Fall 2019 - CMPT 843 G100
Database and Knowledge-base Systems (3)
Class Number: 10537
Delivery Method: In Person
An advanced course on database systems which focuses on data mining and data warehousing, including their principles, designs, implementations, and applications. It may cover some additional topics on advanced database system concepts, including deductive and object-oriented database systems, spatial and multimedia databases, and database-oriented Web technology.
The purpose of this graduate course is twofold: broadening graduate students' knowledge and understanding of the current frontiers of data analytics and management research, and teaching data analytics and data mining research methodologies and skills. In this semester, we will focus on computational statistics and applications. Specifically, we will cover some fundamental and useful ideas and methods, including sampling, EM optimization methods, simulation, bootstrapping, and density estimation, as well as their programming implementation. Since it is an advanced graduate course, sufficient preparation and interest in data analytics (i.e., database systems and data mining) and solid undergraduate entry level statistics are assumed. The course itself uses mathematics and probability heavily..
- Optimization and simulation
- EM methods
- Density estimation
- Distributed optimization and data mining
Grading will be announced in the first week of the class. Evaluation will be based on assignments, exams and projects.
Readings in Database Systems, 4th Edition, Peter Bailis, Joseph M. Hellerstein, Michael Stonebraker, 9780262693141, http://www.redbook.io/
Graduate Studies Notes:
Important dates and deadlines for graduate students are found here: http://www.sfu.ca/dean-gradstudies/current/important_dates/guidelines.html. The deadline to drop a course with a 100% refund is the end of week 2. The deadline to drop with no notation on your transcript is the end of week 3.
SFU’s Academic Integrity web site http://www.sfu.ca/students/academicintegrity.html is filled with information on what is meant by academic dishonesty, where you can find resources to help with your studies and the consequences of cheating. Check out the site for more information and videos that help explain the issues in plain English.
Each student is responsible for his or her conduct as it affects the University community. Academic dishonesty, in whatever form, is ultimately destructive of the values of the University. Furthermore, it is unfair and discouraging to the majority of students who pursue their studies honestly. Scholarly integrity is required of all members of the University. http://www.sfu.ca/policies/gazette/student/s10-01.html
ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS