Kyryl Opens ML

This mini-course, "Infrastructure," is the first module of the comprehensive "Machine Learning in Production" course. While the full course covers all aspects of deploying and managing ML projects end-to-end, including Data, Experiments, Pipelines, Serving, Monitoring, and Platforms, this mini-course focuses specifically on building and managing ML infrastructure. Completing this mini-course gives you a strong foundation in infrastructure, which is a crucial part of the broader ML lifecycle covered in the full course.

This course is ideal for software engineers, ML professionals, tech switchers, and tech entrepreneurs interested in mastering the basics of ML infrastructure.

A basic understanding of programming concepts and familiarity with machine learning principles are recommended to get the most out of this course.

The course is designed to be completed in approximately 1.5 weeks. However, you can pace yourself according to your schedule and learning preferences.

No, you have access to the course materials indefinitely.

The course can be completed in about 8 hours total. You can choose to spread this out over a week or complete it in a single session, depending on your availability and learning style.

By the end of this course, you'll have a solid foundation in ML infrastructure, including setting up and managing environments using Docker, Kubernetes, and CI/CD. You'll also understand how to create and use design documents effectively.

Don't worry! Our course comes with a supportive Discord community channel dedicated to homework help. Here, you can ask questions, seek guidance, and collaborate with fellow learners and the instructor. Additionally, for each homework assignment, we provide an example implementation to guide you through the process.

Yes, upon completing this course, you will receive a 70$ discount on the full "Machine Learning in Production" course. Use your email address as the promo code at checkout.