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Neither did any real understanding of\nwhy a chatbot suddenly \"knows\" your PDF, or how an AI agent decides which\ntool to pick, or what actually happens when you type `docker run` and an LLM\nstarts answering questions on a server somewhere in `us-east-1`.\n\n23 hours, 70 lectures, and a *lot* of `pip install` errors later — here's the\nproof of work as a student who took the course (not an instructor — that\ncredit goes to Siddhardhan S and Aditya Sharma). Every folder below is a\nrabbit hole I went down, survived, and turned into something that actually\nruns.\n\nIf you're learning this stuff too: clone it, break it, rebuild it. That's\nkind of the whole point.\n\n<br>\n\n## 🗺️ The Journey (a.k.a. Repo Structure)\n\n| Stage | Module | What happens here |\n|:---:|---|---|\n| 🌱 | [`01-genai-foundations`](./01-genai-foundations) | Where \"AI\" stops being a buzzword — LLMs, Transformers, attention, demystified |\n| 🔌 | [`02-accessing-llms`](./02-accessing-llms) | Talking to OpenAI, Gemini, Groq & Ollama without writing the same code 4 times |\n| ✍️ | [`03-prompt-engineering`](./03-prompt-engineering) | The art of asking nicely — zero-shot vs few-shot, side by side |\n| 💬 | [`04-genai-chatbots`](./04-genai-chatbots) | Giving the LLM a memory and a face (Streamlit UI included) |\n| 📚 | [`05-rag`](./05-rag) | Teaching an LLM to answer from *your* documents, not just its training data |\n| 🕵️ | [`06-ai-agents`](./06-ai-agents) | LLMs that don't just talk — they *do* things, using PydanticAI, AutoGen & CrewAI |\n| 🚀 | [`07-llm-deployment`](./07-llm-deployment) | Taking it off my laptop — Docker, EC2, vLLM, RunPod |\n| 🔗 | [`08-mcp`](./08-mcp) | The protocol that lets any agent use any tool — no more custom glue code |\n| 🏆 | [`09-capstone-projects`](./09-capstone-projects) | Three real apps where everything above finally clicks together |\n\nEvery module has a `notes.md` (the \"wait, why does this work?\" answers) and\nactual runnable code — not just theory.\n\n<details>\n<summary>📁 Prefer a literal file tree? Click here.</summary>\n\n```\ngenai-rag-agents-deployment/\n├── README.md\n├── LICENSE\n├── requirements.txt\n├── .env.example\n├── .gitignore\n│\n├── 01-genai-foundations/\n│   └── notes.md\n│\n├── 02-accessing-llms/\n│   ├── notes.md\n│   └── access_llms_example.py\n│\n├── 03-prompt-engineering/\n│   ├── notes.md\n│   └── prompt_templates.py\n│\n├── 04-genai-chatbots/\n│   ├── notes.md\n│   └── chatbot_streamlit.py\n│\n├── 05-rag/\n│   ├── notes.md\n│   └── rag_pipeline_langchain.py\n│\n├── 06-ai-agents/\n│   ├── notes.md\n│   └── agent_example.py\n│\n├── 07-llm-deployment/\n│   ├── notes.md\n│   ├── deploy_fastapi.py\n│   └── Dockerfile\n│\n├── 08-mcp/\n│   ├── notes.md\n│   └── mcp_server_example.py\n│\n├── 09-capstone-projects/\n│   ├── convopro/\n│   │   └── README.md\n│   ├── studypal/\n│   │   └── README.md\n│   └── astrarag/\n│       └── README.md\n│\n└── assets/\n    └── certificate/\n        └── certificate.pdf\n```\n\n</details>\n\n<br>\n\n## 🧰 What's Under the Hood\n\n<div align=\"center\">\n\n| 🧠 Brains | 🕵️ Agents | 🗃️ Memory | 🎨 Face | 🚀 Ships It |\n|:---:|:---:|:---:|:---:|:---:|\n| LangChain | PydanticAI | Chroma | Streamlit | Docker |\n| LlamaIndex | AutoGen | — | — | AWS EC2 |\n| — | CrewAI | — | — | vLLM / RunPod |\n\n</div>\n\n<br>\n\n## ⚡ Try It Yourself\n\n```bash\ngit clone https://github.com/<your-username>/genai-rag-agents-deployment.git\ncd genai-rag-agents-deployment\n\npython -m venv venv && source venv/bin/activate    # Windows: venv\\Scripts\\activate\npip install -r requirements.txt\ncp .env.example .env       # drop your API key in here\n```\n\nThen pick a rabbit hole:\n\n```bash\npython 05-rag/rag_pipeline_langchain.py        # ask questions, get grounded answers\npython 06-ai-agents/agent_example.py           # watch an agent reason step by step\nstreamlit run 04-genai-chatbots/chatbot_streamlit.py   # chat with memory, in the browser\nuvicorn 07-llm-deployment.deploy_fastapi:app --reload  # your own AI, as an API\n```\n\n<br>\n\n## 🏆 The Capstones — Where It All Comes Together\n\n| Project | The Pitch |\n|---|---|\n| 💬 [**ConvoPro**](./09-capstone-projects/convopro) | Your own private ChatGPT — no OpenAI dashboard, no data leaving your server |\n| 📖 [**StudyPal**](./09-capstone-projects/studypal) | Dump your notes in, ask it anything — an AI that actually studied *your* syllabus |\n| 🤖 [**AstraRAG**](./09-capstone-projects/astrarag) | The final boss: an agent that knows *when* to search your docs, not just how |\n\n<br>\n\n## 🎓 Proof It Happened\n\n| | |\n|---|---|\n| **Course** | Complete Generative AI Course: RAG, AI Agents & Deployment |\n| **Instructors** | Siddhardhan S|\n| **Completed by** | *Aditya Sharma* |\n| **Completed on** | September 8, 2026 |\n| **Damage** | 23 hours · 70 lectures · more coffee than I'd like to admit |\n\n📄 [Certificate PDF](./assets/certificate.pdf) &nbsp;•&nbsp; 🔗 [Verify Online](ude.my/UC-2f827bf7-355e-4afe-8333-224ada998cd4)\n\n<br>\n\n## 📜 License\n\nMIT — see [LICENSE](./LICENSE). Fork it, remix it, learn from it. That's the deal.\n\n---\n\n<div align=\"center\">\n\n**If this saved you an hour of Googling \"why does my RAG pipeline hallucinate,\" drop a ⭐.**\n\n*Built one confused `print()` statement at a time.*\n\n</div>\n","readmeExcerpt":"<div align=\"center\"> 🤖 From \"What is a Transformer?\" to Deploying AI Agents on AWS *A 23-hour deep dive into Generative AI — documented, coded, and shipped.* <br> $1 $1 $1 $1 $1 $1 $1 **📄 $1** &nbsp;•&nbsp; **🔗 $1** </div> <br> 👋 So, what's the story here? A few weeks ago this repo didn't exist. 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