CSC 160: AI for All (Fall 2026)
Course Information
Course Description
This experimental course will explore how AI can be safely, ethically, and effectively leveraged by students to enhance their ability to learn. Students will be expected to both collaboratively and independently pursue AI applications within their own domains of interest, and to participate in course discussions. Basic concepts of how AI systems work and how they are built will be covered at a general audience level. This course has no formal prerequisites and is open to all students; however, students are encouraged to complete their primary writing requirement before taking the class. This is a four credit course.
Course Outcomes
By the end of this course, students will be able to:
Explain general concepts, techniques, and models comprising the field of AI.
Evaluate limitations and strengths of current and new AI models and tools.
Articulate informed perspectives on ethical, social, and scientific issues associated with current and potential near future applications of AI.
Use AI tools for constructive applications and learning.
Apply metacognitive strategies to learn more effectively with and without AI.
Instructor
- Instructor: Adam Purtee
- Homepage: cs.rochester.edu/u/apurtee.
- Email: apurtee AT cs DOT rochester.edu
- See blackboard for office hours and location.
Assignments
Regular Assignments
Regular assignments will typically require students to use an AI tool, read a selection about a topic, and/or engage with an ethical challenge related to the use of AI in some domain or context. Students will then write a short reflective essay conveying their experience and understanding to the instructor and TAs. Regular assignments are expected to be completed as individuals.
The AI Experiment Project
The goal of the course project is to do science with AI, about AI, or both. We will discuss the project together during the first few weeks of class. You will then propose a project, carry out your proposal over the semester, present your results verbally in class and in writing. You are encouraged to work together in small groups for this experiment -- science is easier to do with colleagues.Grading
Your Overall Numeric Grade
Your scores on the individual components of this course will be weighted to obtain your course score. All appeals of grades on individual scores must be made within one week of the grade being available. The following table represents the weighting of course components.
| Overall Category | Weight |
|---|---|
| Regular Assignments | 45% |
| Project | 45% |
| Participation | 10% |
| Total | 100% |
| Project Component | Weight |
|---|---|
| Proposal | 8% |
| Workshops (2/3) | 7% |
| Report/Slides | 10% |
| Presentation | 10% |
| Substantiveness | 10% |
Letter Grades
Letter grades will follow the Official University of Rochester Grading Scheme . Note that the University scheme places “average” between C and B. The following table is an estimate of how numeric grades map to letter grades.
| Letter Grade | Threshold |
|---|---|
| A (Excellent) | ≥ 93% |
| A− | ≥ 90% |
| B+ | ≥ 87% |
| B (Above Average) | ≥ 83% |
| B− | ≥ 80% |
| C+ | ≥ 77% |
| C | ≥ 73% |
| C− (Minimum satisfactory) | ≥ 70% |
| D (Minimum passing) | ≥ 60% |
| E | < 60% |
Schedule
| Date | DoW | Topic |
|---|---|---|
| Sep 1 | Tue | Introduction |
| Sep 3 | Thu | AI before Deep Learning (~1950-~2012) |
| Sep 8 | Tue | The Rise of Deep Learning (~2012-~2017) |
| Sep 10 | Thu | How AI Chat Works |
| Sep 15 | Tue | Effective Prompting |
| Sep 17 | Thu | Human Learning |
| Sep 22 | Tue | First Project Workshop |
| Sep 24 | Thu | Trust and Verification |
| Sep 29 | Tue | Reasoning: The Jagged Frontier |
| Oct 1 | Thu | Agents and Tools |
| Oct 6 | Tue | AI Ethics and Impacts |
| Oct 8 | Thu | Second Project Workshop |
| Oct 13 | Tue | No class — Fall break. |
| Oct 15 | Thu | Art and Creativity |
| Oct 20 | Tue | Copyright, Fair-use, and Plagiarism |
| Oct 22 | Thu | The Job Market |
| Oct 27 | Tue | Cybersecurity and Privacy |
| Oct 29 | Thu | Government: AI Use and Regulation |
| Nov 3 | Tue | Persuasion by AI and of AI |
| Nov 5 | Thu | Datacenters |
| Nov 10 | Tue | Healthcare and Mental Health |
| Nov 12 | Thu | Humanoid Robots |
| Nov 17 | Tue | Consciousness |
| Nov 19 | Thu | Predicting the Future |
| Nov 24 | Tue | Third Project Workshop |
| Nov 26 | Thu | No class - Thanksgiving. |
| Dec 1 | Tue | Symposium |
| Dec 3 | Thu | Symposium |
| Dec 8 | Tue | Symposium |
| Dec 10 | Thu | Symposium |
| Dec 18 | Fri | Final Reflection |
Policies
Academic Honesty
All assignments and activities associated with this course must be performed in accordance with the University of Rochester’s Academic Honesty Policy. More information is available at: www.rochester.edu/college/honesty
All incidents of academic dishonesty will be reported. Violations of the academic honesty policy carry significant penalties, such as a zero on the assignment and additional reductions to the resulting overall grade. Repeat offenders may be expelled from their majors and from the university.
Artificial Intelligence
Because of the topic of this course, students will be required to use generative AI tools in specific ways to complete assignments. However, the reflective essays and other writing requirements are meant to solicit YOUR thoughts and arguments, so they should be written by you without the use of AI. Misrepresentation of AI generated (or substantially edited) work as human authored will be considered academic dishonesty in this course. Similarly, while you are encouraged to discuss your work and the challenging questions of this course with others, submission of another student's work as your own will also be considered academic dishonesty.
Disability Resources
The University of Rochester respects and welcomes students of all backgrounds and abilities. In the event you encounter any barrier(s) to full participation in this course due to the impact of disability, please contact the Office of Disability Resources. The access coordinators in the Office of Disability Resources can meet with you to discuss the barriers you are experiencing and explain the eligibility process for establishing academic accommodations. You can reach the Office of Disability Resources at: disability@rochester.edu; (585) 276-5075; Taylor Hall.
Students with an accommodation for any aspect of the course must make arrangements in advance through the Disability Resources office. Then, as instructed by the office, contact the instructor to confirm your arrangements.