Please Note
It is your responsibility to make sure you read and understand the contents of this syllabus. If you have any questions, please contact the instructor.
Table of contents
- Basic Course Information
- Course Description
- Credits
- Instructors
- Academic Integrity
- COVID-19
- Pre-requisites
- Learning Outcomes
- References
- Schedule
- Piazza
- Grading Policy
- Semester-long Project
- Attendance
- Bonus
- Accessibility Resources
- Critical Campus Resources
- Preferred Name
- Diversity
- Suggestions or Comments?
Basic Course Information
- Spring 2026 course
Lecture
- Times: Mondays and Wednesdays, 11:30am-12:50pm
- Location: Davis 113A
- Office Hours: * Fridays, 12:30-1:30PM, Davis 335
Recitation
- Times: Wednesdays, 2-2:50pm
- Location: Davis 113A
Course Description
Introductory mathematics course assuming minimal mathematical background (non-calculus based) that introduces the foundations of math necessary to understand machine learning and AI technologies. This course is designed for students who do not plan to major in math or engineering. Key topics will include basic linear algebra and probability grounded in real world examples of the use and interpretation of these techniques in AI applications.
Credits
4 credits
Instructors
It is preferable to set up an appointment (by email) if you want to talk to me outside of my office hours.
Academic Integrity
Penalty for Violations
In accordance with the current departmental policy on academic integrity violations, we will follow this procedure in AI220:
- If the violation is the student’s second academic violation, then it will result in an automatic
Fletter grade in the course. - If the violation is the first ever academic violation, then it will result in a minimum of a
letter grade reductionin the grade for course andzero in the relevant assignment. If the violation is serious enough, then it can result in anF in the course. While it gives us no pleasure in failing students, we will do so since we have to be fair to (the vast majority) of students who do not cheat.
Generative AI Policy
In short, the course policy for the use of Generative AI is that any use of a Generative AI tool for any purpose in the tool must be explicitly approved by Kenny (note: If I tell you to use it, e.g., on a specific homework problem, this counts as “explicit approval,” you don’t need to ask :) ). This includes, but is not limited to, the need for explicit approval to use Generative AI tools (e.g. ChatGPT) to help with writing and to ideate on projects.
GenAI Policy
Failure to follow this policy will result in a violation of the Academic Integrity rules for this course.
I reserve the right to use in-class assessments to assess the extent to which you are capable of explaining your own responses on your own homework assignments.
Some notes on this policy:
- This is not me saying that the use of Generative AI is off limits (indeed at various points in the class you will explicitly have to think about generative AI), but rather that there are good and bad uses from an instructional perspective, and I want to discuss these uses with you.
- I am unlikely to approve the use of Generative AI to “fix” one’s writing - we’d rather just see your writing, imperfections and all, than a filtered version of it!
Policy on improper distribution of course materials
All materials prepared and/or assigned by me for this course are for the students’ educational benefit. Other than for permitted collaborative work, students may not photograph, record, reproduce, transmit, distribute, upload, sell or exchange course materials, without our prior written permission. “Course materials” include, but are not limited to, all instructor-prepared and assigned materials, such as lectures; lecture notes; discussion prompts; study aids; tests and assignments (and their solutions); and presentation materials such as PowerPoint slides, Prezi slides, or transparencies; and course packets or handouts. Public distribution of such materials may also constitute copyright infringement in violation of federal or state law. Violation of this policy may additionally subject a student to a finding of “academic dishonesty” under the Academic Integrity Policy and/or disciplinary charges under the Student Code of Conduct. For more details, please see the undergrad department policy on academic integrity, and/or the graduate policy.
COVID-19
Please follow UB/SUNY protocols regarding COVID-19. This page has an overview of updates and policies .
Specifically, please note that following parts of the If you are sick, monitoring health :
If students need to miss class, an exam, work or an assignment due to illness and isolation, they must notify their instructor and/or supervisor as soon as possible and no later than 24 hours.
Lectures, presentations and office hours will be held in-person. These are subject to change based on current UB/SUNY policies.
Pre-requisites
For all sections, willingness to think beyond your usual boxes and openness to unfamiliar ideas will be crucial.
Otherwise, this course assumes that students have successfully reached a level of mathematics equivalent to MTH 114: Precalculus.
Learning Outcomes
| Outcome | Method of Assessment |
|---|---|
| Be able to define a vector and understand its relationship to linear systems | Quizzes, Project, Final |
| Understand how to calculate the norm of a vector and the distance between vectors | Quizzes, Project, Final |
| Be able to define a matrix and calculate its properties | Quizzes, Project, Final |
| Understand sets and how to calculate probabilities in basic discrete and continuous models | Quizzes, Project, Final |
| Be able to calculate probabilities in counting problems | Quizzes, Project, Final |
| Be able to identify discrete and continuous probability distributions | Quizzes, Project, Final |
| Apply the concepts learned in the course to analyze real-world data sets | Project |
References
- Introduction to Applied Linear Algebra – Vectors, Matrices, and Least Squares by Stephen Boyd and Lieven Vandenberghe. Textbook freely available online
- Introduction to Probability, Second Edition by Joseph K. Blitzstein and Jessica Hwang . Textbook freely available online.
- We will use several other resources as well!
Schedule
See the schedule page
Piazza
We will be using Piazza for all AI 220 related announcements. If you are attending the course, you must check Piazza regularly. We would strongly urge you to enable email notifications on piazza (it is on by default). These announcements will include the ones that inform if and when classes/office hours are re-scheduled etc.
We will also be using Piazza for class discussion. The system is highly catered to getting you help fast and efficiently from classmates and myself. Rather than emailing questions to the teaching staff, we encourage you to post your questions on Piazza. If you have any problems or feedback for the developers, email team@piazza.com. To familiarize yourself with the system, look at their help page .
You should be signed up for Piazza by now. If for some reason that did not work, please go to the Piazza sign up page .
Few other points:
- You can post anonymously but note that you will be anonymous to students only. Your identity will be known to the instructors.
- Please make sure that you use your UB email to sign up– this is to make sure that we can verify your identity if necessary.
- You can write posts that are private to just the instructors but if we feel that the answer would be relevant to the class then we reserve the right to make the post public. (If you would like not to have your name in the public version of your private post, please post anonymously in the private post too. Note by the first point, we will still know your identity.)
Grading Policy
Here is the split of grades:
| Course Component | $\%$ of grade |
| Project Interview 1 | $10\%$ |
| Project Interview 2 | $10\%$ |
| Final Project Presentation | $15\%$ |
| Quizzes | $40\%$ ($10\%$ per quiz, dropping the lowest) |
| Attendance | $25\%$ (with important caveats, see below) |
| Bonus | Up to $5\%$ |
See the next few sections for more details on each of the above components.
Letter Grades
| Grade | Quality Points | Percentage |
| $A$ | 4.0 | 85.0% or more |
| $A^-$ | 3.67 | 75.0% - 84.95% |
| $B^+$ | 3.33 | 70.0% - 74.95% |
| $B$ | 3.00 | 65.0% - 69.95% |
| $B^-$ | 2.67 | 60.0% - 64.95% |
| $C^+$ | 2.33 | 55.0% - 59.95% |
| $C$ | 2.00 | 50.0% - 54.95% |
| $C^-$ | 1.67 | 45.0% - 49.95% |
| $D^+$ | 1.33 | 40.0% - 44.95% |
| $D$ | 1.00 | 35.0% - 39.95% |
| $F$ | 0 | 34.95% or below |
Changing cutoffs
We reserve the right to change the cutoffs depending on overall class performance. However, we will only move the cutoffs down. In other words, in case you are in a certain percentage range in the last column in the table above, then the letter grade in the corresponding first column is the minimum letter grade you will receive.
Incompletes
Incompletes (the grade of “I”) will not in general be given. This is reserved for the rare circumstance that prevents a student from completing the work in the course. University and Department policy dictates that an “I” can be given only if both of the following conditions are met: (i) only a small amount of work remains, such as the final exam and one or two assignments, and (ii) the student has a passing average in the work completed. In such a circumstance, the student will be given instructions and a deadline for completing the work, which is usually no more than 30 days past the end of the semester. Please see the UB catalog link for more.
Semester-long Project
For details on the project, including grading, see the Project page
Attendance
Read carefully!
Attendance is critical in this class, and thus the attendance policy is strict. Make sure you read the attendance policy carefully!
Meaning of “excused absence
When we say “excused absence” below, we are referring to absences that are excused under the official UB Policy.
Attendance points are all or nothing. Moreover, violating the attendance policy means that your grade in the course will be at most a B+. To receive full points (and avoid the letter grade limit), you cannot miss more than three classes. This includes the late policy and leave-early policy below. Excused absences still count as missed classes, this is why we allow you to miss three! If you have an exceptional circumstance in which 1) all of your absences are excused, and 2) you miss more than three classes, we will address the issue at that point.
Late Policy
We understand that sometimes it might be hard to get to class on time but if you are more than three (3) minutes late, you will be considered late to the class. Two lates will be counted as one absence.
Leave Early Policy
If you just leave the class before it ends, then you will lose the attendance for that day as well.
Bonus
In addition to the bonus opportunities mentioned above, there will be other explicit opportunities to get more bonus points (e.g. your groups could present your project on the CSE Demo day on the last Friday of the semester). The list of the bonus opportunities will be listed on the Bonus page (though it is possible that we might forget to put something on the page even after we announced it in class– if so please send us a reminder!).
You can accumulate up to 500 bonus points. As mentioned above, these $500$ bonus points will translate into $5\%$ of your grade.
Accessibility Resources
If you have a diagnosed disability (physical, learning, or psychological) that will make it difficult for you to carry out the course work as outlined, or that requires accommodations such as recruiting note-takers, readers, or extended time on exams or assignments, you must consult with Accessibility Resources (: 60 Capen Hall, : 645-2608, TTY: 645-2616, : 645-3116).
You must advise your instructor during the first two weeks of the course so that we may review possible arrangements for reasonable accommodations.
Critical Campus Resources
Sexual Violence
UB is committed to providing a safe learning environment free of all forms of discrimination and sexual harassment, including sexual assault, domestic and dating violence and stalking. If you have experienced gender-based violence (intimate partner violence, attempted or completed sexual assault, harassment, coercion, stalking, etc.), UB has resources to help. This includes academic accommodations, health and counseling services, housing accommodations, helping with legal protective orders, and assistance with reporting the incident to police or other UB officials if you so choose. Please contact UB’s Title IX Coordinator at 716-645-2266 for more information. For confidential assistance, you may also contact a Crisis Services Campus Advocate at 716-796-4399.
Mental Health
As a student you may experience a range of issues that can cause barriers to learning or reduce your ability to participate in daily activities. These might include strained relationships, anxiety, high levels of stress, alcohol/drug problems, feeling down, health concerns, or unwanted sexual experiences. Counseling, Health Services, and Health Promotion are here to help with these or other issues you may experience. You can learn more about these programs and services by contacting:
Counseling Services
120 Richmond Quad (North Campus), 716-645-2720
Health Services
4350 Maple Road (at Sweet Home Rd.) , 716-829-3316
Health Promotion
114 Student Union (North Campus), 716-645-2837
Preferred Name
If you would like to be addressed by a name that is different from the one in UB records, please let us know and we will use your preferred name in our communications with you. Further, you will be able to use your preferred name in all of your submissions.
Diversity
The UB School of Engineering and Applied Sciences considers the diversity of its students, faculty, and staff to be a strength, critical to our success. We are committed to providing a safe space and a culture of mutual respect and inclusiveness for all. We believe a community of faculty, students, and staff who bring diverse life experiences and perspectives leads to a superior working environment, and we welcome differences in race, ethnicity, gender, age, religion, language, intellectual and physical ability, sexual orientation, gender identity, socioeconomic status, and veteran status.
Suggestions or Comments?
We would be happy to get feedback from you. You can either talk/send email to Kenny and/or Atri, or use piazza .