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Become an AI-Powered Engineer
A series of comprehensive mini-courses 
on AI-assisted programming
LLM Engineering Essentials
Designed for professionals seeking skills to launch their own LLM-powered projects
Machine Learning Essentials for Coders
Students learn the ML basics at their own pace
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AI-Powered Data Science
An intensive data course held at the Tel Aviv University campus
Intro to ML from an LLM standpoint
Ideal for those based in London and eager to explore applications of LLMs
Why Nebius Academy
Educational programs
Online
Become an AI-Powered EngineerLLM Engineering EssentialsMachine Learning Essentials for Coders
In-person
AI-Powered Data ScienceIntro to ML from an LLM standpoint
For Business
Contact us
Start Learning
Free Nebius Academy course
Intro to ML from an LLM standpoint
In-person in London
14 weeks
3 hours a week
From industry experts
Applications are closed
You can leave your contact details so we can notify you about the next enrollment.
With guidance from experienced professionals, learn applications of large language models, get a grasp on machine learning methodology, and find out what’s inside ML models and how to benefit from them.
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This course is best suited for
Software engineers and developers
Deepen your knowledge to get a chance to move into AI/ML Engineer roles.
Data scientists
Master ML and LLMs to explore the opportunities the field offers.
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Study & exercise to apply new concepts
Up-to-date theory
Our instructors are here to answer all your questions. After each lecture, there will be a discussion to clarify and examine the course content in detail.
Practice
Home assignments won’t be graded, but our experts will talk them through in class.
In-person sessions
Join us at a convenient space in London (11 Cavendish Square, Chandos St, London W1G 9EB).
What will you learn?
This free course covers the basics of machine learning (ML), focusing on large language models (LLMs).
Skills you'll gain:
Creating, comparing, and using ML models in real-world situations
Leveraging a broad range of ML architectures: from linear models to transformers
Getting value from LLMs for your projects
Curriculum
Nov 5th — Feb 11th
1.
What is ML and how LLMs bring so much value
2.
Comparing models: LLM zoo and ML metrics
3.
What’s on top of an LLM: logits and linear models
4
How do we actually train ML models: gradient descent
5.
Geometry vs Semantics: from metric classification to Retrieval-Augmented Generation (RAG)
6.
Understanding neural networks
7.
Fine-tuning a pre-trained model
8.
Neural networks for sequences
9.
Attention and transformers
10.
Decoder-only transformers and how to train an LLM
11.
Intro to LLMOps: deploying an LLM, quantization, LoRA
12.
Architectural design choices that shape today’s LLM landscape
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Our instructors are industry experts
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Stanislav Fedotov
AI and Education Expert, AI Content Lead at Nebius Academy
Stanislav started his career as a mathematician, but later switched to creating and managing educational projects in Data Science.
LinkedIn
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Tatiana Gaintseva
Researcher, Methodologist, PhD Student at Queen Mary University of London
Tatiana is doing her PhD in AI in Computer Vision. Experienced in AI education, she is currently working on research related to the interpretability of multi-modal models.
LinkedIn
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Karina Zainullina
Research Engineer (LLMs)
at Nebius
Machine Learning Engineer with deep passion and experience in NLP, specializing in generative LLMs pretraining and fine-tuning.
LinkedIn
Join our supportive community
Fellow learners and experts will help you with ML skills and concepts, share tips and best practices, and stay connected with you even after you graduate.

We use Slack to chat, network, and learn together: enroll to access the group and all the community benefits we offer.
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FAQ
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