SCHOOLWHOOL CLASSROOM · ADVANCEDLLMs &
LLMs &
Generative AI Course
Build real applications with large language models, not just prompts.
Explore the course Included in Early Access 25% off for the waitlist
5 modules 13 lessonsAdvanced Your own paceJob-ready Ends in a portfolio project
YOUR NEXT LEARNING CHAPTER
Lessons being recordedA little theory. A lot of discovery.
COURSE PREVIEW
This track is being recorded.
Explore the full outline below. Join the Early Access waitlist to get every track, and 25% off at launch.
EARLY ACCESS · COMING SOONSchoolWhool classroomLearn something that stays with you.
BUILT FOR THE CURIOUSUnderstand the why.
Understand the why.
Then build the how.
Learn to build with large language models: prompting, LLM APIs, tool use, RAG, evaluation, LoRA fine-tuning, AI agents and deployment.
What you’ll learn
- Explain how LLMs are trained and how they generate text.
- Build RAG pipelines over your own documents.
- Fine-tune a model with LoRA.
- Ship and evaluate an LLM application or AI agent.
Before you start
Comfort with Python. The NLP course helps, but the track explains what it relies on.
Part of SchoolWhool Early Access.Get every track, plus your AI job agent
Early Access includes all six course tracks and the AI Job Agent. Join the waitlist and get 25% off when it opens. No payment now.
Questions about this course
What does an LLM engineer do?
They build products on large language models: retrieval, prompting, tool use, evaluation, fine-tuning and deployment.
Does the course cover RAG and AI agents?
Yes. Retrieval-augmented generation has its own module, and the last module covers agents and production.