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Hey there, 
 
Welcome to Module 1!
 
Over the next two weeks, we will explore the basics of machine learning.
What You’ll Learn
  1. Introduction to Machine Learning
  2. ML vs Rule-Based Systems
  3. Supervised Machine Learning
  4. CRISP-DM
  5. The Modelling Step (Model Selection Process)
  6. Setting up the Environment
  7. Introduction to NumPy
  8. Linear Algebra Refresher
  9. Introduction to Pandas
  10. Summary
All the course materials are available on GitHub and are open for access. Simply click on the lesson you need to find a video lecture and accompanying notes on the GitHub page.
Join Module 1
Homework
Your assignment for this module is to:
  • Set up your environment
  • Load the dataset
  • Conduct data exploration (including versions, counts, missing values, and maximum values)
  • Handle missing data
  • Conclude with a mini linear regression calculation
The deadline for this homework is September 30, 2025, 1:00 AM CET.
Submit Your Homework Here →
Got stuck while starting the homework?
Having questions is a normal part of the learning process.
 
Here's what to do:
  1. Check the FAQ
  2. If you don't find an answer to your question in the FAQ, ask it on the ML Zoomcamp Slack channel. We will update the FAQ with answers.
Join Our Slack Channel
💡 Pro Tips
  • Expect to spend about 6-7 hours on this module if you're a beginner, including the materials and the homework assignment.
  • Break it into smaller chunks, don't wait until the last day.
Hundreds of learners are starting this module alongside you. Be sure to collaborate and share knowledge.
🔗 Quick Links
You've Got This!
This is Module 1 of 10: completing the homework brings you one step closer to earning your final certificate.

It's okay if you don't get everything right away; most students don't.

Every attempt gets you closer to mastering ML.
Good luck with learning!

Alexey and the DataTalks.Club Team
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