Machine Learning
An introduction to machine learning fundamentals — from mathematical foundations to building first predictive models. Designed for learners with no prior ML experience who want to understand how algorithms learn from data.
7 chapters · 32 lessonsClassical MLBeginner
Prompt Engineering in Practice
Master the art of crafting effective prompts for language models. From the basics to advanced techniques like Chain of Thought, RAG, and prompt chaining.
16 chapters · 56 lessonsLLM / NLPBeginner
Python — From Basics to Advanced
Complete Python course — from your first `print()` to `asyncio`, generators, advanced typing, performance, multiprocessing, and packaging. 20 chapters, 80 lessons, 400 questions.
25 chapters · 100 lessonsProgrammingBeginner
Neural Networks: From Fundamentals to Modern AI
A course for developers and data scientists with basic Python knowledge who want to understand how neural networks are built and trained. Upon completion, participants can independently implement, train, and optimize deep convolutional and recurrent networks.
13 chapters · 65 lessonsDeep LearningIntermediate
Build AI Agents with LangChain
A practical course on building AI agents with LangChain for learners who already know the basics of working with language models and want to create multi-step agentic applications.
8 chapters · 32 lessonsAgentic AIIntermediate
Transformer from Scratch
An advanced course for building the Transformer architecture from scratch in PyTorch. Course shell prepared for chapters and lessons to be added later.
10 chapters · 40 lessonsAI ArchitectureAdvanced