AI-Bootcamp and learn-ai-engineering
These are complementary learning resources that together provide structured bootcamp training (A) alongside a curated collection of free learning materials (B) for building foundational AI engineering knowledge.
About AI-Bootcamp
curiousily/AI-Bootcamp
Self-paced bootcamp on Generative AI. Tutorials on ML fundamentals, Ollama, LLMs, RAGs, LangChain, LangGraph, Fine-tuning, DSPy & AI Agents (CrewAI), (Using ChatGPT, gpt-oss, Claude, Qwen, Gemma, Llama, Gemini)
The curriculum spans three progressive tracks: foundational ML engineering (Python, math, PyTorch), production systems (data pipelines with DVC, experiment tracking with MLflow, cloud deployment via AWS), and LLM-native applications (local inference with Ollama, retrieval-augmented generation, agentic workflows). Content integrates hands-on Jupyter notebooks with video tutorials and Discord community support, emphasizing reproducible, production-ready implementations across the full AI stack from training to deployment.
About learn-ai-engineering
ashishps1/learn-ai-engineering
Learn AI and LLMs from scratch using free resources
Organized curriculum spanning mathematical foundations through production deployment, covering machine learning frameworks (scikit-learn, XGBoost), deep learning platforms (TensorFlow, PyTorch), and modern LLM ecosystems including LangChain, LlamaIndex, and Ollama. Includes specialized tracks for computer vision, NLP, reinforcement learning, and agentic AI, plus practical guides for prompt engineering, RAG systems, and MLOps tools like Streamlit and MLflow.
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