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651-4284-00L 3 Credits BSC , MSC D-ERDW

AI-Assisted Coding and Collaborative Project Development

Lecturers & Examiners: Dr. Alexis Shakas
VVZ CR n/a

Last Updated: 2026-06-03 00:14:22

Abstract

Learn how to structure your project in git and leverage the power of Python for scientific programming. In this project-based course, you collaborate with peers using Git to structure a semester project of your choice. We learn best practices for creating reproducible, readable and reusable software leveraging AI-assistants for efficiency and overcoming the learning curve.

Objective

Succesfully develop research-oriented code in python. Confidently use AI-assistants to improve and enhance programming skills. Critically implement tests to assess code output and debugging Independently structure a Git project and collaborate with peers. Learn to structure projects using Git and collaborate with peers to develop a semester project.

Content

Python data structures, methods, documentation, use of standard libraries for scientific computing and plotting. Use stepwise refinement to structure real-world problems and create prompts for AI-assisted coding. Prioritize tests and good coding standards. Explore AI-assistants to efficiently and effectively write code, with an aim to maximize learning in the meanwhile. Learn how to use Git to structure a project with your peers, and make it into a package that others can use and reproduce your results. You will develop a project during the course with python, using AI assistants and host that project on a git repository. The course takes place at the PBLabs and is ideal for project-based work.

Resources

Lecture Notes

Lecture notes will be on a Git repository.

General Information

Language
English
Levels
BSC , MSC
Frequency
Yearly recurring

Examination

Type
graded semester performance
Project based assessment (no exam).

Registration & Places

Max Places
48

Course Components

Type Title Time & Place Hours
lecture with exercise AI-Assisted Coding and Collaborative Project Development
  • Tue 13:15-15:00 (RZ D 8)
  • 17.03 Date 13:15-15:00 (ML H 41.1)
  • 31.03 Date 13:15-15:00 (ML H 41.1)
  • 14.04 Date 13:15-15:00 (ML H 41.1)
  • 05.05 Date 13:15-15:00 (ML H 41.1)
2 h weekly

Offered In

  • Earth and Climate Sciences Bachelor
    • Majors
      • Major: Geology and Geophysics (Advisors of the major in Geology and Geophysics are Dr. Vincenzo Picotti (Geology) and Dr. Andrea Zunino (Geophysics).)
        • Electives (Additional courses can be chosen from the complete offerings of the ETH Zurich and University of Zurich. The following elective courses are strongly recommended for students interested in the "Space Systems" focus: - 701-0106-00L Mathematik V: Angewandte Vertiefung von Mathematik I - III)
  • Earth Sciences Master
    • Electives (Courses can be chosen from the complete offerings of the ETH Zurich and University of Zurich (according to prior agreement with the MSc Committee).)