Curriculum Checklist
Fall start only.
Print and fill out this page to help keep track of your progress throughout your graduate career in ISOM.
Fall (module 1)
| Course | Credits | Grade |
|---|---|---|
| ISM6128 Advanced Business Systems Design & Development I | 2 | |
| ACG5005 Financial Accounting | 2 | |
| MAR5806 Problems & Methods in Marketing Management | 2 | |
| GEB5212 Professional Writing | 1 | |
| QMB6938 Analytics Processes for Business Bootcamps | 1 |
Fall (module 2)
| Course | Credits | Grade |
|---|---|---|
| QMB6358 Statistical Analysis for Managerial Decisions | 2 | |
| ISM6215 Business Database Systems I Prerequisite: C or higher in ISM6128 | 2 | |
| ACG5075 Managerial Accounting Prerequisite: ACG5005 | 2 | |
| MAR6930† Marketing Analytics I Prerequisite: MAR5806 | 2 | |
| QMB6942 Analytics Practicum I Prerequisite: Analytics Bootcamp | 1 |
† Indicates optional electives. Students must choose at least 6 of these for a total of 12 credits in order to graduate.
Spring (module 3)
| Course | Credits | Grade |
|---|---|---|
| ISM6405 Intro to Business Intelligence Prerequisite: C or higher in ISM6215 and in ISM6358 | 2 | |
| ISM6930 Intro to Python | 2 | |
| FIN5437† Corporate Finance I | 2 | |
| MAN6366† Organizational Staffing | 2 | |
| QMB6943 Analytics Practicum II | 1 |
† Indicates optional electives. Students must choose at least 6 of these for a total of 12 credits in order to graduate.
Spring (module 4)
| Course | Credits | Grade |
|---|---|---|
| ISM6423† Data Mining for Business Intelligence Prerequisite: C or higher in ISM6405 | 2 | |
| ISM6562† Business Data Presentation & Visualization Prerequisite: C or higher in ISM6215 | 2 | |
| ACG7848† Data Analysis and Skills Prerequisite: Intro to Python ISM | 2 | |
| MAR6930† Marketing Analytics II Prerequisite: Marketing Analytics I | 2 | |
| GEB5215‡ Professional Communications | 1 | |
| QMB6944 Analytics Practicum III | 1 |
† Indicates optional electives. Students must choose at least 6 of these for a total of 12 credits in order to graduate.
‡ Indicates optional timing for GEB5215. Students can choose to take this either in Spring or Summer.
Summer (module 5)
| Course | Credits | Grade |
|---|---|---|
| QMB6755† Managerial Quantitative Analyses | 2 | |
| FIN6930† AI & ML Applications for Finance & FINTECH | 2 | |
| ISM6304† Artificial Intelligence Methods Prerequisite: Intro to Python | 2 | |
| ACG7849† Web Crawling & Text Analysis Prerequisite: Intro to Python | 2 | |
| GEB5215‡ Professional Communications | 1 |
† Indicates optional electives. Students must choose at least 7 of these for a total of 14 credits in order to graduate.
‡ Indicates optional timing for GEB5215. Students can choose to take this either in Spring or Summer.
(36 credits needed)
Students must maintain an Overall and Major GPA of 3.0+ to qualify for graduation.