How the challenge works and what you’ll build

How to deploy, monitor, and evaluate your ML system in a live environment

What’s expected from your model and how to get started

What if everyday objects weren’t so ordinary? In this talk, Alexey will share how he and his son built a GenAI-powered system that transforms photos of common objects into horror stories—automatically generating a new podcast episode every day. He'll dive into the process, deployment, automation, and key lessons learned.

An overview session where the course creator discusses the Machine Learning Zoomcamp, including course curriculum, assignments and scoring, homework and feedback, course projects for your portfolio, and DataTalks.Club community; plus tips for navigating the course materials and maximizing your learning experience.

Hands-on workshop on building a search engine from scratch, focusing on text search and vector search. Topics include in-memory text search, tokenization and preprocessing, inverted index construction, embeddings, converting text to vectors, cosine similarity, and strategies to combine text and vector search. The session includes practical coding in a Jupyter Notebook using Python to implement both text and vector search approaches.

Workshop led by Alexey Grigorev on building a chatbot using large language models with Python. Topics include data extraction from FAQs, knowledge base indexing, chatbot setup in a Jupyter Notebook, interfacing with LLMs, and implementing Retrieval-Augmented Generation (RAG).

Overview of the Machine Learning Zoomcamp course: topics and technologies covered; course assignments and scoring; homework and getting feedback; course projects for your portfolio; DataTalks.Club community; tips for navigating the course materials and getting the most out of your learning experience.