Eligibility: Tong Class students only
Availability: Offered every semester
Instructor Information
- Name: Yixin Zhu
- Email: [email protected]
- Office Hours: By appointment (email only; no WeChat)
- Office Location: 王克桢楼1905
TA Information
- Name: Chang Pan (TA) and Fengyuan Yang (TA)
- Email: [email protected], [email protected]
- Office Hours: Fridays, 20:00–21:00, 王克桢楼1904
Course Overview
This course is designed to introduce students to the fundamentals of research in Artificial Intelligence (AI) systems. Students will gain hands-on experience by working on research projects across various AI domains.
Plagiarism
- Please refer to the plagiarism page for details.
Errata / Typos
- Please contact the instructor or TA
Objectives
By the end of this course, students will:
- Understand the principles and methodologies of AI research
- Gain practical experience in conducting research projects
- Develop critical thinking and problem-solving skills in AI domains
- Learn to analyze and interpret research findings
- Enhance the ability to communicate research results effectively
- Acquire skills in academic writing and LaTeX
- Understand the importance of research collaboration and academic integrity
Gradescope
All assignments and project deliverables in this course are submitted and graded through Gradescope.
- How to use Gradescope: A Student Guide
- Registration
- Joining the Course
- Gradescope Course ID: TBD
- Gradescope Entry Code: TBD
Computing Resources
- All students: Students are encouraged to register and use commercially available AI Token platform. See the Token Page for details.
- Tong Class majors: The Institute for AI provides computing nodes for coursework and projects. See the Cluster page for access and usage instructions.
- Non-Tong Class majors (including AI double majors): The course does not provide GPU compute or compensation for GPU hours for any assignment. Please plan to use your own resources, rent GPU hours from a cloud provider at your own expense, or try a free tier such as Google Colab or Kaggle Notebooks. For the capstone project, please contact your project advisor for compute support.
Weekly Schedule
- Week 1 [09.11] Course Logistics, Introduction to Research, Academic Writing, and Ethics, Yixin Zhu, PKU
- Week 2 [09.18] Module 0: Programming Best Practices, Chi Zhang, PKU
- Week 3 [09.25] Holiday
- Week 4 [10.02] Holiday
- Week 5 [10.09] Module 1: Machine Learning, Muhan Zhang, PKU
- Week 6 [10.16] Module 2: Computer Vision, Siyuan Huang, BIGAI
- Week 7 [10.23] Module 3: Cognitive Reasoning, Yixin Zhu, PKU
- Week 8 [10.30] Module 4: Robotics, Yixin Zhu, PKU
- Week 9 [11.06] Module 5: Natural Language Processing, Zilong Zheng, BIGAI
- Week 10 [11.13] Module 6: AI Hardware and Acceleration, Xiyuan Tang and Yaoyu Tao, PKU
- Week 11 [11.20] Module 7: Multi-Agent Systems, Yaodong Yang, PKU
- Week 12-18 [11.23-01.08] Capstone Project, Yixin Zhu, Chi Zhang, Muhan Zhang, Yaodong Yang, Xiyuan Tang, and Yaoyu Tao
Assessment
- Attendance: 10%
- Weekly Assignments: 55%
- Each of the 8 modules (Modules 0–7) offers two versions of its assignment: a full assignment (10%) and a short assignment (5%). For each module you attempt, complete one version of your choice.
- You must complete 7 of the 8 modules, made up of exactly 4 full assignments and 3 short assignments.
- If you complete all 8 modules, the highest-scoring combination of 4 full and 3 short assignments will be used toward your final score.
- Module 0 offers a full assignment only.
- Course Project: 35%
- Mid-project Review: 10%
- Project Report: 20%
- Overall Evaluation by Project Advisor: 5%