CS 247

CS 247: Advanced Data Mining

Instructor: Yizhou Sun

Office hours: Mondays 3pm-5pm @ zoom

TA: Ziniu Hu (bull@cs.ucla.edu)

Office hours: Fridays 3-5pm @ zoom

Lecture times: T/Th 10am-11:50am

Lecture location: zoom

Academic Integrity Policy

About the Course

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, graph/network mining, and recommender systems. 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.

Learning Objectives

Review and understand fundamentals of basic data mining techniques
Learn recent data mining techniques on several advanced data types
Develop skills to apply data mining algorithms to solve real-world applications
Gain initial experience in conducting research on data mining

Schedule

Prerequisites

Required prerequisite courses: CS 145 or CS 146 or equivalent.
You are expected to have background knowledge in data structures, algorithms, basic linear algebra, and basic statistics.
You are expected to know basic knowledge in data mining and machine learning.
You will also need to be familiar with at least one programming language, and have programming experiences.

Grading

Homework: 50%
Quizzes: 15%
Course project: 35%

*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.

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 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/spring2020/cs247

Academic Integrity Policy

"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.

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