From Beginner to Advanced LLM Developer
Build Your First Scalable Product with LLMs, Prompting, RAG, Fine-Tuning, and Agents!
Master the skills top companies need and build your own advanced LLM MVP with real-world applications.
From initial concept to deployment, you’ll have hands-on experience building a real-world LLM product. This could become a portfolio project that gives you a competitive edge in the job market, a Minimum Viable Product for a startup idea, or a Proof of Concept for a new product at your company.
Build the portfolio, gain the expertise, and walk into your next interview with the confidence that you can create, deploy, and manage AI solutions at scale.
Bring LLMs into your company to increase efficiency, automate tasks, or create new product lines—all with the knowledge you gain here.
“This is the most comprehensive...to date on building LLM applications, and helps learners understand everything from fundamentals to the simple-to-advanced building blocks of constructing LLM applications. The application topics include prompting, RAG, agents, fine-tuning, and deployment - all essential topics in an AI Engineer's toolkit.”
Jerry Liu, Co-founder and CEO of LlamaIndex“A truly wonderful resource that develops understanding of LLMs from the ground up, from theory to code and modern frameworks. Grounds your knowledge in research trends and frameworks that develop your intuition around what's coming. Highly recommend.”
-Pete Huang, Co-founder of The Neuron“An incredible survey of all the real-world problems one encounters when trying to productionize an LLM, as well as multiple solutions to each roadblock. Highly recommend this!”
Nick Singh, Founder of DataLemur.com & Author of Ace the Data Science Interview“A comprehensive and well-rounded resource that covers all the fundamentals of LLMs with a well-struck balance between theory and code[…]”
Tina Huang, Founder of Lonely Octopus, YouTuber, Ex-Meta“It covers the foundational aspects of LLMs as well as advanced use-cases like finetuning LLMs, Retrieval Augmented Generation and Agents. This will be valuable to anyone looking to dive into the field quickly and efficiently.”
Jeremy Pinto, Senior Applied Research Scientist at MilaHands-on Guide on LLMs, Prompting, RAG, Fine-tuning, and Tool Use
Step-by-Step Instructions to Build and Deploy a Full LLM Project—including our very own AI Tutor chatbot
Practical Code Projects and Read to Run Colab Notebooks
Certification Upon Completion with Your Own Working LLM RAG Project
Community Access for Ongoing Learning and Support
This certification is for engineers, executives, and enthusiasts eager to pivot into LLMs.
From Beginner to Advanced LLM Developer | The Towards AI Academy
FREE PREVIEWCourse Introduction and Scope: Why Become an LLM Developer?
FREE PREVIEWSyllabus In-Depth
FREE PREVIEWCourse Logistics and Tools Guide
FREE PREVIEWWhy Prompt Engineering, RAG, Tools, and Fine-tuning?
Understanding Large Language Models without Math or Code
Understanding LLMs Part 2: New Kind of Intelligence, New Kind of Stupidity
Introduction to Part 1: Core LLM Skills via Building our RAG AI Tutor
Introduction to LLMs and how to use via API
Limitations and Weaknesses of LLMs
Choosing your LLM; Metrics. Benchmarks. Closed or Open-source
What is Prompting? Talking with AI Models...
Prompting 101
What is Prompt Injection? Can you Hack a Prompt?
Building our AI Tutor System Prompt. Introducing Prompt Injection and Hacking
Evaluating and Iterating Prompts
What is RAG?
RAG 101
Building an OpenAI API chatbot without RAG
Building your Knowledge Base for RAG
Building a basic RAG pipeline from scratch
Build an OpenAI GPT with our AI blog data
Basic RAG with LlamaIndex
How vector DBs work and when to use one
Using a Vector Database
Improving Data Sources and Prompts
RAG Evaluations
Evaluating your RAG Pipeline
Security, Privacy & Cost; Comparing 5 key ways to access LLMs
Using Llama 3.1 70B on Together.ai and comparing RAG performance
Multimodal LLMs and Their Role in RAG Pipelines
How to Select the Right Embedding Model for Your Use Case?
Scraping Data from Websites
Scraping via API with Firecrawl
Perplexity Web API
Web Search API
Structuring Your Data: OpenAI Structured JSON Outputs
Parsing Data with LlamaParse
Choosing Data Sources and Building our AI Tutor Dataset
Through 60 lessons, you'll learn core LLM development concepts. From Data Collection and Parsing to Prompt Engineering, Fine-Tuning and building and deploying a full Advanced RAG pipeline with tools like OpenAI, LlamaIndex, and Gradio. The focus is entirely hands-on, ensuring you gain real-world coding experience as we add complexity and layers to your AI product.
Through 15 lessons, you'll explore a variety of tools like LLM agents, diffusion models, and APIs that can be integrated into your projects. We will also give our thoughts on the economics of the LLM ecosystem and help you choose the right niche and business strategy for building your own LLM Pipeline. This section is about thinking beyond the AI Tutor and planning custom AI applications that align with your personal or professional goals.
You’ll bring everything together by building and submitting your own LLM + RAG project. Whether it’s a variation of the AI tutor or a completely new idea, this final project will be your proof of mastery. We’ll review your project and certify your skills, helping you showcase your expertise in building real-world AI applications.
To truly maximize the learning experience, a technical foundation is essential for this course due to the hands-on nature of the projects.
Intermediate Python knowledge
Basic knowledge of GitHub
Necessary libraries for code implementations
Compatible device to setup a coding environment
At least 40 hours to gain the full benefit of the course
Yes
Yes, you will receive a Towards AI certificate upon completion.
Yes, there are three ways to receive a discount on our courses. If you're a student, we offer a 50% discount on all courses. Additionally, if you've previously purchased our book or another course, you're eligible for a discount. We also provide a bundle discount for groups of two or more people. For further details or to claim your discount, please email Louis-François at [email protected] for a follow-up.
You’ll work on building your own AI tutor, create RAG pipelines, and build your advanced LLM MVP. Each project is designed to solve real-world problems, ensuring you gain practical, hands-on experience.
This course is for developers, engineers, and professionals who want to fast-track their AI careers or bring LLMs into their company. Whether you're aiming to land an AI engineer role or upskill to implement cutting-edge AI solutions, this course is designed for you.
Unlike many theoretical courses, this one is fully hands-on, project-based, and focused on the skills top companies are hiring for right now. We guide you through every step, ensuring you not only understand the concepts but can also apply them immediately.
For every referral you provide, you’ll gain access to our exclusive eBook. If you refer three or more people, we’ll send you a physical copy of our book as a thank you! Additionally, we have an affiliate program for individuals with an audience. By joining, you can earn commissions for every successful referral made through your unique affiliate link. Please email Louis-François at [email protected] with proof of referral.
Yes! We offer both course bundles and custom training solutions tailored specifically for companies. For more information on company packages or to discuss a customized training plan, reach out to Louis at [email protected].
If, after completing the first section, you feel the course isn’t right for you, we’ll provide a 100% refund within 30 days—no hassle, no worries.