Course Syllabus

CSE 5 - Principles and Practice of AI [Bonjour - SP26]

Course Information

New Course Note

This is the first offering of this course. Some aspects of the course structure, schedule, assignments, and grading details may be adjusted during the quarter as the course is refined. Any changes will be communicated clearly and in advance.

Course Staff

Instructor: Trevor Bonjour

Instructor Email: tbonjour@ucsd.edu 

Instructor Office Hours:  TBD

Teaching Assistants 

Communication

Emails may be missed - Please use Piazza for all course-related questions/discussions. If needed, you can post a private message to the instructors on Piazza. 

Lectures 

Lectures are on Tuesdays and Thursdays, 3:30 pm to 4:50 pm in CENTR 109

Lectures will be held in-person at the regularly-scheduled time and place. Attendance is highly encouraged. Lectures are designed to include in-class activities, discussion, and collaborative work, and students who attend in person will get the most out of these experiences. Lecture notes and other materials will be posted, and lectures will be podcasted and posted online for remote viewing.

Please note, we have requested that podcasting be enabled for the lectures, but we cannot guarantee that it will always work. You will be able to find the lecture recordings at https://podcast.ucsd.edu/.

Textbook and Materials

You will not need to purchase any materials for this course. All required materials will be provided through canvas. These may include activities, notes, readings, references, and videos.

Course Overview

Course Description

This course introduces students to the conceptual and technological foundations of artificial intelligence (AI) and provides a framework to understand and assess social and ethical aspects of AI. The course will explore the computational basis of intelligence -- machine learning (ML) and its various approaches. Students will be exposed to building ML models, training and validating them. The course will delve into how AI is applied and discuss its implications. This course is intended for students to develop a high-level understanding of the AI field. This is not intended for students who plan to study AI, computer science, or data science.

Prerequisites

None

Learning Outcomes

Upon successful completion of this course, students will be able to:

  • Explain the basic concepts behind artificial intelligence and machine learning.
  • Explain the social, ethical, and cultural implications of AI technologies.
  • Analyze AI outputs for potential bias or failure.
  • Design simple activities to test and evaluate AI behavior.
  • Use generative AI tools to support learning and experimentation.
  • Reflect critically on AI's role in society and make informed decisions about its use.

Assessments

This course includes a mix of activities, quizzes, assignments, presentations, and a final project.

Activities and Participation

A significant portion of this course is based on activities completed during lecture and discussion sections. These activities are designed to reinforce key concepts, encourage exploration of AI tools, and promote discussion and critical thinking.

Activities may include worksheets, group discussions, tool exploration exercises, short written responses, case studies, and occasional student presentations. Most activities are graded for completion and reasonable effort rather than correctness.

Students who are unable to attend a class session may earn activity credit by completing the activity outside of class and submitting it by 11:59 PM on the Sunday following that week's lectures. While activities can be completed outside of class, many are designed for live interaction and discussion and are most valuable when done in person.

Some activity sessions may include short student presentations related to course topics. Presentation days will be announced in advance. Students must be present in person on their scheduled presentation day in order to receive credit for that component of the course.

Quizzes

There will be short online quizzes throughout the quarter that assess understanding of key concepts discussed in class. These quizzes will focus on conceptual understanding of artificial intelligence, generative AI, limitations of AI systems, bias, ethics, and responsible use of AI tools. Quizzes may allow multiple attempts and are intended to reinforce learning rather than act as high-stakes exams.

Take-Home Assignments

There will be several take-home assignments during the quarter. Assignment instructions will specify the submission format, deadlines, and allowed resources.

Final Project

There will be a final project that serves as the final exam for the course. Additional details will be provided later in the course.

Grading

Grade Breakdown

We will use the following tentative grade breakdown:

Grade Breakdown
Assessment Percentage
Activities and Participation  40%
Take-Home Assignments 30%
Final Project 20%
Quizzes 10%

Grading Scale

The standard grading scale below is the starting point for the course. After all scores are in, final letter-grade cutoffs may be adjusted slightly downward if appropriate, but cutoffs will never be raised. For example, the A cutoff will never exceed 94%.

Grading Scale
Letter Grade Range
A ≥ 94%
A- ≥ 90% and < 94%
B+ ≥ 87% and < 90%
B ≥ 84% and < 87%
B- ≥ 80% and < 84%
C+ ≥ 77% and < 80%
C ≥ 74% and < 77%
C- ≥ 70% and < 74%
D ≥ 61% and < 70%
F < 61%

Pass/Not Pass for Undergraduate Students: We will follow the university grading system of C- or higher for P/NP grades.

Incomplete Grade: Sometimes, circumstances beyond a student's control prevent them from completing a class even once they have completed the majority of the coursework at a passing level. UCSD has a process in place for you to request an Incomplete (I) if this happens to you. Here is the campus policy about the Incomplete grade and some information about it.

 

Course Policies

Accommodations for Students with Disabilities

We aim to create an environment in which all students can succeed in this course. We need and want to hear from you if additional accommodations would improve your experience in the course.

If you have a disability, please contact the Office for Students with Disability (OSD), which is located in University Center 202 behind Center Hall, to discuss appropriate accommodations right away. They also provide the OSD Student Portal. We will work to provide you with the accommodations you need, but you must first provide a current Authorization for Accommodation (AFA) letter issued by the OSD. You are required to present the AFA letters to the Faculty and to the OSD Liaison in the department in advance so that accommodations may be arranged. We ask that you work to organize the AFA and to let us know about it as early in the quarter as possible so that we can best support your needs. For more information, see Disability Resources at UCSD.

Academic Integrity

In this course we expect students to adhere to the UC San Diego Integrity of Scholarship Policy. This means that you will complete your work honestly, and with integrity, and support an environment of integrity within the class.

Because this course involves the use of AI tools, the goal is not to avoid AI, but to use it responsibly, thoughtfully, and transparently. Many assignments in this course will explicitly involve using AI tools, but you are responsible for the work you submit and should understand and be able to explain your work if asked.

Some examples of how academic integrity applies in this course include:

  • You may use AI tools where allowed or required, but submitted work should reflect your understanding, analysis, and reasoning.
  • You may not submit AI-generated content as your own work without reviewing, modifying, and understanding it.
  • You should be able to explain any work that you submit, including prompts you used and how you used AI tools.
  • Students may not submit the same work as another student unless the assignment is explicitly a group assignment.
  • Students may not post course materials, assignment questions, or solutions to public websites or repositories.

Use of Generative AI Tools

Generative AI tools (such as ChatGPT, Copilot, Gemini, Claude, etc.) are an important part of this course and will be used in some activities and assignments.

You are encouraged to use AI tools to:

  • Explore ideas
  • Brainstorm
  • Learn new concepts
  • Compare explanations
  • Analyze outputs
  • Experiment with prompts
  • Support your learning

However, AI tools should not be used to replace your own thinking. You are responsible for evaluating AI-generated content, checking for errors, understanding the material, and making your own decisions about how to use AI outputs.

In general:

  • You are responsible for any work you submit.
  • You should understand and be able to explain your work.
  • You should critically evaluate AI outputs rather than assuming they are correct.
  • You should use AI tools responsibly and ethically.

Specific guidelines for AI use may be provided for individual assignments.

Outside Tutoring

Individuals are not permitted to approach students to offer services of any kind in exchange for pay, including tutoring services. This is considered a solicitation for business and is strictly prohibited by University policy.

Class material and intellectual property

Our lectures and course materials, including videos, assignments, and similar materials, are protected by U.S. copyright law and by University policy. We are the exclusive owner of the copyright in those materials we create. We acknowledge the cumulative contributions to this course material of previous instructors, TAs, and tutors, as well as contributions to the class structure from colleagues in CSE and at UCSD.

You may take notes and make copies of course materials for your own use. You may also share those materials with another student who is enrolled in or auditing this course. You may not reproduce, distribute or display (post/upload) lecture notes or recordings or course materials in any other way — whether or not a fee is charged — without our express prior written consent. You also may not allow others to do so. If you do so, you may be subject to student conduct proceedings under the UC San Diego Student Code of Conduct.

Similarly, you own the copyright in your original work. If I am interested in posting your answers or papers on the course web site, I will ask for your written permission.

Late Adds

I follow the CSE department guidance on Late Adds, namely that “all students are expected to attend class for the first two weeks and complete assignments if they are on the waitlist for a course. Attending class and completing course assignments does not guarantee enrollment. If students choose to miss class or not turn in assignments while on the waitlist, the student will receive a “0” on all missed assignments, if they secure a seat in the course off the waitlist.

 

Resources for Students

Mental Health Services

For students seeking services for mental health issues (including, but not limited to: stress, sleep issues, depression, anxiety, academic distress, relationship issues, etc.), Counseling and Psychological Services (CAPS) provides free, confidential psychological counseling and crisis services for all registered UC San Diego students. CAPS also provides a variety of groups, workshops and drop-in forums.

To contact CAPS, call (858) 534-3755. All students are screened with a brief telephone assessment. For more information, visit the Counseling and Psychological Services website.

Getting Help

We expect that all students will need help at some point during the quarter. Many resources are available including TA and instructor office hours, as well as the Piazza discussion board. We also encourage you to form study groups.

The IDEA Engineering Student Center, located just off the lobby of Jacobs Hall, is a hub for student engagement, academic enrichment, personal/professional development, leadership, community involvement, and a respectful learning environment for all. The Center offers a variety of programs, listed on the IDEA Center Facebook page at http://www.facebook.com/ucsdidea (you are welcome to Like this page!) and the Center website at http://idea.ucsd.edu/. The IDEA Center programs support both undergraduate students and graduate students.” The Teaching and Learning Commons continues to offer their full suite of student success programs, including learning strategies coaching.

Diversity and Inclusion

We are committed to fostering a learning environment for this course that supports a diversity of thoughts, perspectives, and experiences, and respects your identities (including race, ethnicity, heritage, gender, sex, class, sexuality, religion, ability, age, educational background, etc.). Our goal is to create a diverse and inclusive learning environment where all students feel comfortable and can thrive.

Our instructional staff will make a concerted effort to be welcoming and inclusive to the wide diversity of students in this course. If there is a way we can make you feel more included please let one of the course staff know, either in person, via email/discussion board, or even in a note under the door. Our learning about diverse perspectives and identities is an ongoing process, and we welcome your perspectives and input.

We also expect that you, as a student in this course, will honor and respect your classmates, abiding by the UCSD Principles of Community (https://ucsd.edu/about/principles.html), along with the guidelines for online interaction posted on the site. Please understand that others’ backgrounds, perspectives, and experiences may be different than your own, and help us to build an environment where everyone is respected and feels comfortable.

If you experience any sort of harassment or discrimination, please contact the instructor as soon as possible. If you prefer to speak with someone outside of the course, please contact the Office of Prevention of Harassment and Discrimination: https://ophd.ucsd.edu/.

Basic Needs/Food Insecurities

If you are experiencing any basic needs insecurities (food, housing, financial resources), there are resources available on campus to help, including The Hub and the Triton Food Pantry. Please visit http://thehub.ucsd.edu/ for more information.

Course Summary:

Course Summary
Date Details Due