## CS 249: Special Topics - Advanced Data Mining

Instructor: Yizhou Sun

• Office hours: M/W 4:00pm-5:00pm

TA: Jae LEE (jlee734@ucla.edu)

• Office hours: 3-5pm Tuesdays @BH 2432

Lecture times: M/W 2pm-3:50pm
Lecture location: 5436 BH

Description: This course introduces concepts, algorithms, and techniques of data mining on different types of datasets, which covers basic data mining algorithms, as well as advanced topics on text mining, recommender systems, and graph/network mining. A team-based course project involving hands-on practice of mining useful knowledge from large data sets is required, in addition to regular assignments. The course is a graduate-level computer science course, which is also a good option for senior undergraduate students who are interested in the field, as well as students from other disciplines who need to understand, develop, and use data mining systems to analyze large amounts of data.

### Prerequisites

• You are expected to have background knowledge in data structures, algorithms, basic linear algebra, and basic statistics.
• You will also need to be familiar with at least one programming language, and have programming experiences.

• Homework: 30%
• Midterm exam: 30%
• Course project: 35%
• Participation: 5%

*All the deadlines are 11:59PM (midnight) of the due dates.

*Late submission policy: you will get original score* $\mathbf{1}(t<=24)e^{-(ln(2)/12)*t}$, if you are t hours late.

*No copying or sharing of homework!

• But you can discuss general challenges and ideas with others.
• Suspicious cases will be reported to The Office of the Dean of Students.

Q & A

This term we will be using Piazza for class discussion. The system is highly catered to getting you help fast and efficiently from classmates, the TA, and myself. Rather than emailing questions to the teaching staff, I encourage you to post your questions on Piazza.