frontiers of Applied Artificial Intelligence. Over 12 intensive weeks, software engineers and AI innovators learn to design multi-agent autonomous systems using CrewAI & LangChain, build high-accuracy Retrieval-Augmented Generation (RAG) pipelines with Pinecone, and fine-tune open-source LLMs locally using Ollama, Hugging Face, and LoRA quantization.
Master the frontiers of Applied Artificial Intelligence. Over 12 intensive weeks, software engineers and AI innovators learn to design multi-agent autonomous systems using CrewAI & LangChain, build high-accuracy Retrieval-Augmented Generation (RAG) pipelines with Pinecone, and fine-tune open-source LLMs locally using Ollama, Hugging Face, and LoRA quantization.
Software engineers, tech leads, AI developers, and system architects building production autonomous AI solutions.
Architect autonomous multi-agent teams, deploy enterprise RAG pipelines, and fine-tune open-source LLMs locally.
Understand vector indexing, dense embeddings, hybrid search scoring, and document context window optimization.
Build cooperative AI agent teams using CrewAI, define custom tools, role personas, and automated delegation chains.
Implement parent-child retrievers, re-ranking models, vector databases in Pinecone, and LangSmith evaluation metrics.
Fine-tune open-source LLMs (Llama 3, Mistral) using LoRA/QLoRA on Hugging Face, apply GGUF quantization, and deploy locally via Ollama.
Vector embedding models, chunking strategies, Pinecone vector stores, hybrid search, RAG fusion, and context compression.
Multi-agent frameworks, CrewAI task delegation, custom python tool binding, memory stores, and autonomous decision routing.
Hugging Face datasets, PEFT/LoRA fine-tuning, 4-bit quantization, GGUF conversion, running local Ollama endpoints, and FastAPI microservices.
Architect a CrewAI agent squad consisting of a Researcher, Analyst, and Writer agent that autonomously creates in-depth market reports.
Fine-tune an open-source Llama model on private company data and deploy it behind a secure local FastAPI server.
Solid understanding of Python functions, classes, and REST API basics is required for this course.
No! We show you how to leverage Google Colab GPUs for fine-tuning labs and run quantized models locally on standard hardware.
AI Agent Engineering is currently the highest-demanded niche in software development with top industry compensation packages.
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