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AI / LLM

LLM Bootcamp

Transformers, fine-tuning, RAG, and LLMOps.

🧠 LLM Boot Camp Curriculum

📘 Module 1: Foundations of Large Language Models

1. What is a Language Model?

  • Evolution from N-grams to Transformers
  • Why “large” matters in modern AI

2. Transformers 101

  • Self-attention mechanism
  • Positional encoding & architecture
  • Mini Transformer demo in PyTorch

📘 Module 2: Pre-trained LLMs – Under the Hood

3. Tokenization Deep Dive

  • BPE, WordPiece, SentencePiece
  • Tokenizer visualization & decoding
  • GPT, LLaMA, Falcon, Mistral
  • Model card reading and comparison

5. Embeddings & Representations

  • Sentence and word embeddings
  • Using OpenAI or Hugging Face APIs

📘 Module 3: Prompting & Fine-Tuning

6. Prompt Engineering Basics

  • Zero, one, few-shot prompting
  • Prompt hacks & real-world examples

7. Fine-Tuning vs LoRA

  • Why and when to fine-tune
  • Fine-tune with PEFT / LoRA on Hugging Face

8. RLHF (Reinforcement Learning from Human Feedback)

  • Overview of alignment techniques
  • Human feedback simulation demo

📘 Module 4: Building with LLMs

9. LangChain / LlamaIndex 101

  • Chains, memory, and agents
  • Building Q&A apps with RAG

10. LLM APIs in Production

  • OpenAI, Cohere, HuggingFace Inference
  • Handling rate limits, logging, observability

11. Chatbot + RAG Project

  • Ingest PDF/text
  • Add memory & tool use

📘 Module 5: Advanced Topics & Deployment

12. LLMOps: Serving & Scaling

  • FastAPI, vLLM, Hugging Face Spaces, Modal
  • Deploying local models with Ollama

13. Security, Bias & Ethics

  • Prompt injection attacks
  • Jailbreaks, red-teaming & safe responses

14. Build a Mini Language Model

  • Train from scratch on a toy dataset
  • Tokenization → model → sampling loop

🎓 Capstone Projects (Pick One)

  • ✅ Chatbot for documents (PDF, CSV)
  • ✅ Auto-tagging for customer support
  • ✅ Custom-trained LoRA chatbot
  • ✅ RAG-based search engine

🚀 Bonus Chapter: Becoming an LLM Engineer

  • Must-have skills & GitHub project ideas
  • Resume and interview tips
  • Building your AI portfolio

Built for developers, students, and tech teams ready to master LLMs in record time.