Georgia Tech CS 3630 Fall 2025 edition
Upon completion of this course, students will be able to:
The only formal prerequisite is CS1332 Data Structures & Algorithms. Prior knowledge of fundamentals of linear algebra and probability is helpful, but not required. Background in AI and Machine Learning is not assumed. The course requires access to a laptop. If you don’t have access to a laptop, please contact the instructor ASAP. All programming assignments will be completed in Python.
Important: Classes are delivered in person, Tue-Thu at 11am, in Scheller 100.
The grading distribution is:
| Component | Nr. | Grade | Total |
|---|---|---|---|
| Quiz 1 | 1 | 0% | 0% |
| Quizzes 2-7 | 6 | 5% | 30% |
| Participation | - | 6% | 6% |
| Project 1 | 1 | 4% | 4% |
| Projects 2-7 | 6 | 10% | 60% |
| 100% |
The late policy for projects is to linearly decrease the maximum score from 100 to 0, starting at the submission deadline (Tuesday, 23:59:59) and ending on Friday, 23:59:59. Thus, the maximum possible score decreases continuously from 100 to zero over the 72 hour period following the submission deadline (e.g., if you submit your project exactly 29 hours and 30 minutes late, you would have a maximum possible score of 59.02777777777778%).
Academic dishonesty will not be tolerated. This includes cheating, lying about course matters, plagiarism, or helping others commit a violation of the Honor Code. Plagiarism includes reproducing the words of others without both the use of quotation marks and citation. Students are reminded of the obligations and expectations associated with the Georgia Tech Academic Honor Code and Student Code of Conduct, available here.
You are expected to implement the core components of each project on your own, but the extra credit opportunities often build on third party data sets or code. That’s fine. Feel free to include results built on other software, as long as you are clear in your hand-in that it is not your own work.
You should not view or edit anyone else’s code. You should not post code to Piazza, except for starter code / helper code that isn’t related to the core project.
I ask you to be present for the assignments, thoroughly understand them, and take full ownership of the artifacts you produce. Coding with AI is now a fact of life, and it’s great, thrilling even! I encourage the use of tools like co-pilot and cursor to help you code.
However, the use of generative AI to code up an entire assignment with minimal involvement from your part (e.g., pasting the entire assignment in to an AI, or using “Agentic” AI to take care of the whole project) defeats the point of the class. Hence, this falls under the academic dishonesty policy. The purpose of the assignment is to build intuition and skill in robotics, which cannot be outsourced. Hence, I expect you to personally embark on each TODO in the coding assignments, being fully engaged. This includes using AI tools as you go along, but not to substitute your own understanding.
The assignments will frequently be accompanied with reflection questions designed to help assess whether you have fully grokked the methods/algorithms/techniques the assignments are designed to help you learn. I expect that you to be the author of the answers, not the prompter.
If needed, we will make classroom accommodations for students with documented disabilities. These accommodations must be arranged in advance and in accordance with the ADAPTS office.
This term we will be using Piazza for class discussion. The system is highly catered to getting you help fast and efficiently from classmates, the TA, and myself. Rather than emailing questions to the teaching staff, I encourage you to post your questions on Piazza. If you have any problems or feedback for the developers, email team@piazza.com.
Use Piazza to ask questions and seek clarifications. If you have a very specific question (related to your grade etc.) or a question that involves your personal information, you can make a private post on Piazza.
The TA office hours will be announced very soon, along with the location, in a pinned post on Piazza.
The materials from this class rely significantly on slides prepared by other instructors. Each slide set and assignment contains acknowledgements. Feel free to use these slides for academic or research purposes, but please maintain all acknowledgements.