Popular
4.5
Beginner
2h
Updated 1 week ago
Essentials of Large Language Models: A Beginner’s Journey
Learn how large language models work, from inference and training to prompting, embeddings, and RAG. Build practical skills to apply LLMs effectively in real-world language applications.
In this course, you will learn how large language models work, what they are capable of, and where they are best applied. You will start with an introduction to LLM fundamentals, covering core components, basic architecture, model types, capabilities, limitations, and ethical considerations.
You will then explore the inference and training journeys of LLMs. This includes how text is processed through tokenization, embeddings, positional encodings, and attention to produce outputs, as well as how models are trained for next-token prediction at scale.
Finally, you will learn how to build with LLMs using a developer-focused toolkit. Topics include prompting, embeddings for semantic search, retrieval-augmented generation (RAG), tool and function calling, evaluation, and production considerations. By the end of this course, you will understand how LLMs actually work and apply them effectively in language-focused applications.
In this course, you will learn how large language models work, what they are capable of, and where they are best applied. You wi...Show More
WHAT YOU'LL LEARN
An understanding of language models and large language models, including their capabilities, applications, and limitations
Familiarity with the inference journey of an LLM, including tokenization, embeddings, positional encodings, and attention mechanisms
Working knowledge of how LLMs are trained for next-token prediction, including pretraining at scale and assistant alignment concepts
Working knowledge of the developer toolkit for building with LLMs, including prompting, embeddings for semantic search, RAG, and tools/function calling
Hands-on experience choosing when to prompt, use RAG, or fine-tune, and evaluating outputs with basic guardrails for production use
An understanding of language models and large language models, including their capabilities, applications, and limitations
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TAKEAWAY SKILLS
Content
1.
Course Overview
2 Lessons
Get familiar with large language models, their applications, and ethical considerations in AI.
2.
The Inference Journey
7 Lessons
Learn about advanced LLM fundamentals, components, types, capabilities, examples, and limitations.
3.
The Training Journey
3 Lessons
Understand how the model is trained for next-token prediction and the four key steps it takes to get better at the process.
4.
Building with LLMs: The Developer’s Toolkit
6 Lessons
Master effective prompt engineering, embeddings, and RAG for advanced LLM applications.
Certificate of Completion
Showcase your accomplishment by sharing your certificate of completion.
Complete more lessons to unlock your certificate
Developed by MAANG Engineers
Trusted by 2.9 million developers working at companies
"Very good insight about overall AI evaluation and sample model training."
Ramesh Perla
Senior Software Engineer @ Microsoft
"I thought this course was a great general overview of LLMs that introduced the main concepts and context of LLMs within the world of AI, how they work at a high level, and how their performance is measured."
Jorge Astorga
AI Technical Program Manager @ Cruise
"These are high-quality courses. Trust me the price is worth it for the content quality. Educative came at the right time in my career. I'm understanding topics better than with any book or online video tutorial I've done. Truly made for developers. Thanks"
Anthony Walker
@_webarchitect_
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