LLM Development from Scratch (Part 1: Lessons 0–10)
Part 1 of the from-scratch LLM journey — from tokenisers to embeddings, Lessons 0–10.
Secure checkout · PayTR · Lifetime access
Curriculum
Sections, lesson durations, and free previews
LLM Development from Scratch (Part 1: Lessons 0–10)
- 1Lesson 0: LLM Development from Scratch — Introduction13 minAvailable after enrollment
- 2Lesson 1: Core LLM Terminology, Key Papers and Resources26 minAvailable after enrollment
- 3Lesson 2: Setup and Tools for LLM Development16 minAvailable after enrollment
- 4Lesson 3: Building a Tokenizer from Scratch in Python26 minAvailable after enrollment
- 5Lesson 4: Using Open-Source Tokenizers19 minAvailable after enrollment
- 6Lesson 5: Building a Subword Tokenizer from Scratch25 minAvailable after enrollment
- 7Lesson 6: Building a BPE Tokenizer with SentencePiece and Uploading to Hugging Face15 minAvailable after enrollment
- 8Lesson 7: Context Length and Dataset Preparation24 minAvailable after enrollment
- 9Lesson 8: Creating a DataLoader with PyTorch30 minAvailable after enrollment
- 10Lesson 9: Embedding Layers and Semantic Representation25 minAvailable after enrollment
- 11Lesson 10: The Link Between Vocabulary and Embeddings33 minAvailable after enrollment
🔍 What you will find in this course:
✅ Core concepts such as tokenisation, embeddings and attention
✅ Line-by-line code explanations
✅ Jupyter Notebooks runnable in Google Colab
✅ 3D visualisations and animated explanations
✅ Training a small GPT model and building its interface
✅ Quizzes, assignments and interactive learning
✅ Open-source files and community support
🧠 Who is this for?
• Students developing skills in artificial intelligence
• Engineers, statisticians and researchers
• Anyone who wants to understand LLMs in theory and practice
Interested in this course?
Click the button below to enroll and start learning.
Secure checkout · PayTR · Lifetime access