Instructor: Yizhou Sun
Lecture times: M/W 10am-11:50am
Lecture location: zoom
Office hours: Mondays 3:30pm-5:30pm @ zoom
TAs:
Junheng Hao (haojh.ucla@gmail.com), Office hours: Thursdays 8:30-10:30 AM @ zoom
Zijie Huang (zijiehuang@cs.ucla.edu), office hours: Mondays 1:00pm-3:00pm @ zoom
Yue Wu (arielwu@cs.ucla.edu), office hours: Tuesdays 7:00-9:00 pm @ zoom
Shichang Zhang (shichang@cs.ucla.edu), office hours: Wednesdays 1:30-3:30pm @ zoom
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.
Know what data mining is and learn the basic algorithms
Develop skills to apply data mining algorithms to solve real-world applications
Gain initial experience in conducting research on data mining
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 will be given in Python (Jupyter Notebook), and course project can be done in any programming language.
Homework: 30%
Midterm exam: 20%
Final exam: 15%
Course project: 25%
Participation: 10%
*All the deadlines are 11:59PM (midnight) of the due dates.
*Late submission policy: you will get a discount as above, 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.
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.
Find our class page at: piazza.com/ucla/fall2020/cs145
"With its status as a world-class research institution, it is critical that the University uphold the highest standards of integrity both inside and outside the classroom. As a student and member of the UCLA community, you are expected to demonstrate integrity in all of your academic endeavors. Accordingly, when accusations of academic dishonesty occur, The Office of the Dean of Students is charged with investigating and adjudicating suspected violations. Academic dishonesty, includes, but is not limited to, cheating, fabrication, plagiarism, multiple submissions or facilitating academic misconduct."
For more information, please refer to the guidance.