Math 372, Practical Machine Learning, Spring 2026

Section 34590

MW 10:10-12:05, 3N-113

Important Dates (http://www.csi.cuny.edu/currentstudents/academiccalendars/)

Text: An Introduction to Statistical Learning, James et al.

Syllabus: Syllabus (http://www.math.csi.cuny.edu/~maher/teaching/2026/spring/ml/official-372-syllabus.pdf).

Homework: Homework will sent out by email and posted on the website.

Exams: There will be a midterm during the semester and a final exam at the end of the semester. You must take the final exam at the time scheduled by the university. You may not use a phone or calculator with symbolic algebra capability during exams.

• Midterm: Wed Mar 25
• Final: TBA

At the instructor’s discretion, any written exam may be replaced by an oral exam.

Grading: The course grade will be determined as follows:

HW: 30%, Midterm 30%, Final 40%

You must take the final exams at the time scheduled by the university.

Method of Study: Optimal Method of Study: (1.) Come to class (attendance is mandatory). (2.) Read the relevant sections after class. (3.) Do the homework. (4.) Compare your solutions with other students. (5.) Come to office hours or the help room with any remaining questions.

Help: Email is the best way to contact me. Come and see me during my office hours! Free math tutoring is also available (http://www.math.csi.cuny.edu/Students/Tutoring).

Attendance: Attendance is mandatory.

Disability policy: Qualified students with disabilities will be provided reasonable academic accommodations if determined eligible by the Office for Disability Services. Prior to granting disability accommodations in this course, the instructor must receive written verification of student’s eligibility from the Office of Disability Services, which is located in 1P-101. It is the student’s responsibility to initiate contact with the Office for Disability Services staff and to follow the established procedures for having the accommodation notice sent to the instructor.

Integrity policy: CUNY’s Academic Integrity Policy is available online at https://www.csi.cuny.edu/sites/default/files/pdf/privacy/cuny_academic_integrity.pdf