Редакція dev.ua AI Eng 3 June 2025, 16:37

Google launches updated “Machine Learning Crash Course” in Ukrainian

The field of artificial intelligence (AI) and machine learning is constantly evolving, with new technologies emerging such as generative AI and large language models. Understanding the basic concepts of machine learning is becoming key for those who want to create intelligent software, effectively use AI tools, or simply stay up to date with technology trends.

That’s why Google is introducing an updated, free Machine Learning Crash Course in Ukrainian. The course covers the fundamentals of machine learning (ML) and AI, includes material on large language models, AutoML, as well as in-depth information on working with data and AI. This online course is a quick, practical introduction to machine learning from Google. In 15 hours of the course, anyone interested, with basic programming knowledge, will be able to master key practical skills with ML.

The course will be useful

For beginners who want to get acquainted with machine learning and artificial intelligence.
Developers looking to expand their knowledge and skills.
For anyone interested in modern technologies and wants to understand how they work.

The course contains

12 modules on practical topics covering key aspects of machine learning.
9 videos explaining machine learning concepts
Over 100 exercises and tests;
Ability to receive badges after successfully passing tests at the end of each module;
Interactive visualizations and real-world examples.

All materials are available online, so you can take the course at your own pace and at a time convenient for you. The course is built on the principle of modularity: each module is self-sufficient, so if you already have experience, you can immediately move on to a topic that interests you.

Course Module Overview

Machine Learning Models: introduces building regression and classification models.
Data: discusses basic techniques and recommendations for working with machine learning data.
Advanced Machine Learning Models: Introduces the most advanced machine learning architectural models.
Machine Learning in Real-World Environments: Teaches the most important aspects of building and deploying machine learning models in real-world environments, including implementation guidelines, automation, and responsible development.
Building Machine Learning Models at Google: examines the key principles and best practices for building and deploying ML models on Google’s infrastructure.

You can familiarize yourself with the course and start studying today at the link.

Google also offers many other learning resources that people can use in their work, personal lives, or studies. To explore these resources, visit the Google Knowledge Hub.