Understanding Large Language Models
Creator: Mike master August 30, 2026What You'll Learn
- Trace the end-to-end data flow through a transformer architecture from input tokens to output probabilities
- Calculate scaled dot-product attention scores using query, key, and value matrix operations
- Implement multi-head attention blocks to capture diverse contextual relationships across token sequences
- Compare the computational complexity and memory usage of standard attention mechanisms across varying context window sizes
- Explain the role of positional encodings in preserving sequence order within parallelized self-attention operations
About This Course
This intermediate course breaks down the foundational architecture powering modern large language models, taking you from high-level model structures to the mathematical mechanics of transformer networks. You will examine tokenization, vector embeddings, and the core structural layers that enable LLMs to process and generate coherent text. You will dissect self-attention and multi-head attention mechanisms step by step to see how models track contextual relationships across token sequences. By the end of the course, you will be able to trace data through a complete transformer pipeline and evaluate the computational tradeoffs of different attention designs.
Who this is for: This course is built for software engineers, data practitioners, and technical product builders who want a precise architectural understanding of LLMs. You will benefit most if you have basic familiarity with Python and fundamental linear algebra concepts like matrix multiplication.
Modules
01: Introduction to Large Language Models
8 min
01: Introduction to Large Language Models
8 min
Final Quiz
Covers all 1 modules. Pass with 80% or higher to complete the course.
New To YouVersity?
This course is built from real YouTube videos, structured into modules with quizzes and progress tracking. Original creators keep every view and every ad dollar — courses just send them focused, motivated viewers.
- Structured modules
- Free to enrol
- Progress saved across devices
- Quizzes after each section
Ready To Start?
Begin the first module now. No credit card needed
Before You Decide
Playlists don't have quizzes, don't track progress, don't pull videos from multiple channels into a sequence, and don't give you a certificate. A playlist is a list. This is a course.
The videos are still free. What costs money is the structure around them: modules in the right order, quizzes built from the content, progress that follows you across devices, and a certificate at the end. You could piece all of that together yourself. Or you could have it built in minutes.
They're yours. Permanently. Every certificate you earned stays dated, valid, and shareable whether you're still subscribed or not. Cancelling doesn't touch anything you've already completed.
Install it from the Chrome Web Store. When you're on any YouTube video, click the YouVersity icon to save it to your library. Once you've saved enough, turn your library into a structured course. It's a second way to create courses: instead of typing a topic, you hand-pick the videos yourself.
The opposite. Videos stay embedded on YouTube. Every view in a course is a real view on their channel with their ads. We send them focused, motivated viewers who actually watch to the end. Creators keep everything they already earn, plus new traffic.
Probably not. Most people take two or three. At $9 a month, even one course is worth it compared to buying individually. The 30 is a ceiling, not a homework assignment.
Related Courses
Learning Claude Code: Agentic Coding with VS Code
Learn how to use Claude Code, Anthropic's AI coding agent, directly inside VS Code. This course covers installing and setting up Claude Code, understanding agentic workflows, driving multi-step coding tasks with prompts, using the VS Code extension, managing context and memory, and practical tips for shipping real features with an AI pair programmer.
Mike M.
ChatGPT for Everyday Work
Put ChatGPT to work on the tasks that eat up your week, with no technical background required. Learn how to write prompts that get useful answers, draft emails and documents, summaries long material, and build simple, repeatable workflows. Finish saving hours every week and knowing exactly when to trust the output and when to check it.
Mistura A.
Vibe Coding For Beginners
"Vibe Coding for Beginners" introduces you to building software using AI where you focus on the big-picture ideas while AI handles the actual typing of the code.
Hannat S.