Course Description
Study of advanced and emerging techniques and methods of business analytics, including gathering, processing and analyzing large volumes of data to generate insights that inform business decisions. Prerequisite: ISM 240, (ECO 250 or STA 108), and (ISM 218 or ACC 325); ISSC Major or CYMA Major or ACCT Major.
Syllabus
Student Learning Outcomes, Goals, Objectives:
Students successfully completing this course will be able to:
- Demonstrate an understanding of Advanced Business Analytics for decision-making
- Identify, design and assess different business analytics methodologies
- Demonstrate proficiency in the fundamentals of Python for analytics applications
- Explore and develop AI based descriptive, including data visualization and predictive analytic models
Course Grading Information:
| Activity/Performance Measure | Percentage/Points |
|---|---|
| Python Training Assignment(s) | 200 points |
| Descriptive Analytics Assignment(s) | 200 points |
| Predictive Analytics Assignment(s) | 200 points |
| Clustering Assignment(s) | 200 points |
| Final Exam | 200 points |
| Total | 1000 points |
The letter grade will be based on the following distribution:
Grading Scale
| Percentage | Letter Grade |
|---|---|
| 940-1000 points | A |
| 900-939 points | A- |
| 870-899 points | B+ |
| 840-869 points | B |
| 800-839 points | B- |
| 770-799 points | C+ |
| 740-769 points | C |
| 700-739 points | C- |
| 670-699 points | D+ |
| 640-669 points | D |
| 610-639 points | D- |
| 0-609 points | F |
* Grades are truncated, not rounded.
Attendance/Participation:
Late/ missed assignments: It is your responsibility to communicate in advance with the professor if you anticipate missing assignments, exams, or other coursework due to university - approved excuse.
Course Materials Purchased by the Students:
No course materials are required.
Scholarly Perspectives
This course engages diverse scholarly perspectives to develop critical thinking, analysis, and debate and inclusion of a reading does not imply endorsement.