LLM Development from Scratch (Part 4: Lessons 31–41)
From generate function to Gradio UI — the final part, Lessons 31–41.
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Curriculum
Sections, lesson durations, and free previews
LLM Development from Scratch (Part 4: Lessons 31–41)
- 1Lesson 31: Merging the Notebook and Preparing for Release23 minAvailable after enrollment
- 2Lesson 32: Writing a Generate Function for the LLM23 minAvailable after enrollment
- 3Lesson 33: Building a Chatbot UI with Gradio — Part 123 minAvailable after enrollment
- 4Lesson 34: Building a Chatbot UI with Gradio — Part 234 minAvailable after enrollment
- 5Lesson 35: Moving from CPU to GPU and Batch Processing20 minAvailable after enrollment
- 6Lesson 36: Batch Processing and Padding27 minAvailable after enrollment
- 7Lesson 37: Batch Processing and Acceleration with MPS11 minAvailable after enrollment
- 8Lesson 38: What Are Temperature, Top-P and Top-K?29 minAvailable after enrollment
- 9Lesson 39: Coding Temperature, Top-P and Top-K21 minAvailable after enrollment
- 10Lesson 40: What Is Top-P (Nucleus) Sampling?19 minAvailable after enrollment
- 11Lesson 41: Enhancing the UI and Adding Parameter Controls15 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