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Large Language Models (LLMs)
Understand how LLMs work, from transformers and tokenization to fine-tuning and evaluation. Build practical intuition through 1-on-1 Zoom sessions.
Beginner
Intermediate
Advanced
Your learning roadmap
Course topics by level
Move from strong foundations to confident, practical application with a curriculum adapted to your goals.
Beginner
LLM Overview
- What LLMs are and how they are used
- Common models and capabilities
- Strengths and limitations
Core Concepts
- Tokens and tokenization
- Embeddings and context windows
- Next-token prediction intuition
Intermediate
Transformers Basics
- Attention mechanism overview
- Encoder / decoder ideas
- Why transformers scale well
Using LLMs Practically
- Working with model APIs
- Temperature, top-p, and output control
- Evaluating answers for quality
Advanced
Training & Adaptation
- Pretraining vs fine-tuning
- Instruction tuning concepts
- When to fine-tune vs prompt
Safety & Best Practices
- Hallucinations and grounding
- Privacy and data handling basics
- Responsible LLM usage
Personal learning, practical results
Turn this roadmap into real skills.
Tell us what you want to achieve and we’ll shape a focused learning plan around your level, pace, and goals.
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