NEW Agentic AI Engineering Guide: The 6 mistakes breaking production agents and how to fix them.
Industry Leaders on the Course
“This is the most comprehensive textbook 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.”
“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.”
“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!”
“A comprehensive and well-rounded resource that covers all the fundamentals of LLMs with a well-struck balance between theory and code[…]”
“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.”
The Gaps Between Developer and AI Engineer
We close them with real projects, proven frameworks, and the exact skills companies are hiring for.
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Software Engineering ≠ LLM Engineering
Learn to engineer around probabilistic systemsThis course teaches you to design reliable systems on top of unpredictable models, using prompt engineering, context engineering, and RAG to control what the model knows, and fine-tuning to control how it behaves.
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The Talent Gap Is Your Opportunity
Get trained in exactly what the role demandsThe AI engineering role is only 2-3 years old; the window to get in early is still open. Master the full stack: from choosing the right models and architectures to evaluating, optimizing, and deploying production-grade AI systems at scale.
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Demos ≠ Production Systems
Ship real, deployable LLM productsMove beyond notebooks and build something that gives you a competitive edge in the job market, launches your startup idea, or drives a new product at your company.
Build Your First LLM Product This Week
• A fully deployed LLM application, production-ready
• Gain portfolio-ready skills with certification
• Master fundamentals that outlast trends
Hear From the Engineers Who Took the Leap
Love it
Paul Iusztin
If you are interested in AI Engineering, this course is one of the few within the AI space worth your time and money. I have closely worked with the Towards AI team and totally vouch for their deep expertise, passion and educational skills. Also, ...
Read MoreIf you are interested in AI Engineering, this course is one of the few within the AI space worth your time and money. I have closely worked with the Towards AI team and totally vouch for their deep expertise, passion and educational skills. Also, love their approach to teaching engineering, where instead of many small projects, they walk you through a larger project, from end-to-end, reflecting what you actually encounter within the industry.
Read LessExcellent course
Martin Ballard
The course covers an immense amount of information. I feel like I really learned a ton about working with LLMs and how to develop and deploy my own applications.
The course covers an immense amount of information. I feel like I really learned a ton about working with LLMs and how to develop and deploy my own applications.
Read LessFrom Beginner to Advanced LLM Developer
Boonchiat Tan
"This course is fantastic! The content is well-curated, making it easier to learn the techniques quickly. Great job! Thanks again!"
"This course is fantastic! The content is well-curated, making it easier to learn the techniques quickly. Great job! Thanks again!"
Read LessHighly Recommend This Course
Farhad Dalirani
This course is highly valuable. You can learn a lot about different critical aspects of LLMs and RAG. Before taking it, I used to wander through endless resources, most of which were, in fact, low quality. The course is fantastic, and I highly rec...
Read MoreThis course is highly valuable. You can learn a lot about different critical aspects of LLMs and RAG. Before taking it, I used to wander through endless resources, most of which were, in fact, low quality. The course is fantastic, and I highly recommend it to everyone. One of the things I love about the course is that it’s not just a series of video lectures; it includes many code notebooks with detailed explanations, allowing you to learn by coding and engaging, which is the best approach. In order to create a good generative AI app with LLMs, a person should be knowledgeable about various topics, such as effective prompting, choosing the right tools, data collection and curation, working with various modalities, vector databases, query engines, building RAG systems for different needs, creating agents with tools like internet search, understanding various cloud and API providers, working with local LLMs, evaluation methods, deploying efficiently using techniques like quantization and caching, among many other related topics. This course covers ALL of them. Moreover, the support of creators have been great, I noticed a few minor issues in the code examples, which were fixed when I pointed them out!
Read LessUnderstanding the basics of LLMs without math
Tiamiyu Hamzat
To be honest, this course is completely different from other courses on LLM I have seen out there. This course is fully packed with lots of knowledge, advanced techniques and skills to build a successful LLM project. I am glad I did not hesitate t...
Read MoreTo be honest, this course is completely different from other courses on LLM I have seen out there. This course is fully packed with lots of knowledge, advanced techniques and skills to build a successful LLM project. I am glad I did not hesitate to purchase this course.
Read Lessgreat course
Danny Vaks
The most comprehensive LLM / AI engineering course out there
Carlo Casorzo
I am amazed about the thoroughness and clarity of this TowardsAI course. It really covers the whole spectrum of LLM engineering end-to-end, starting from the very basics and reaching a very deep level. 100% recommended
I am amazed about the thoroughness and clarity of this TowardsAI course. It really covers the whole spectrum of LLM engineering end-to-end, starting from the very basics and reaching a very deep level. 100% recommended
Read LessExceptional course with in-depth resources
Vitor Ramos
This course stands out for its exceptional structure and quality of references that truly deepen the learning experience. The materials are carefully curated and provide a comprehensive foundation that encourages further exploration of the topics ...
Read MoreThis course stands out for its exceptional structure and quality of references that truly deepen the learning experience. The materials are carefully curated and provide a comprehensive foundation that encourages further exploration of the topics covered. Each reference not only supports the lessons but also enriches understanding, making complex concepts accessible and engaging. The overall course design is well-organized, ensuring that learners can easily navigate through the content and achieve their learning goals. Highly recommended for anyone looking to expand their knowledge with quality resources.
Read LessA must have book and training course for LLM Developers and Data Science Students
Badshah Mukherjee
I find the book and training videos a must-have for anyone interested in learning about LLMs and developing a career in them. I have recommended them to my students in Data Science and AI to accelerate their understanding and build MVPs.
I find the book and training videos a must-have for anyone interested in learning about LLMs and developing a career in them. I have recommended them to my students in Data Science and AI to accelerate their understanding and build MVPs.
Read LessTruly practical from engineering perspective
Victor Palomares
Great tutorial. It is building concepts from the ground up. From an engineering perspective going through the code and running the examples helps to grasp a deep understanding. I find this is very practical and equips you with the tooling to face ...
Read MoreGreat tutorial. It is building concepts from the ground up. From an engineering perspective going through the code and running the examples helps to grasp a deep understanding. I find this is very practical and equips you with the tooling to face real world use cases.
Read LessComplete and practical
Mikhail Rybalchenko
I really enjoy the course. It's super comprehensive and strikes a good balance between theory and hands-on. It also way more affordable than many other options out there. What makes the course stand out is that it doesn't stop at the basics, it ac...
Read MoreI really enjoy the course. It's super comprehensive and strikes a good balance between theory and hands-on. It also way more affordable than many other options out there. What makes the course stand out is that it doesn't stop at the basics, it actually goes into design, deployment and optimization. A great choice to master AI engineering.
Read LessWho Is This Course For?
This certification is for software developers, machine learning engineers, data scientists or computer science and AI students to rapidly convert to an LLM Developer role and start building.
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The Developer Going All-In on AI: Ready to make AI your primary skill set. Build a portfolio, earn certification, and walk into high-demand LLM and AI engineering roles with proof you can deliver.
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The Engineer Leading AI at Their Company: You see AI transforming your industry. Gain the hands-on experience to lead initiatives, deploy real solutions, and drive innovation from the inside.
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The Developer With a Product Idea: You have an idea and the technical chops to build it. Turn it into a deployed, production-grade LLM application, all within 50+ hours of focused learning.
Course Curriculum
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From Beginner to Advanced LLM Developer | The Towards AI Academy
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Course Introduction and Logistics
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Syllabus In-Depth
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How to use LLMs via API
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An LLM Developer’s Role is to Address AI’s Weaknesses and Increase its Capabilities
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Why Prompt Engineering, RAG, Tools, and Fine-tuning?
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Understanding AI and Large Language Models without Math or Code
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Alien Intelligence Leads to Unintuitive Mistakes
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Course Tools Guide
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Part 1: Section Overview: Building Our RAG AI Tutor; Introduction to Using LLMs
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To use a LLM or to not use it?
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Choosing your LLM Part 1: Open vs Closed Source and Key Comparison Metrics
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Choosing your LLM Part 2: Key Benchmarks and Leaderboards
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Choosing your LLM Part 3: The Leading Open and Closed LLMs Today
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What is Prompting? Talking with AI Models...
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Prompting 101
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What is Prompt Injection? Can you Hack a Prompt?
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Building our AI Tutor System Prompt. Introducing Prompt Injection and Hacking
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Evaluating and Iterating Prompts
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Quiz
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Part 1: Section Overview: Building Our RAG AI Tutor; Using Basic RAG for Our Project
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What is RAG?
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RAG 101
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Building your Knowledge Base for RAG
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Building a basic RAG pipeline from scratch
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Build an OpenAI GPT with our AI blog data
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Quiz
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Part 1: Section Overview: Building Our RAG AI Tutor; Developing a RAG AI Tutor With LLamaIndex
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Basic RAG with LlamaIndex
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How vector DBs work and when to use one
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Using a Vector Database
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Improving Data Sources and Prompts
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RAG Evaluations
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Evaluating your RAG Pipeline
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Quiz
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Part 1: Section Overview: Building Our RAG AI Tutor; Using Other LLMs and Embedding Models
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Security, Privacy & Cost; Comparing 5 key ways to access LLMs
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Using Llama 3.1 70B on Together.ai and comparing RAG performance
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Ollama Tutorial: Running Deepseek Distill Locally
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Multimodal LLMs and Their Role in RAG Pipelines
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How to Select the Right Embedding Model for Your Use Case?
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Quiz
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Part 1: Section Overview: Building Our RAG AI Tutor; Collecting, Filtering, and Cleaning Data for RAG and LLM Pipelines
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Scraping Data from Websites
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Scraping via API with Firecrawl
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Perplexity Web API
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Web Search API
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Structuring Your Data: OpenAI Structured JSON Outputs
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Parsing Data with LlamaParse
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Choosing Data Sources and Building our AI Tutor Dataset
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Quiz
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Course Highlights
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$1000$349 - 92 Lessons
- Monthly Payment Plan Option
Risk-Free Learning: 30-Day Money-Back Guarantee
How It Works
Project-based learning designed for working professionals—self-paced with live instructor support.
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Self-Paced + Live Introductory Cohort Calls: Learn on your schedule with lifetime access. Join introductory cohort calls with instructors and fellow course takers.
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Learn by Building: Hands-on projects from day one. Build a production LLM system from scratch, not toy examples or follow-along tutorials.
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Active Discord Community: Get unstuck fast. Connect with fellow builders, share progress, and collaborate on projects in an active engineering community.
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Certificate Upon Completion: Prove you built and deployed production AI. Graduate with certification backed by two real systems—portfolio-ready proof you ship.
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Lifetime Access + Updates: All current content plus future updates as AI evolves. Your investment stays valuable.
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Money-Back Guarantee: 30-day full refund, no questions asked. Risk-free enrollment.
Course Prerequisite
To truly maximize the learning experience, a technical foundation is essential for this course due to the hands-on nature of the projects.
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Intermediate Python knowledge
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Basic knowledge of GitHub
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Necessary libraries for code implementations
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Compatible device to setup a coding environment
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At least 50 hours to gain the full benefit of the course
FAQ
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Will I get a certificate upon completion?
Yes, you will receive a Towards AI certificate upon completion.
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What projects will I work on?
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.
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What are the course prerequisites?
Intermediate Python, basic GitHub knowledge, and a device you can set up a coding environment on. No prior AI or LLM experience needed.
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When was this course created? Is it still up to date?
The course was originally launched in 2025, but we update it every single week with new lessons, tools, and techniques as the AI landscape evolves. You’re not just buying a static course—you’re getting a living resource designed to keep you ahead.
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How is this course different from other AI courses?
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.
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How does this course compare to your "Agentic AI Engineering" course?
The Agents course is a deep dive into building production-grade autonomous systems. Full Stack AI Engineering is broader. You build a complete LLM product from data collection to RAG, fine-tuning, deployment, and business positioning, with agents as one component of the stack. If Agents is about mastering autonomy, Full Stack is about mastering the full AI product lifecycle.
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Do you have a referral or affiliate program?
Yes. Towards AI offers an Affiliate Program and Referral Program, enabling you to earn money (up to $70 per course & $180 for a bundle) and free access to our courses by promoting our top courses and the "Building LLMs for Production" eBook. Check the 'Affiliate' page linked in the header.
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Can I get a discount?
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.
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Can I take this course within my company?
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].
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