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course-zoomcamp

Machine Learning Zoomcamp

Syllabus

Taking the course

2022 Cohort

We start the course again in September 2022

Self-paced mode

You can take the course at your own pace. All the materials are freely available, and you can start learning at any time.

To take the best out of this course, we recommened this:

  • Register at DataTalks.Club and join the #course-ml-zoomcamp channel
  • For each module, watch the videos and work through the code
  • If you have any questions, ask them in the #course-ml-zoomcamp channel in Slack
  • Do homework. There are solutions, but we advise to first attempt the homework yourself, and after that check the solutions
  • Do at least one project. Two is better. Only this way you can make sure you're really learning. If you need feedback, use the #course-ml-zoomcamp channel

Of course, you can take each module independently.

Prerequisites

  • Prior programming experience (at least 1+ year)
  • Being comfortable with command line
  • No prior exposure to machine learning is required

Nice to have but not mandatory

  • Python (but you can learn it during the course)
  • Prior exposure to linear algebra will be helpful (e.g. you studied it in college but forgot)

Asking questions

The best way to get support is to use DataTalks.Club's Slack. Join the #course-ml-zoomcamp channel.

To make discussions in Slack more organized:

Putting everything we've learned so far in practice!

11. KServe (optional)

Putting everything we've learned so far in practice one more time!

Writing an article about something not covered in the course.

For those who love projects!

Previous cohorts

2021 Cohort

Our other courses

If you liked this course, you'll like other courses from us:

Supporters and partners

Thanks to the course sponsors for making it possible to run this course

Thanks to our friends for spreading the word about the course