Frequently Asked Questions

Table of contents

  1. Frequently Asked Questions
    1. Course Basics
    2. Technical Setup
    3. Homework and Projects
    4. Certificates
    5. Course Materials
    6. Support and Help
    7. Common Issues
    8. Additional Resources

Course Basics

Q: When does the course start?
A: The next cohort starts January 13th 2025. Register using this link. Join the Telegram channel and DataTalks.Club’s Slack for announcements.

Q: What are the prerequisites?
A: You should have:

  • Basic coding experience
  • Familiarity with SQL
  • Experience with Python (helpful but not required) No prior data engineering experience needed. See prerequisites.

Q: How many hours per week should I expect to spend?
A: Typically 5-15 hours per week, depending on your background and experience.

Q: Can I join after the start date?
A: Yes, you can still join and submit homework, but be mindful of assignment deadlines.

Q: Do I need a confirmation email after registering?
A: No, you’re automatically accepted. Registration is just to gauge interest.

Technical Setup

Q: Which Python version should I use?
A: Python 3.9 is recommended for compatibility with course materials. Python 3.10 and 3.11 should also work.

Q: Should I use local machine, GCP, or GitHub Codespaces?
A: You have three options:

  1. Local machine (may have challenges on Windows)
  2. GitHub Codespaces (pre-installed tools)
  3. Cloud VM (GCP recommended)

Q: Why use GCP instead of other cloud providers?
A: GCP is recommended because:

  • Everyone has a Google account
  • $300 free credits for new users
  • BigQuery integration
  • Consistent with course materials

Q: What should I set up before starting?
A: Install and configure:

  • Google Cloud account and SDK
  • Python 3 (with Anaconda)
  • Terraform
  • Git

Homework and Projects

Q: What are the homework deadlines?
A: Check courses.datatalks.club/de-zoomcamp-2025 and the Google Calendar.

Q: Are late submissions allowed?
A: No, but you can submit while the form remains open. Check submission timestamp on the Course page.

Q: What should I submit as the homework URL?
A: Your GitHub/GitLab/Bitbucket repository containing your work for that week.

Q: How does the points system work?
A: Points are awarded for:

  • Homework completion
  • FAQ contributions (1 point/week max)
  • Learning in public (1 point/link, 7 points max)

Certificates

Q: Do I need to complete all homework for the certificate?
A: No, only the peer-reviewed capstone projects are required.

Q: Can I get a certificate in self-paced mode?
A: No, certificates require completing a “live” cohort due to peer review requirements.

Q: How do I get my certificate?
A: After project grading:

  1. Verify your name in your profile
  2. Wait for grading completion announcement
  3. Follow certificate generation instructions

Course Materials

Q: Which YouTube playlist should I follow?
A: The main playlist is Data Engineering Zoomcamp. Additional playlists for specific years are available.

Q: Can I follow the course after it finishes?
A: Yes, all materials remain available. You can:

  • Study at your own pace
  • Review past homework
  • Prepare for next cohort
  • Work on projects

Q: What’s different in the current cohort?
A: 2025 edition uses Kestra instead of MageAI. See the demo and updated materials.

Support and Help

Q: How do I get help during the course?
A: Multiple support channels:

  • Slack channel (search before asking)
  • FAQ documentation
  • @ZoomcampQABot for searches
  • Office hours via YouTube Live

Q: How should I ask questions in Slack?
A: Include:

  • Your OS/environment
  • Commands you ran
  • Error messages (no screenshots)
  • What you’ve tried
  • Use code formatting (```)
  • Keep discussion in threads

Q: Will office hours be recorded?
A: Yes, all sessions are recorded and available shortly after.

Common Issues

Q: What if I have trouble with Windows?
A: Consider using WSL for better compatibility, especially for shell scripts.

Q: How do I fix VSCode connection issues to GCP VM?
A: Try managing SSH fingerprints or deleting the known_hosts file.

Q: How do I open HTML files from WSL?
A: Install wslu and use wslview filename.html

Additional Resources

Q: Where can I find more learning materials?
A: Check Awesome Data Engineering Resources

Q: How can I contribute to the course?
A: You can:

  • Star the repository
  • Share with others
  • Create PRs for improvements
  • Update this FAQ
  • Help fellow students