Free course
Online
12 weeks
~6 hours/week

LLM Engineering Essentials

Gain the skills to build LLM-powered services that work. Master LLM APIs and self-hosted LLMs as you code, experiment, and create a platform for custom AI-powered NPCs.
Sign up for updates:
1
Understand the fundamentals of LLM APIs and workflows to create a chatbot based on your favorite fantasy character
2
Learn to work with self-hosted LLMs, encoders, and vector stores, and build a RAG system
3
Explore monitoring tools like Prometheus and Grafana. Optimize and fine-tune your LLM-powered service

What you will learn

Prompting Strategies
Inference Parameters
LLM Workflows
Agents
Reasoning
RAG
Hugging Face Ecosystem
Inference Engines
Quantization
Evaluation
Monitoring
Fine-Tuning
Reinforcement Learning
Scaling
Move beyond tutorials.
Go further.
Sharpen your skills with real-world examples, carefully curated materials, and tasks designed to make learning both challenging and engaging.
Why choose this program?
Rich knowledge base, up-to-date materials, and practical tasks you can complete at your own pace.
Effective study plan that will help you go from basics to deployment.
Guidance and feedback for cohort participants — join Q&A meetings, gain AI insights, and connect with fellow students to share experiences.

Syllabus

Study advanced concepts. Apply your new knowledge right away.
Week 1. LLM Basics
Week 2. LLM Workflows
Week 3. Context
Week 4. Self-Served LLMs
Week 5. Optimization and Monitoring
Week 6. Fine-Tuning
Start learning for free
Complete practical tasks and deploy an NPC Factory
Enjoy our course project as a standalone, fun experience. Build a chatbot based on your favorite character, use RAG to add context, and develop a fully functional platform for serving smart, custom NPCs.

Who is this program for?

We designed this course for developers and engineers looking to advance their LLM skills and start building real-world, fully functional AI-powered services.
Especially suitable for:
Software Engineers
Data Scientists
Data Engineers
ML Engineers
Data Analysts
Technical Managers
Required skill
Machine learning & deep learning basics
You should be familiar with loss functions and metrics and have experience with neural networks.
Required skill
Coding skills
We expect students to know Python: assignments and coursework rely on this language.
Join us on GitHub
Explore the course materials, write code, solve tasks, and study in a familiar environment — at your own pace.
Get materials now
Designed for you by experts from academia and industry
Alexey Bukhtiyarov
NLP Team Lead at Ex-human
Alexey, an expert in DL and LLMs, leads an NLP team at an AI startup, with a background in distributed training and multi-GPU programming.
Stanislav Fedotov
AI Program Lead at Nebius Academy
With a rich background in arranging educational programs in the field of AI, Stanislav is deeply passionate about AI education.
Katya Nikitskaya
Data Scientist and researcher
Katya is an experienced Data Scientist with a strong background in machine learning, LLM and generative AI. She brings over 15 years of expertise in analytics and business intelligence, combining deep research capabilities with practical engineering skills.
Nikita Pavlichenko
Senior ML Engineer at JetBrains
Nikita Pavlichenko develops advanced code generation models. Previously, he researched LLM alignment and RLHF at Toloka.
Sergei Petrov
Machine Learning Engineer at Meta
Sergei obtained an Engineering MSc degree at Stanford University, his research was focused on Computer Vision applications for Earth Science.
Rod Rivera
AI Product Engineer, Professor of AI at ITAM, DevRel at Jentic
Rod is an AI educator and the founder of the AI Product Engineer community. With over 10 years of industry experience and a background in Machine Learning research, he’s passionate about helping people and organizations build AI skills and turn them into real-world value.
Sergei Skvortsov
ML Engineer at Nebius
Sergei is focusing on leveraging neural networks for inference tasks and optimizing algorithms for GPU performance.
Alex Umnov
Machine Learning Scientist at Booking.com
Alex is an ML scientist with experience in applied NLP. His previous work includes solving Computer Vision and Ranking tasks.
Join Our Community
Connect with fellow learners, ask questions, and share ideas
in our community. Stay in the loop with live session announcements, insider tips, and updates on all things AI.

For even more insights, subscribe to our newsletter — and never miss a beat in your LLM journey.
We’re passionate about AI education.
See what our students have to say:
Dina Karakash
Job title: Venture Partner and Head of AI & Research
Course: Intro to ML from an LLM Standpoint
Most students were already in the field, tackling real AI challenges — from building models and AI agents to applying flexible AI frameworks in specific industries. The lecturers were both researchers and practitioners deeply passionate about AI. This course went well beyond 36 hours of content.
Yael Hamrani
Job title: Data Science & Integration R&D Engineer
Course: Practical Generative AI
The course is practical, insightful, and the community aspect adds a lot of value. I’d recommend it to anyone looking to meaningfully expand their AI skill set.
Alexander Kazakov
Job title: OCR, Computer Vision, Machine Learning
Course: Practical Generative AI
I joined the Generative AI program to stay up to date with modern technologies, and I found the first module both informative and practical. The availability of experts for discussions was especially valuable, and the hands-on assignments, like extracting information from databases, were engaging. I’d recommend this program to colleagues in ML and text analysis - especially those new to neural networks.
Andi Mardinsyah
Job title: Data Scientist
Course: Practical Generative AI
I chose the Generative AI program from Nebius Academy because of its well-structured curriculum that balances theory and practice. The first module on Generative AI applications was extremely useful, especially with its hands-on coding approach. Despite my busy schedule, the short yet informative lectures made learning manageable. This program is a great fit for Data Scientists working with NLP and LLM, and I’d definitely recommend it to my colleagues.
Sridharman Jing Yao Thulasidas
Job title: Data Analyst
Course: Intro to ML from LLM standpoint
This course gave me a deeper understanding of RAG and agents, with real-world examples like simulating a patient’s life cycle in a hospital. The structured lessons and interactive format made learning engaging, while the Q&A sessions provided insights into industry challenges. Now, I feel more confident working on LLM-related projects.
Igor Samenko
Job title: DS, ML & DL Engineer
Course: Practical Generative AI
I really enjoy this course! The balance of new material, referenced articles, and technical depth makes it highly relevant for the coming years. The teaching team is outstanding—passionate experts delivering high-quality content. I appreciate the hands-on approach, from challenging quizzes to homework based on cutting-edge technology. The 'paperwatch' channel is a goldmine of hot topics, and I hope to keep access after the course. Highly recommend!
Semyon Abramov
Job title: Machine Learning Research Engineer
Course: Practical Generative AI
Excited to have completed the Practical Generative AI course by Nebius Academy! Over four months, I gained hands-on experience with LLMs, vision transformers, generative models, and efficient deep learning techniques. This program expanded my skills and deepened my understanding of Generative AI. Huge thanks to Stanislav Fedotov, Yana Vashkevich, and the entire team for an incredible learning experience!
Get better at LLMs by doing, not just taking notes
Sign up for updates:
FAQ
What does the LLM Engineering Essentials program cover?
Why is this course free?
How will I learn?
How do the LLM Engineering Essentials live sessions work?
Can I skip live sessions?
Can I access the materials before attending a live session?
What will I build?
What skills should I have before starting?
How long does the course take?
How do I get started?
LinkedIn
About Nebius
Dina Karakash
Job title: Venture Partner and Head of AI & Research
Course: Intro to ML from an LLM Standpoint

Most students were already in the field, tackling real AI challenges — from building models and AI agents to applying flexible AI frameworks in specific industries. The lecturers were both researchers and practitioners deeply passionate about AI. This course went well beyond 36 hours of content.

Yael Hamrani
Job title: Data Science & Integration R&D Engineer
Course: Practical Generative AI

The course is practical, insightful, and the community aspect adds a lot of value. I’d recommend it to anyone looking to meaningfully expand their AI skill set.

Alexander Kazakov
Job title: OCR, Computer Vision, Machine Learning
Course: Practical Generative AI

I joined the Generative AI program to stay up to date with modern technologies, and I found the first module both informative and practical. The availability of experts for discussions was especially valuable, and the hands-on assignments, like extracting information from databases, were engaging. I’d recommend this program to colleagues in ML and text analysis—especially those new to neural networks.

Andi Mardinsyah
Job title: Data Scientist
Course: Practical Generative AI

I chose the Generative AI program from Nebius Academy because of its well-structured curriculum that balances theory and practice. The first module on Generative AI applications was extremely useful, especially with its hands-on coding approach. Despite my busy schedule, the short yet informative lectures made learning manageable. This program is a great fit for Data Scientists working with NLP and LLM, and I’d definitely recommend it to my colleagues.

Sridharman Jing Yao Thulasidas
Job title: Data Analyst
Course: Intro to ML from LLM standpoint

This course gave me a deeper understanding of RAG and agents, with real-world examples like simulating a patient’s life cycle in a hospital. The structured lessons and interactive format made learning engaging, while the Q&A sessions provided insights into industry challenges. Now, I feel more confident working on LLM-related projects.

Igor Samenko
Job title: DS, ML & DL Engineer
Course: Practical Generative AI

I really enjoy this course! The balance of new material, referenced articles, and technical depth makes it highly relevant for the coming years. The teaching team is outstanding—passionate experts delivering high-quality content. I appreciate the hands-on approach, from challenging quizzes to homework based on cutting-edge technology. The 'paperwatch' channel is a goldmine of hot topics, and I hope to keep access after the course. Highly recommend!

Semyon Abramov
Job title: Machine Learning Research Engineer
Course: Practical Generative AI

Excited to have completed the Practical Generative AI course by Nebius Academy! Over four months, I gained hands-on experience with LLMs, vision transformers, generative models, and efficient deep learning techniques. This program expanded my skills and deepened my understanding of Generative AI. Huge thanks to Stanislav Fedotov, Yana Vashkevich, and the entire team for an incredible learning experience!