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10-Hour LLM Fundamentals

10h 30m 55s
English
Paid

Unlock the potential of large language models with our intensive course, "LLM Basics in 10 Hours". This comprehensive program is designed to help you understand and effectively use LLMs in real-world projects, enhancing your skills in AI-driven environments.

Course Overview

In this course, you will discover the best practices for utilizing different approaches such as prompting, Retrieval-Augmented Generation (RAG), fine-tuning, and employing agents. You'll learn the contexts in which these strategies are most effective and understand the rationale behind their success.

Build Your LLM Developer Toolkit

Equip yourself with a fundamental "LLM Developer Toolkit". This includes knowledge and skills in:

  • Customization and databases
  • Frameworks and fine-tuning
  • Quality assessment
  • Security measures

Through practical examples, we'll guide you in designing end-to-end workflows, integrating ChatGPT and other models into business processes, creating multi-step agents, and optimizing models for specific tasks and domains.

From Ideas to AI Products

Learn how to transform your ideas into AI products, progressing from initial prototypes to robust solutions. You'll explore modern techniques such as:

  • Distillation
  • Quantization
  • Reinforcement Learning from Human Feedback (RLHF)
  • Protection against prompt-hacking

Who Should Enroll?

This program is tailored for developers and IT specialists, but it is beneficial for anyone eager to master LLMs. From grasping their limitations to developing bespoke solutions, this course has you covered. No preliminary knowledge is required, although familiarity with Python could be advantageous.

About the Authors

Louis-François Bouchard

Louis-François Bouchard thumbnail

Louis-François Bouchard is a French-Canadian AI engineer and educator behind the What's AI newsletter and YouTube channel — one of the more accessible explainer sources on modern AI research. He is also the lead instructor for several courses on the Towards AI platform, where he teaches the production-engineering side of LLM applications.

His CourseFlix listing carries six Louis-François Bouchard courses spanning the applied AI track: Building LLMs for Production, 10-Hour LLM Fundamentals, Build Your First Product with LLMs / Prompting / RAG, Master AI for Work, Beginner Python Primer for AI Engineering, and the Agentic AI Engineering Course.

Material is paid and aimed at engineers picking up applied LLM work as a serious skill. For broader content, see CourseFlix's LLMs & Fundamentals, RAG, and AI Agents category pages.

Towards AI

Towards AI thumbnail

Towards AI is one of the larger AI-focused publishers on the open web — originally a Medium publication and now a multi-author content platform plus a paid course catalog focused on production LLM engineering. The brand has tracked the post-ChatGPT generative-AI wave from inside the field rather than from a generic SaaS-marketing perspective.

The CourseFlix listing reflects their applied focus: Building LLMs for Production, 10-Hour LLM Fundamentals, Build Your First Product with LLMs, Prompting, RAG, the Agentic AI Engineering Course, Beginner Python Primer for AI Engineering, and Master AI for Work. Material is paid and aimed at engineers who already know Python and want to ship production AI features rather than read a survey of the field.

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#1: 1. Foundational Knowledge and Using LLMs
All Course Lessons (6)
#Lesson TitleDurationAccess
1
1. Foundational Knowledge and Using LLMs Demo
01:39:50
2
2. Building on Top of LLMs
01:51:39
3
3. Evaluations
01:41:19
4
4. Orchestrating Agent-Based Solutions
01:50:27
5
5. Guardrails, Advanced Techniques, Optimizations and Monitoring
01:41:38
6
6. Re-training Models
01:46:02
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Frequently asked questions

What prior knowledge or skills are required before taking this course?
This course is tailored for developers and IT specialists, suggesting that a background in programming and a basic understanding of AI concepts would be beneficial. While the course does not explicitly state prerequisites, familiarity with AI-driven environments and basic programming skills could enhance your learning experience.
What kind of projects will I be able to work on after completing the course?
After completing the course, you'll be equipped to design end-to-end workflows and integrate models like ChatGPT into business processes. You'll also be able to create multi-step agents, optimize models for specific tasks, and transform ideas into AI products, progressing from initial prototypes to robust solutions.
How does this course compare in depth and scope to other LLM courses?
The course offers a focused 10-hour program covering foundational knowledge, advanced techniques, and practical applications. It includes topics like prompting, RAG, fine-tuning, and agent-based solutions, providing a comprehensive toolkit for real-world LLM applications. This scope positions it as a practical course aimed at immediate application in AI-driven environments.
What specific tools or platforms will I learn to use during the course?
You will learn to integrate models such as ChatGPT and explore frameworks for customization, databases, and fine-tuning. The course also covers advanced techniques like distillation, quantization, and reinforcement learning from human feedback (RLHF) to optimize and secure AI models.
What topics are not covered in this course?
The course does not cover introductory AI concepts or basic programming skills in depth, assuming some prior knowledge in these areas. It focuses primarily on practical applications and advanced techniques for LLMs, rather than foundational AI theory or non-LLM AI models.
How much time should I expect to dedicate to this course?
The course is designed to be completed in approximately 10 hours, making it a relatively short commitment. This time includes engaging with the lesson material, practical examples, and possibly some additional time for exercises and project work.
How can the skills learned in this course benefit my career in AI development?
The skills acquired in this course, such as designing workflows and integrating LLMs into business processes, will enhance your ability to develop AI-driven solutions. This expertise is valuable for careers in AI development, particularly in roles focused on deploying and optimizing language models in various industry contexts.