Policies, grading, and resources

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Grading

Throughout the semester, students work together in small groups on a machine learning project that illustrates the concepts discussed in class and in the readings. Graded components:

Component Weight
Written scope and project proposal 10%
Peer reviews of three project proposals 5%
Project progress updates 25%
Final group presentation 10%
Written final report and code 25%
Class attendance and participation 20%
Weekly check-in and feedback forms 5%

Deliverable descriptions live on the project page.

Your responsibilities

Attendance

Much of this course is focused on discussion with your classmates, so attending each session matters both for what you get out of the course and for what others get out of it. You're expected to attend every session, and participation factors into your grade as described above. If something comes up that requires you to miss a class — illness, conferences, and so on — please let one of the course staff know in advance.

Academic integrity

Violations of class and university academic integrity policies will not be tolerated. Any instance of copying, cheating, plagiarism, or other academic integrity violation will be reported to your advisor and the dean of students, in addition to resulting in immediate failure of the course.

Data security

The data used for project work in this course is sensitive, and care must be taken to protect the privacy of the people in it.

The data must remain in the secure computing environment provided for the course. Any attempt to download any portion of the project data to a machine outside this environment will result in automatic failure of the class. You may use tools like SQL clients and Jupyter notebooks to interact with the data on the remote servers, but you may not save the dataset — or any portion of it — to disk on a local machine.

Additionally, take care to avoid accidentally committing raw data, queries containing identifiable information, or secrets (key files, database passwords, and so on) to GitHub. If this happens, or if you have any reason to believe your personal computer or private key has been compromised, notify the course staff immediately.

AI use policy

We want this class to reflect what solving problems with ML in the real world looks like, which means different policies depending on (1) where you're working, (2) the data you're using, and (3) the privacy and confidentiality requirements involved. For the data we're using in this class, don't share or upload any confidential data or information to any AI tool on the web. Beyond that, you can use any tool you want. You're accountable for the output and the work you submit. Know that a lot of these models are trained on pretty bad ML code and practices :)

We also want this class to help you understand what AI tools are good for, where they fall short, and how to use them best to solve real-world problems. So use them — but be skeptical, review and test the output, and be ready to share what you find with others in the class.

tl;dr

Phones, laptops, and devices

Because much of the work in this course involves group discussion and responding thoughtfully to your colleagues' progress reports, mobile devices are not permitted during class. If you have a disability or other reason that necessitates the use of a mobile device, please speak with one of the instructors or teaching assistants.

Support and resources

Writing and communication

The Global Communication Center (GCC) can help with the written and oral communication assignments in this class. It's free, open to all students, and located in Hunt Library.

Students with disabilities

We value inclusion and will work to ensure that all students have the resources they need to fully participate in our course. Please use the Office of Disability Resources' online system to notify us of any necessary accommodations as early in the semester as possible. If you suspect you have a disability but are not yet registered with the Office of Disability Resources, contact them at access@andrew.cmu.edu.

Health and wellness

As a student, you may experience a range of challenges that can interfere with learning, such as strained relationships, increased anxiety, substance use, feeling down, difficulty concentrating, or lack of motivation. These concerns or stressful events may diminish your academic performance and reduce your ability to participate in daily activities. CMU services are available, and treatment does work.

All of us benefit from support during times of struggle. There are many helpful resources available on campus, and an important part of the college experience is learning how to ask for help. Asking for support sooner rather than later is almost always helpful.

If you or anyone you know experiences academic stress, difficult life events, or feelings like anxiety or depression, we strongly encourage you to seek support. Counseling and Psychological Services (CaPS) is here to help: call 412-268-2922 or visit cmu.edu/counseling. Consider reaching out to a friend, faculty member, or family member you trust for help getting connected to support.

If you or someone you know is in distress or in danger, call someone immediately, day or night:

Discrimination and harassment

Everyone has a right to feel safe and respected on campus. If you or someone you know has been impacted by sexual harassment, assault, or discrimination, resources are available. You can make a report by contacting the University's Office of Title IX Initiatives by email (tix@andrew.cmu.edu) or phone (412-268-7125).

Confidential reporting services are available through Counseling and Psychological Services and the University Health Center, as well as the Ethics Reporting Hotline at 877-700-7050 or reportit.net (username: tartans, password: plaid).

Learn more at the Title IX Office website.

Student Academic Success Center (SASC)

SASC creates spaces for students to engage with their coursework through group and individual tutoring options, and offers free workshops open to the CMU community. Programs include: