COMPSCI 514: Algorithms for Data Science (Fall 2020)

Time: Tue/Thurs 1:00pm-2:15pm
Location: Lecture Zoom. See announcements for password. If you cannot make the live lecture, all lectures will be recorded and posted under the Schedule tab.
Professor: Cameron Musco
Teaching Assistants:
Course Description: With the advent of social networks, ubiquitous sensors, and large-scale computational science, data scientists must deal with data that is massive in size, arrives at blinding speeds, and often must be processed within interactive or quasi-interactive time frames. This course studies the mathematical foundations of big data processing, developing algorithms and learning how to analyze them. We explore methods for sampling, sketching, and distributed processing of large scale databases, graphs, and data streams for purposes of scalable statistical description, querying, pattern mining, and learning. Course was previously COMPSCI 590D. 3 credits.
Prerequisites: The undergraduate prerequisites are COMPSCI 240 (Probability) and COMPSCI 311 (Algorithms). This is a theoretical course with an emphasis on algorithm design, correctness proofs, and analysis. Aside from a general background in algorithms, a strong mathematical background, particularly in linear algebra and probability is required. If you are a masters student with a limited background in either of these subjects, please email me at the start of the semester.
Textbooks: This is no official textbook for this class. We will use some material from:
Related Classes: You may also find some helpful reference material in these similar classes taught at other universities:
Piazza: We will use Piazza for class discussion, questions, and annoucements. Sign up here. We hope for Piazza to be one of the main interactive components of the class. Thus, we encourage posting and good answering of other students' questions as part of up to 5% extra credit for class participation (see below).
Problem Sets: Problem sets can be completed in groups of up to three students. If you work in a group, you submit a single problem set together. You may talk to people not in your group about the problem sets at a high level, but may not work through the detailed solutions together, write them up together, etc. We very strongly encourage you to work in a three person group, as it will give an advantage in doing the problem sets. At the beginning of the semester we will make a Piazza post where you can look for teammates. We will also have random breakouts during lecture so that you can get to know some of your classmates.
Weekly Quizzes: A quiz will be posted on Piazza each Thursday after class, due the following Monday at 8pm. These are very short quizzes (designed to take ~15 minutes) to check that you are following the material and help me make adjustments if needed. Quizzes will include check-in questions asking for feedback on class pacing and on topics that need clarification, or that you would like to see discussed more.
Exams: The midterm and final will be take home, open note exams. For each, you will have a 1.5 hour window to complete the exam during a 48 hour period. The midterm will be October 8th-9th. The final will be December 1st-2nd.
Class Participation: Up to 5% extra credit may be awarded for class participation. This may come in many forms, e.g.:
Academic Honestly: If caught violating the problem set or quiz rules, students will receive a 0% on the assignment for the first violation, and fail the class for a second violation. Any cheating on the midterm or final will lead to failing the class. For fairness, we apply these rules universally, without exceptions.
Disability Services: UMass Amherst is committed to making reasonable, effective, and appropriate accommodations to meet the needs to students with disabilities and help create a barrier-free campus. If you have a documented disability on file with Disability Services, you may be eligible for reasonable accommodations in this course. If your disability requires an accommodation, please notify me within the first two weeks of the course so that we may make arrangements in a timely manner.
Helpful UMass Resources: