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Intro to ML from an LLM Standpoint
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.
Software engineers and developers
Data scientists
Deepen your knowledge to get a chance to move into AI/ML Engineer roles.
Master ML and LLMs to explore the opportunities the field offers.
This course is best suited for
Starts on November 5th
In-person in London
14 weeks
3 hours a week
From industry experts
Free Nebius Academy course
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 Central London.
What will you learn?
This free course covers the basics of machine learning (ML), focusing on large language models (LLMs).
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)
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
Skills you'll gain:
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
Our instructors are industry experts
Stanislav Fedotov
Karina Zainullina
AI and Education Expert, AI Content Lead at Nebius Academy
Research Engineer (LLMs) at Nebius
Stanislav started his career as a mathematician, but later switched to creating and managing educational projects in Data Science.
Machine Learning Engineer with deep passion and experience in NLP, specializing in generative LLMs pretraining and fine-tuning.
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.
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.
We use Slack to chat, network, and learn together: enroll to access the group and all the community benefits we offer.
Join our supportive community
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Application
Join the community
Start learning!
Fill out the form by October 27th to register. Please note that we will need a link to your CV or LinkedIn profile to ensure this course is the right fit for you.
In 3-4 days after applying, you’ll receive an email with feedback from our team, the next steps, and a link to the Slack group where you’ll communicate with our instructors, community managers, and other students.
The course is set to start on November 5th.
Sign up now to reserve your spot
FAQ
We'll guide you through the basics of machine learning (ML), focusing on large language models (LLMs).
We are part of Nebius AI, a European AI-centric public cloud with global expertise. Recognizing the immense potential of ML and AI technologies, we actively encourage and support their study. Our mission is to provide accessible education for anyone with sufficient background and motivation, eager to begin their journey into ML and AI.
To register for this in-person course, fill out the form on the website by October 27th. We’ll also ask for a link to your LinkedIn profile or a copy of your CV, so we can make sure the course is the right fit for you.
You are expected to have a solid grasp of Python programming.
Yes, it's in-person and will be held in London.
You'll have regular lectures with experienced professionals at a convenient space in Central London.
You'll have regular lectures with experienced professionals at a convenient space in Central London.
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