Prerequisites: MET CS 521 & MET CS 546; MET CS 579 or MET CS 669; or consent of instructor. - Study basic concepts and techniques of data mining. Topics include data preparation, classification, performance evaluation, association rule mining, regression and clustering. Students learn underlying theories of data mining algorithms in the class and they practice those algorithms through assignments and a semester-long class project using R. After finishing this course, students will be able to independently perform data mining tasks to solve real-world problems.
FALL 2024 Schedule
| Section |
Instructor |
Location |
Schedule |
Notes |
| A2 |
Lee |
HAR 322 |
R 6:00 pm-8:45 pm |
|
FALL 2024 Schedule
| Section |
Instructor |
Location |
Schedule |
Notes |
| A3 |
Lee |
COM 213 |
W 2:30 pm-5:15 pm |
|
FALL 2024 Schedule
| Section |
Instructor |
Location |
Schedule |
Notes |
| O2 |
Joner |
|
ARR 12:00 am-12:00 am |
Students are assigned into class sectionsof about 15 with a member of the teaching team. Please note the prerequisite(s). Completion of the prerequisite course or consent of the instructor is required. F1 student visa holders should contact the MET CS Dept at metcs@bu.edu prior to registering for any online courses. |
SPRG 2025 Schedule
| Section |
Instructor |
Location |
Schedule |
Notes |
| A1 |
Lee |
CAS 326 |
M 6:00 pm-8:45 pm |
|
SPRG 2025 Schedule
| Section |
Instructor |
Location |
Schedule |
Notes |
| A2 |
Lee |
EPC 206 |
W 6:00 pm-8:45 pm |
|
Note that this information may change at any time. Please visit the MyBU Student Portal for the most up-to-date course information.
