Corequisite: MET AD 100 Lab - This course presents fundamental knowledge and skills for applying business analytics to managerial decision-making in corporate environments. Topics include descriptive analytics (techniques for categorizing, characterizing, consolidating, and classifying data for conversion into useful information for the purposes of understanding and analyzing business performance), predictive analytics (techniques for detection of hidden patterns in large quantities of data to segment and group data into coherent sets in order to predict behavior and trends), prescriptive analytics (techniques for identification of best alternatives for maximizing or minimizing business objectives). You will learn how to use data effectively to drive rapid, precise, and profitable analytics-based decisions. The framework of using interlinked data inputs, analytics models, and decision-support tools will be applied within a proprietary business analytics shell and demonstrated with examples from different functional areas of the enterprise. R and Power BI software are used.
FALL 2026 Schedule
| Section |
Instructor |
Location |
Schedule |
Notes |
| A1 |
Yu |
STH B22 |
M 6:00 pm-8:45 pm |
|
FALL 2026 Schedule
| Section |
Instructor |
Location |
Schedule |
Notes |
| A2 |
Ritt |
MET 122 |
T 12:30 pm-3:15 pm |
|
FALL 2026 Schedule
| Section |
Instructor |
Location |
Schedule |
Notes |
| A3 |
Parzen |
CDS 264 |
W 2:30 pm-5:15 pm |
|
FALL 2026 Schedule
| Section |
Instructor |
Location |
Schedule |
Notes |
| A4 |
Page |
CAS 201 |
R 6:00 pm-8:45 pm |
|
FALL 2026 Schedule
| Section |
Instructor |
Location |
Schedule |
Notes |
| O1 |
Parzen |
|
ARR 12:00 am-12:00 am |
|
SPRG 2027 Schedule
| Section |
Instructor |
Location |
Schedule |
Notes |
| A1 |
Page |
|
M 2:30 pm-5:15 pm |
|
SPRG 2027 Schedule
| Section |
Instructor |
Location |
Schedule |
Notes |
| A3 |
Parzen |
|
W 6:00 pm-8:45 pm |
|
SPRG 2027 Schedule
| Section |
Instructor |
Location |
Schedule |
Notes |
| O1 |
Parzen |
|
ARR 12:00 am-12:00 am |
Prereq: AD100, ADR100
Students are assigned to class sections of about 20 with a member of the teaching team.
F1 student visa holders should contact the MET Administrative Science Department: adminsc@bu.edu before registering for any online class |
Note that this information may change at any time. Please visit the MyBU Student Portal for the most up-to-date course information.