CF

LLM Fundamentals

1h 34m 14s
English
Paid

LLM Fundamentals is a 9-lesson 1 hour 34 minutes self-paced course by Zen van Riel. The course "Fundamentals of Large Language Models (LLM)" is a practical introduction to modern artificial intelligence technologies with a focus on working with large language models.

Course facts

Lessons
9
Duration
1 hour 34 minutes
Level
All levels
Language
English
Updated
Instructor
Zen van Riel
Price
Premium
The course "Fundamentals of Large Language Models (LLM)" is a practical introduction to modern artificial intelligence technologies with a focus on working with large language models. During the training, you will create a full-fledged question-answer service for PDF documents that operates locally on your computer. This is one of the most in-demand application scenarios for LLM, widely used in modern SaaS products. The course does not require deep knowledge in the field of AI and does not assume the availability of expensive equipment—all solutions run on an ordinary machine.

What You Will Learn

The course combines practice and basic theory necessary for informed work with AI:
  • What artificial intelligence is and how it is defined in different fields
  • The fundamentals of machine learning and its key approaches (supervised/unsupervised learning)
  • The differences between classical ML and generative AI
  • The concept of narrow AI and artificial general intelligence (AGI)
  • How large language models work at a conceptual level
  • Why LLMs are capable of generating text and appear "creative"

Practical Part

The main focus of the course is on the practical use of LLM:
  • Working with ready-made language models without the need for training them
  • Using APIs and local models
  • Building a system that:
    • accepts PDF documents
    • analyzes their content
    • answers user questions

Who This Course Is For

  • Developers beginning to work with AI
  • Analysts and data specialists
  • Technical enthusiasts without a deep mathematical background
  • Anyone who wants to apply LLM for solving real-world tasks

Outcome

After completing the course, you will:
  • Understand how large language models are structured and operate
  • Learn to apply them in real scenarios
  • Create your own local AI service for working with documents
  • Gain a foundation for further advancement in AI and machine learning

Who teaches LLM Fundamentals? Zen van Riel

Zen van Riel thumbnail

I am focused on creating AI systems that truly work in production, rather than remaining at the demo level.

As a software engineer, I work on scaling real AI solutions in production at GitHub, and I also teach developers how to adapt to the future by practically implementing artificial intelligence.

Besides my main work, I am developing AI Native Engineer — my YouTube channel and community, where I share applied AI development skills.

My experience:

  • Over 5 years of developing and implementing cloud solutions
  • Deep expertise in LLMs, cloud architecture, and full-stack AI systems
  • Experience in creating and scaling AI products

I am convinced that the best engineers use AI not only as a tool to accelerate development but also as a foundation for creating new features and AI-native platforms that solve real problems.

What lessons are included in LLM Fundamentals?

This is a demo lesson (10:00 remaining)

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#1: 001 Machine Learning & AI 101
All Course Lessons (9)
#Lesson TitleDurationAccess
1
001 Machine Learning & AI 101 Demo
08:02
2
002 Option 2 - Codespace
09:12
3
003 Running AI on just your CPU
16:16
4
004 Python Pair Programming - Processing AI responses
21:41
5
005 Lecture on embeddings & AI search
06:44
6
006 Inject any data into your AI (RAG)
09:18
7
007 Pair Programming - Python REST API
10:31
8
008 Implementing the PDF Q&A Server
11:55
9
009 What's next
00:35
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Frequently asked questions

What prerequisites are needed to enroll in the course?
The course is designed for developers, analysts, and technical enthusiasts who are starting to work with AI. It does not require deep knowledge in AI or access to expensive equipment, as all solutions can be executed on an ordinary computer.
What practical skills will I gain from this course?
You will learn to build a question-answer service for PDF documents that operates locally. The course covers how to work with ready-made language models using APIs and local models without needing to train them, making it applicable for developers and analysts interested in AI applications.
Who is the target audience for this course?
The course is aimed at developers beginning to work with AI, analysts, data specialists, and technical enthusiasts who are interested in understanding and working with large language models and AI technologies.
How does this course compare in depth to other AI courses?
This course offers a practical introduction to AI with a focus on large language models. It provides foundational knowledge in machine learning and AI concepts but does not delve into deep technical details or require building models from scratch, unlike more advanced courses.
What specific tools or platforms will be used in the course?
The course involves using Python for pair programming and building a REST API. You will also work with embeddings and AI search, as well as implement a PDF Q&A server, all of which can be run on a standard computer without specialized hardware.
What topics are not covered in this course?
The course does not cover the deep technical aspects of training large language models from scratch, nor does it require or teach the use of advanced AI hardware. Instead, it focuses on practical applications using existing models.
How much time should I expect to commit to this course?
The course comprises 9 lessons, but the total runtime is not specified. You should expect to spend additional time on practical exercises and projects, particularly when building and testing the PDF Q&A system.