## CS 145: Introduction to Data Mining

Instructor: Yizhou Sun

• Office hours: Wednesdays 3:00pm-5:00pm @BH 3531E

TAs:

• Yunsheng Bai (yba@cs.ucla.edu), office hours: 1-3pm Thursdays @BH 3256S
• Junheng Hao (haojh.ucla@gmail.com), office hours: 9:30-11:30am Tuesdays @BH 3256S
• Shengming Zhang (michaelzhang@cs.ucla.edu), office hours: 3-5pm Mondays @BH 3256S

Lecture times: M/W 12:00pm-1:50pm
Lecture location: Franz Hall Room 1260

Description: This course introduces basic concepts, algorithms, and techniques of data mining on different types of datasets, including (1) vector data, (2) set data, (3) sequence data, and (4) text data. The class project involves hands-on practice of mining useful knowledge from large data sets. The course is an undergraduate-level computer science course. Also, the course may attract students from other disciplines who need to understand, develop, and use data mining techniques 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: 25%
• Midterm exam: 25%
• Final exam: 20%
• Course project: 25%
• 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

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