CSE D 501: Modern Artificial Intelligence and Machine Learning Autumn 2026

Course Staff

Course Overview

This course builds the foundational skills for utilizing AI and ML techniques. This includes mathematical and coding skills, fundamental concepts in AI ethics such as bias and fairness, potential pitfalls and drawbacks of different AI and ML methods, and an overview of how AI and ML can be applied to real applications. 

Learning Objectives

By the end of this course, students will demonstrate the ability to:

• Implement basic machine-learning algorithms in software

• Analyze and implement basic machine learning and artificial intelligence algorithms including regression, classification, clustering, reinforcement learning, and neural networks

• Identify uses and pitfalls of basic machine learning and artificial intelligence algorithms in a range of application areas

• Analyze potential sources of bias and unfairness in a machine-learning workflow

Class Schedule/Location

Wednesdays, 6:30-9:20 pm, CSE2 G01

Course Materials

There is no mandatory textbook, although there will be some required reading, as well as suggested textbooks to follow. All course materials will be provided for free on the course website, Canvas or through the UW library.

Communication and Office Hours

The staff is available to help you on the Ed forum and during office hours. Please consider first asking questions on the Ed forum, so that others can also benefit from the shared responses. You are also free to answer other students' questions or hold discussions on the Ed forum; however, do not directly share coded or fully written questions.  Ed questions can be asked anonymously to your fellow students, but course staff can see who posts anonymous questions.

Office hours will be by appointment only (see Canvas Office Hours page), and we will send out a poll to determine the best times for available slots. If you cannot make any of the listed office hours spots and would like to talk directly with Taylor or Vlad, please let us know and we will attempt to find an alternate time. 

• Taylor Kessler Faulkner, instructor

  • Available on Zoom Tuesday 10-11am, Thursday 4:30-5:30pm, Friday 10-11am

• Vlad Murad, TA, 

  • Available on Zoom Monday 5-6pm, Thursday 5-6pm

If you have any concerns about the classroom or course climate, you can contact Taylor directly, refer to the resources listed in the Policies sections, or use the CSE anonymous feedback tool.

Course Links

Please use Ed for course-related questions. We will use Gradescope for assignment submissions. The course Canvas will be used for a gradebook and for sharing lecture recordings and assignment files.

Grades

Your grades for this course will consist of the following:

• Assignments (4), worth 20% each (80% total)

• In-person quizzes (8), worth 20% total

  • Lowest 2 grades dropped

The percentile grades will be translated to a 4 point scale using a linear transformation. For conversion to the 4.0 scale, I guarantee the following minimum grades (we do not make any guarantees of the course grades within these buckets):

• 98% ➔  4.0

• 90% ➔  3.5

• 80% ➔  3.0

• 75% ➔  2.7

Do note that these are only minimum guarantees and do not make any guarantees on how high your grade can be. Missing the requirement to get a particular grade does not make it impossible to earn that grade; we just can’t give you a promise that you will have it. In other words, it is still possible to get a 3.5 even if your percentage is less than 90%, we just can’t make you a guarantee that will happen.

Policies

Academic Integrity

The University takes academic integrity very seriously. Behaving with integrity is part of our responsibility to our shared learning community. If you’re uncertain about whether something is academic misconduct, ask me. I am willing to discuss questions you might have.

Acts of academic misconduct may include but are not limited to:

• Cheating (working collaboratively on quizzes/exams and discussion submissions, sharing answers, and previewing quizzes/exams)

• Plagiarism (representing the work of others as your own without giving appropriate credit to the original author(s))

Concerns about these or other behaviors prohibited by the Student Conduct Code will be referred for investigation and adjudication by CSSC.

Students found to have engaged in academic misconduct may receive no credit for the affected assignment. Stronger penalties, up to and including failing the course, may apply for repeated or egregious violations. In cases of group work, all students will be held equally responsible for violation unless there is clear evidence that a subset of team members were not involved or aware.

Course-specific policies:

• All homework will be turned in electronically. Quizzes may be turned in electronically or on paper, depending on format.

• Assignments should be completed individually unless otherwise specified, but collaboration at a high level is encouraged. You may discuss the subject matter, assignments, and prepare for quizzes with other students in the class, but all final written or coded answers must be your own work. You are expected to maintain the utmost level of academic integrity in the course, pertinent to the Allen School's policy on academic misconduct.

• Each student has six penalty-free late days for the whole quarter. Consecutive days off (weekends or holidays) count as one late day. 

• The maximum late days that can be used per assignment is two.

• You must link pages to questions for written assignments submitted to Gradescope. You will lose 0.25 points off the assignment if you do not do so. (For guidance, watch this Gradescope YouTube video on linking pages to questions.)

Overview: AI is allowed in this course for collaboration in learning, problem-solving, and creating. You may use AI tools for any course work—including assignments, and projects—unless a specific activity states otherwise. Specifically, no AI can be used on quizzes. Use AI actively and thoughtfully: its role is to help you explore, build, test, revise, and deepen your understanding. Read the full policy before using AI so you understand the privacy expectations and any activity-specific restrictions.

Definition of AI: For this policy, "AI" refers to generative AI systems that can produce or modify text, code, images, audio, video, or other content — whether in a single response to a prompt or by operating autonomously across multiple steps (e.g., chatbots such as ChatGPT, Claude, and Gemini; code assistants and agents such as GitHub Copilot, Cursor, and Claude Code; and AI-powered writing, translation, and image-generation tools). This includes AI features built into IDEs, operating systems, or browsers when they generate or substantially rewrite content, but excludes non-generative tools such as basic spell-check, grammar/syntax highlighting, and linters. A tool's ability to act autonomously (e.g., independently writing, running, and debugging code) does not exempt it from this definition.

Rationale: This course treats AI as a full collaborator in the learning process: it can be used to ask questions, explore possibilities, build and debug software, and refine your work. AI can accelerate experimentation and make feedback more available, but you remain responsible for directing the collaboration, evaluating its output, and developing the understanding behind the work you submit. 

Permitted Actions:

• You may use AI tools for any course-related task, including brainstorming, concept explanations, summarization, drafting, coding support, debugging assistance, editing and revision, preparing for quizzes and exams, and completing assignments and projects.

• You are encouraged to use AI collaboratively: ask it to explain its reasoning, propose alternatives, challenge your assumptions, review your work, and help you investigate errors.

• If an activity includes additional restrictions, those restrictions will be stated explicitly.

Prohibited Actions:

• Do not use AI in ways that violate any activity-specific restrictions stated by the instructor.

• Do not represent AI-generated content as independently produced.

• Do not violate data privacy rules.

Examples:

• Allowed: collaborating with AI to brainstorm project ideas, explain a concept, generate an outline, propose test cases, or compare solution approaches.

• Allowed: using AI to help write, debug, document, or improve code for an assignment when no activity-specific restriction applies.

• Allowed: using AI to critique your reasoning or code, then using that feedback to revise your work and strengthen your understanding.

• Allowed: using AI to prepare for a quiz or exam when that activity permits AI use.

• Not allowed: using AI on an activity that explicitly prohibits or limits it.

• Not allowed: uploading restricted course materials or sensitive information to an AI tool.

Required Attribution:

• If you used AI on a graded assignment, include a short note specifying the tool you used and how you used it.

• Example: “I used Claude Code to develop and debug the code for this assignment.”

Guidelines for Effective AI Use:

• Treat AI as an active collaborator: give it context, ask follow-up questions, and use its responses to extend rather than replace your own thinking.

• Check important output, especially code, factual claims, citations, and calculations; AI can be confidently wrong.

• Use AI to explore alternatives, find mistakes, generate tests, and iterate on your work.

• Be prepared to explain and defend work you submit, including choices you made with AI assistance.

• Follow all assignment-specific directions about permitted tools, disclosure, and attribution.

Data Privacy Expectations:

• Do not upload course-specific materials—including assignment prompts, course code, datasets, class notes, hidden tests, solution keys, or other restricted content—to AI tools without the instructor’s explicit approval.

  • Some AI tools (e.g., Cursor, Claude Code, and similar coding agents) can automatically access files beyond what you explicitly share — including your entire local repository, file system, or connected accounts. Before using such a tool, confirm what it can access and restrict or scope that access so it does not read private repositories, hidden test files, other students' code, solution keys, or other restricted materials without your intent.

• Do not submit personal, sensitive, or university-protected information into AI tools.

• Be aware that prompts and outputs may be stored or reused by third-party AI providers.

• UW’s  Purple tool and certain GenAI tools provided by the Allen School for use in courses are designed specifically for UW students and staff and have stronger privacy protections than public commercial tools. When AI usage is permitted, using Purple or Allen School-provided tools is advised if possible.

Academic Integrity: Using AI in ways prohibited by this policy or by assignment-specific instructions will be considered academic misconduct and referred to CSSC. Students found responsible for violating this policy will, at minimum, receive no credit for the affected assignment. Stronger penalties, up to and including failing the course, may apply for repeated or egregious violations. In cases of group work, all students will be held equally responsible for violation unless there is clear evidence that a subset of team members were not involved or aware.

Accommodations and Approved Exceptions: Students with accessibility needs or other extenuating circumstances should contact the instructor to discuss exceptions. Accommodations or exceptions require instructor approval before they are used. 

General Accommodations

If you have any unforeseen or extenuating circumstance that arise during the course, please do not hesitate to contact us to discuss your situation. The sooner we are made aware, the more easily we can address such situations. 

Religious Accommodations

Washington state law requires that UW develop a policy for accommodation of student absences or significant hardship due to reasons of faith or conscience, or for organized religious activities. The UW’s policy, including more information about how to request an accommodation, is available at Religious Accommodations Policy. Accommodations must be requested within the first two weeks of this course using the Religious Accommodations Request form.

Accommodations & Access

Your experience in this class is important to me. It is the policy and practice of the University of Washington to create inclusive and accessible learning environments consistent with federal and state law. If you have already established accommodations with Disability Resources for Students (DRS), please activate your accommodations via myDRS so we can discuss how they will be implemented in this course.

If you have not yet established services through DRS, but have a temporary health condition or permanent disability that requires accommodations (conditions include but not limited to; mental health, attention-related, learning, vision, hearing, physical or health impacts), contact DRS directly to set up an Access Plan. DRS facilitates the interactive process that establishes reasonable accommodations. Contact DRS at disability.uw.edu.

Title IX

UW, through numerous policies, prohibits sex- and gender-based violence and harassment, and we expect students, faculty, and staff to act professionally and respectfully in all work, learning, and research environments. For support, resources, and reporting options related to sex- and gender-based violence or harassment, visit UW Title IX’s webpage, specifically the Know Your Rights & Resources guide. 

If you choose to disclose information to me about sex- or gender-based violence or harassment, I will connect you (or the person who experienced the conduct) with resources and individuals who can best provide support and options. You can also access those resources directly:

• Confidential: Confidential advocates will not share information with others unless given express permission by the person who has experienced the harm or when required by law.

• Private and/or anonymous:  SafeCampus  provides consultation and support and can connect you with additional resources if you want them. You can contact SafeCampus anonymously or share limited information when you call.

Please note that some senior leaders and other specified employees have been identified as “Officials Required to Report.” If an Official Required to Report learns of possible sex- or gender-based violence or harassment, they are required to call SafeCampus and report all the details they have in order to ensure that the person who experienced harm is offered support and reporting options.

Mental health & wellbeing resources

The following wellbeing & mental health resources are available to you on campus: 

• Let’s Talk connects you with support from a counselor without an appointment via drop-in hours.

• The Counseling Center provides you with personal counseling, assessment, referral, and crisis intervention services (206-543-1240).

• Hall Health Mental Health provides you with a range of services to assess and treat mental health concerns including psychiatry and associated medication management support (206-543-5030).

• UW LiveWell provides you with support and case consultation if you are experiencing personal hardship, including academic hardship as the result of extenuating life circumstances (206-543-6085).

• Husky Health & Well-Being provides you with a central online resource for access to health and wellness services across the campus.

• Academic Advising can help if you are experiencing challenges navigating academic commitments.

• SafeCampus is here for you 24/7 if you ever need to privately discuss safety and well-being concerns for yourself or others (206-685-SAFE [7233]). SafeCampus’s team of caring professionals will provide individualized support, while discussing short- and long-term solutions and connecting you with additional resources when requested.

• Forefront Suicide Prevention provides information and services to reduce suicide by empowering individuals and communities to take sustainable action, championing systemic change, and restoring hope (206-543-1016).

• Crisis Clinic: If you or someone you know experiences a crisis outside of business hours, please call the Crisis Clinic at 206-461-3222.

• Food and Housing: If you are experiencing food or housing insecurity, you can start with UW emergency Aid or the UW Food Pantry. If you are concerned about your mental, emotional, or physical safety for yourself or others, call SafeCampus at 206-685-7233 anytime – no matter where you work or study – to anonymously discuss safety and well-being concerns for yourself or others. SafeCampus’s team of caring professionals will provide individualized support, while discussing short- and long-term solutions and connecting you with additional resources when requested.

• Study Centers