How Large Language Models Work: Foundations, Training, and Applications
Intermediate20 hours13 sections53 lessonsRated 4.8 out of 5 from 12 ratings
Follow text through a language model, then study how training, retrieval, tools, and evaluation shape an application. Numerical examples and text, image, audio, and video cases connect model mechanics with system design decisions.
What you will be able to do
- Follow text through tokenization, embeddings, attention, and decoding with numerical examples.
- Distinguish pretraining, instruction tuning, and preference-based post-training.
- Compare prompting, retrieval, tool calling, and fine-tuning for an application.
- Choose task-based evaluations and guardrails for language-model features.
Who this course is for
Engineers and data scientists who want to understand how language models work before designing LLM features or answering generative AI questions.
Helpful to know first
- Basic Python; comfort with vectors and probabilities helps with the numerical examples.
Course content
13 sections 53 lessons 20 hours
Define what a language model predicts and how it fits into an application. Review the Python background and learning goals for the course.
Locked sections open with Premium.Upgrade to Premium
Rate this course
Rated 4.8 out of 5 from 12 ratingsTell us how useful this course was. You can update your rating later.
Loading your rating...
Course rating
Rated 4.8 out of 5 from 12 ratings
- 5 stars: 9 ratings
- 4 stars: 3 ratings
- 3 stars: 0 ratings
- 2 stars: 0 ratings
- 1 star: 0 ratings