DVC Tools for Data Scientists & Analysts
All the things you need to know to take you from your notebook to production with DVC tools!
What's Included?
Write your awesome label here.
What's Included?
Write your awesome label here.
Building blocks for success
You will learn how to use DVC tools to create a flexible and effective pipeline to get your machine learning projects into production efficiently and fully reproducible.
Write your awesome label here.
Collaborate
Break down the wall between data science and engineering teams. You will be able to work together more transparently and efficiently, significantly speeding your time to market for your projects.
Write your awesome label here.
Best Practices
You will learn to apply the best practices from software development to machine learning projects. DVC tools enable version control of data, models and experiments as well as CI/CD for machine learning projects.
Course content
Meet the instructors
Write your awesome label here.
Mikhail Rozhkov
Has over 6 years of hands-on experience in Machine Learning & Data Science projects as data scientist and team lead. Leads projects and helps teams to implement good tools and engineering practices. Author of online courses on ML Experiments automation and MLOps with DVC. Helped ML teams from banking, telecom, retail and other industries to set up MLOps tools and processes.
Write your awesome label here.
Milecia McGregor
Milecia is a senior software engineer, international tech speaker, and mad scientist that works with hardware and software. She will try to make anything with JavaScript first. In her free time, she enjoys learning random things, like how to ride a unicycle, and playing with her dog.
