AMAT 584: Topological Data Analysis II — Spring 2022

 Classroom  Earth Science 143
 Class hours  MW 11:40am—1:00pm
 Professor  Boris Goldfarb
 Office  ES (Earth Science) 115
 Office hours  M 9:00am—10:30am, W 10:00am—11:30am
 Telephone  518-442-4633 (leave a message)
 Email address  bgoldfarb at albany.edu
 WWW page  https://www.albany.edu/~goldfarb/

About the course: This course is part of the graduate program, Master of Science in Data Science in the Mathematics and Statistics Department. The purpose of this course to introduce topological data analysis including the theoretical foundations and various implementations of the methods.

Reading/Homeworks/Tests: There is no appropriate text for this course. I will be writing and distributing notes. I plan to do that one section at a time, ahead of the days that we cover the material in class. You can read the handout before or after each lecture. There will be 20 sections. Each section will contain problems to solve. That will be the official homework. I will collect the homework and grade it. We can also discuss the homework problems in class, so definitely bring any questions to class. As you can see there will be no in-class tests.

Grades: The course letter grades will be based on the total score obtained from the homework grades:

    10 homeworks =  100% (each homework is worth 10 points)

The rule regarding the homework due dates this semester will be as follows. I encourage you to start solving the problems as soon as we start reading from a section. I will announce in class when a collection from 2 sections are due to be submitted for grading. The policy regarding the late homework is this: if it is turned in within 24 hours after the BEGINNING of the class it's due, the perfect score will be reduced to 8 points, within between 24 and 48 hours to 6 points, and so on.


The following information is added to satisfy the Minimum Contents of a Class Syllabus requirements. The prerequisite for this class is AMAT 583 or background in algebraic topology. You need to be admitted to the graduate program in mathematics or data science or talk to me to get a permission to register. The course is A-E graded. Attendance is critical to success in the class. Doing and turning in homework too. You are expected to follow the University's Standards of Academic Integrity and Medical Excuse Policies.