Capstone Project

Overview

This extended module, spanning an entire month, is dedicated to devising and developing your own AI project. You will have the opportunity to apply the knowledge and skills you have acquired throughout the course to a real-world problem of your choice. This module emphasizes project planning, implementation, and iterative development. You will also document your work, analyze your results, and prepare a presentation to showcase your project. Writing and presenting your project report is a crucial step in the scientific process, allowing you to communicate your findings effectively and reflect on your work.

Instructors

Yixin Zhu, Chi Zhang, Muhan Zhang, Yaodong Yang, Xiyuan Tang, and Yaoyu Tao, PKU

Topics Covered

Project Development

  • Project ideation and problem definition
  • Proposal writing and project planning
  • Implementation of AI models and systems
  • Integration of multiple AI technologies (ML, CV, NLP, robotics, cognitive reasoning, MAS, etc.)
  • Ethical considerations in AI project development
  • Performance evaluation and optimization
  • Project documentation and presentation

Report Write-up

  • Scientific writing principles
  • Structure of a research paper
  • Data visualization and presentation
  • Critical analysis and discussion of results
  • Ethical considerations and future work
  • Oral presentation skills

Assignments

Throughout these weeks, you will work on your individual capstone project under the guidance of a randomly assigned advisor. Regular check-ins and in-person progress reports will be required. You will also complete a mid-project review by submitting a two-page abstract that presents the project’s introduction, related work, and methodology. The mid-project assessment will be worth 10% of your final grade. At the end of the module, you must submit the final deliverables listed below; the project report accounts for 20% of your final grade. Your assigned advisor will also provide an overall evaluation of your work, worth a further 5%.

Final Deliverables

  1. A fully implemented AI project with source code and documentation.
  2. A comprehensive project report (at least 4 pages in length, excluding references, formatted in the LaTeX template) detailing your problem, approach, implementation, results, and discussion.
  3. A 10–15 minute recorded presentation showcasing your project.
  4. Submit your code with documentation, report (LaTeX), and presentation video through Gradescope. The presentation video should be shared via a timestamped PKU Disk link.

Additional Resources

Notes

  • You are encouraged to utilize the computing resources provided for this course (see Computing Resources) in your project implementation, and to consult your project advisor for compute support.
  • Regular consultations with your assigned advisor will be available throughout these weeks. Make sure to schedule sessions to get feedback and guidance on your project.
  • Consider the ethical implications of your AI project. Refer to the AI ethics guidelines discussed in previous modules.
  • Start working on your project early and iterate based on feedback. Do not leave everything to the last minute!
  • Start writing your report early. Writing often clarifies thinking and may reveal areas where additional work is needed.
  • Use clear, concise language. Avoid jargon where possible, and explain technical terms when they are first used.
  • Make your figures and tables self-explanatory. They should be understandable even without the main text.
  • Practice your presentation multiple times. Time yourself to ensure you stay within the 15-minute limit.
  • Be prepared to answer questions about your work. Think about potential questions in advance.
  • Remember to acknowledge any collaborators, advisors, or resources that significantly contributed to your project.
  • Your capstone project could be a significant part of your portfolio, potentially useful for future academic or career opportunities!
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Last updated on Aug 26, 2026