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Post *🚀 Complete Roadmap to learn AI Fundamentals*

1 July 2026
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Coding Courses
*🚀 Complete Roadmap to learn AI Fundamentals* AI isn't just about using basic tools. To build real-world AI applications, you need to understand the fundamentals first and then learn the right tools. Here's a complete roadmap: *🎯 Phase 1: AI Fundamentals* ✅ What is Artificial Intelligence? ✅ Types of AI ANI, AGI, ASI ✅ Machine Learning vs Deep Learning vs Generative AI ✅ Supervised, Unsupervised & Reinforcement Learning ✅ Neural Networks Basics ✅ Large Language Models LLMs ✅ Tokens & Context Windows ✅ Embeddings ✅ Vector Databases ✅ Prompt Engineering ✅ RAG Retrieval-Augmented Generation ✅ AI Agents ✅ Fine-Tuning ✅ AI Safety & Responsible AI *🎯 Phase 2: Essential Programming Skills* ✅ Python ✅ SQL ✅ Git & GitHub ✅ REST APIs ✅ JSON ✅ FastAPI *🎯 Phase 3: Core AI Libraries* ✅ NumPy ✅ Pandas ✅ Scikit-learn ✅ PyTorch ✅ Transformers *🎯 Phase 4: Generative AI Tools* ✅ OpenAI API ✅ Hugging Face ✅ Ollama ✅ LangChain ✅ LangGraph ✅ LlamaIndex ✅ CrewAI ✅ AutoGen *🎯 Phase 5: Vector Databases* ✅ ChromaDB ✅ Pinecone ✅ Weaviate ✅ FAISS *🎯 Phase 6: AI App Development* ✅ Streamlit ✅ Gradio ✅ FastAPI ✅ Docker ✅ Redis ✅ PostgreSQL *🎯 Phase 7: AI Automation Tools* ✅ n8n ✅ Flowise ✅ Dify ✅ Make ✅ Zapier *🎯 Phase 8: Deployment & MLOps* ✅ Docker ✅ GitHub Actions ✅ MLflow ✅ Weights & Biases ✅ AWS / Azure / Google Cloud *🎯 Phase 9: Build Real Projects* ✅ AI Chatbot ✅ PDF Chat with RAG ✅ AI Coding Assistant ✅ Customer Support Bot ✅ Resume Analyzer ✅ Research Assistant ✅ Multi-Agent AI System ✅ Enterprise Knowledge Assistant
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