Courses & Curriculum
On-Campus
The curriculum for this 10-month program consists of 36 credits (20 core credits and 16 elective credits). In Fall/Spring, courses are taught in 8-week modules. In Summer A courses are taught in 6 weeks.
Students also participate in a practicum, working with real companies and using their data to help solve problems.
Upon completion of the required curriculum, students are awarded a Master of Information Systems and Operations Management with a concentration in Business Analytics.
Online
The curriculum for this two-year program consists of 36 credits (20 core credits and 16 elective credits). In Fall/Spring, courses are taught in 8-week modules. In Summer A courses are taught in 6 weeks.
Most graduate business courses are worth 2 credits. The weekly time commitment varies by course. For a two-credit course, students will typically spend between 6-10 hours per week on lectures, readings, and assignments, etc. Full-time and part-time curriculum options are available.
Upon completion of the required curriculum, students are awarded a Master of Information Systems and Operations Management with a concentration in Business Analytics.
MS-ISOM Required Core Courses
8 Credits
- ISM 6128 Advanced Business Systems Design & Development I (2 credits); Prereq: none
- ISM 6215 Business Database Systems I (2 credits); Prereq: ‘C’ or better in ISM 6128
- QMB 6358 Statistical Analysis for Managerial Decisions (2 credits); Prereq: none
- GEB 5212 Professional Writing (1 credit); Prereq: none
- GEB 5215 Professional Communications (1 credit); Prereq: none
Business Analytics Concentration Required Courses
12 Credits
- ACG 5005 Financial Accounting (2 credits); Prereq: none
- MAR 5806 Problems & Methods in Marketing Management (2 credits); Prereq: none
- ISM 6405 Intro to Business Intelligence (2 credits); Prereq: ‘C’ or better in ISM 6215 and in ISM 6358
- ISM 6413 Intro to Python (2 credits); Prereq: none
- QMB 6938 Analytics Processes for Business Bootcamp (1 credit); Prereq: none
- QMB 6942 Analytics Project Practicum I (1 credit); Prereq: Analytics Process Bootcamp
- QMB 6943 Analytics Project Practicum II (1 credit); Prereq: Analytics Project Practicum I
- QMB 6944 Analytics Project Practicum III (1 credit); Prereq: Analytics Practicum II
Elective Courses
16 Credits. Choose from a variety of business electives:
- ACG 5075 Managerial Accounting (2credits); Prereq: ACG5005
- MAN 6366 Organizational Staffing (2credits);Prereq: none
- FIN 5437 Corporate Finance I (2credits); Prereq: none
- MAN 6930 Human Capital Analytics (2 credits);Prereq: MAN6366
- MAR 6668 Marketing Analytics I (2credits);Prereq: MAR5806
- ISM6423 Data Mining for Business Intelligence (2 credits); Prereq: I SM 6405
- ISM6562 Business Data Presentation and Visualization (2 credits); Prereq: ISM 6215
- ACG7848 Data Analysis and Skills (2 credits); Prereq: ISM 6413
- MAR6669 Marketing Analytics II (2 credits); Prereq: none
- QMB 6755 Managerial Quantitative Analysis (2 hours); Prereq: none
- QMB 6304 Artificial Intelligence Methods (2 credits); Prereq: ISM 6413
- ACG 7849 Web Crawling & Text Analysis (2 credits); Prereq: ISM 6413
Curriculum Plans
In the Warrington College of Business, graduate courses are organized in a modular system. The modular system allows students to focus intensely on course content over an eight-week period with a one week break in between. Our courses are designed to give you a deep dive into the world of analytics, artificial intelligence and machine learning.
This concentration starts in the fall only.
Semester 1 (Fall)
| Course | Title | Credits | Prerequisite | Module |
|---|---|---|---|---|
| ISM6128 | Advanced Business Systems Design & Development I | 2 | none | 1 |
| ISM6413 | Intro to Python | 2 | none | 1 |
| MAR5806 | Problems & Methods in Marketing Management | 2 | none | 1 |
| GEB5212 | Professional Writing | 1 | none | 1 |
| QMB6938 | Analytics Processes for Business Bootcamp | 1 | none | 1 |
| QMB6358 | Statistical Analysis for Managerial Decisions | 2 | none | 2 |
| ISM6215 | Business Database Systems I | 2 | ‘C’ or better in ISM6128 | 2 |
| QMB6304† | Artificial Intelligence Methods | 2 | ‘C’ or better in ACG6413 | 2 |
| MAN6366† | Organizational Staffing | 2 | none | 2 |
| GEB5215 | Professional Communications | 1 | none | 2 |
| QMB6942 | Analytics Project Practicum 1 | 1 | Analytics Process Bootcamp | 2 |
Semester 2 (Spring)
| Course | Title | Credits | Prerequisite | Module |
|---|---|---|---|---|
| ISM6405 | Intro to Business Intelligence | 2 | ‘C’ or better in ISM6215 and in QMB6358 | 3 |
| ACG5005 | Financial Accounting | 2 | none | 3 |
| FIN5437† | Corporate Finance I | 2 | none | 3 |
| MAN6930† | Human Capital Analytics | 2 | none | 3 |
| MAR6668† | Marketing Analytics 1 | 2 | MAR5806 | 3 |
| QMB6943 | Analytics Project Practicum 2 | 1 | Analytics Project Practicum 1 | 3 |
| ISM6423† | Data Mining for Business Intelligence | 2 | ‘C’ or better in ISM6405 | 4 |
| ISM6562† | Business Data Presentation and Visualization | 2 | ‘C’ or better in ISM6215 | 4 |
| ACG5075† | Managerial Accounting | 2 | ‘C’ or better in ACG5005 | 4 |
| ACG7848† | Data Analysis and Skills | 2 | ‘C’ or better in ISM6413 | 4 |
| MAR6669† | Marketing Analytics 2 | 2 | Marketing Analytics 1 | 4 |
| GEB5215‡ | Professional Communications | 1 | none | 4 |
| QMB6944 | Analytics Project Practicum 3 | 1 | Analytics Practicum 2 | 4 |
Semester 3 (Summer A)
| Course | Title | Credits | Prerequisite | Module |
|---|---|---|---|---|
| QMB6755† | Managerial Quantitative Analysis | 2 | none | 5 |
| ACG7849† | Web Crawling & Text Analysis | 2 | ‘C’ or better in ISM6413 | 5 |
| QMB6304‡ | Artificial Intelligence Methods | 2 | ‘C’ or better in ISM6413 | 5 |
| FIN6779† | AI & ML Applications for Finance & FINTECH | 2 | ’C’ or better in FIN5437 | 5 |
| GEB5215‡ | Professional Communications | 1 | none | 5 |
† Indicates optional electives. Must choose at least 6 of these for a total of 12 credits in order to graduate.
‡ Indicates optional timing for GEB 5215. Students can choose to take this either in Spring or in Summer.
This concentration starts in the fall only.
Semester 1 (Fall)
| Course | Title | Credits | Prerequisite | Module |
|---|---|---|---|---|
| ISM6128 | Advanced Business Systems Design & Development I | 2 | none | 1 |
| ISM6413 | Intro to Python | 2 | none | 1 |
| QMB6358 | Statistical Analysis for Managerial Decisions | 2 | none | 2 |
| ISM6215 | Business Database Systems I | 2 | ‘C’ or better in ISM6128 | 2 |
Semester 2 (Spring)
| Course | Title | Credits | Prerequisite | Module |
|---|---|---|---|---|
| ISM6405 | Intro to Business Intelligence | 2 | ‘C’ or better in ISM6215 and in ISM6358 | 3 |
| MAR5806 | Problems & Methods in Marketing Management | 2 | none | 3 |
| FIN5437† | Corporate Finance I | 2 | none | 3 |
| GEB5212 | Professional Writing | 1 | none | 3 |
| ISM6423† | Data Mining for Business Intelligence | 2 | ‘C’ or better in ISM6405 | 4 |
| ISM6562† | Business Data Presentation and Visualization | 2 | ‘C’ or better in ISM6215 | 4 |
| ACG7848† | Data Analysis and Skills | 2 | ‘C’ or better in ISM6413 | 4 |
| GEB5215‡ | Professional Communications | 1 | none | 4 |
Semester 3 (Summer A)
| Course | Title | Credits | Prerequisite | Module |
|---|---|---|---|---|
| QMB6755† | Managerial Quantitative Analysis | 2 | none | 5 |
| ACG7849† | Web Crawling & Text Analysis | 2 | ‘C’ or better in ISM6413 | 5 |
| QMB6304‡ | Artificial Intelligence Methods | 2 | ‘C’ or better in ISM6413 | 5 |
| FIN6779† | AI & ML Applications for Finance & FINTECH | 2 | ’C’ or better in FIN5437 | 5 |
Semester 4 (Fall)
| Course | Title | Credits | Prerequisite | Module |
|---|---|---|---|---|
| ACG5005 | Financial Accounting | 2 | none | 1 |
| QMB6755 | Managerial Quantitative Analysis I | 2 | none | 1 |
| QMB6938 | Analytics Processes for Business Bootcamp | 1 | none | 1 |
| QMB6304‡ | Artificial Intelligence Methods | 2 | ‘C’ or better in ISM6413 | 2 |
| ACG5075† | Managerial Accounting (Accounting 2) | 2 | ‘C’ or better in ACG5005 | 2 |
| MAN6366† | Organizational Staffing | 2 | none | 2 |
| QMB6942 | Analytics Practicum 1 | 1 | Analytics Process Bootcamp | 2 |
Semester 5 (Spring)
| Course | Title | Credits | Prerequisite | Module |
|---|---|---|---|---|
| MAN6930† | Human Capital Analytics | 2 | none | 3 |
| MAR6668† | Marketing Analytics 1 | 2 | MAR5806 | 3 |
| FIN5437† | Corporate Finance I | 2 | none | 3 |
| QMB6943 | Analytics Project Practicum 2 | 1 | Analytics Project Practicum 1 | 3 |
| ISM6423† | Data Mining for Business Intelligence | 2 | ‘C’ or better in ISM6405 | 4 |
| ISM6562† | Business Data Presentation and Visualization | 2 | ‘C’ or better in ISM6215 | 4 |
| ACG7848† | Data Analysis and Skills | 2 | ‘C’ or better in ISM6413 | 4 |
| MAR6669† | Marketing Analytics 2 | 2 | Marketing Analytics 1 | 4 |
| QMB6944 | Analytics Project Practicum 3 | 1 | Analytics Practicum 2 | 4 |
Semester 6 (Summer A)
| Course | Title | Credits | Prerequisite | Module |
|---|---|---|---|---|
| QMB6755† | Managerial Quantitative Analysis | 2 | none | 5 |
| ACG7849† | Web Crawling & Text Analysis | 2 | ‘C’ or better in ISM6413 | 5 |
| QMB6304‡ | Artificial Intelligence Methods | 2 | ‘C’ or better in ISM6413 | 5 |
| FIN6779† | AI & ML Applications for Finance & FINTECH | 2 | ’C’ or better in FIN5437 | 5 |
† Indicates optional electives. Must choose at least 6 of these for a total of 12 credits in order to graduate.
‡ Indicates optional timing for GEB 5215. Students can choose to take this either in Spring or in Summer.
Independent Study (QMB 6905)
An independent study involved doing a project, such as a system design, website implementation or data analysis, for an agency at UF or outside UF. For these projects, the student should develop the proposal in cooperation with the person who will actually be supervising the work. The work supervisor will have to sign off on the project before the independent study starts, and eventually report on the student’s performance. The instructor will then assign the grade for the course after he/she receives the report from the work supervisor. Email your advisor to obtain the independent study application which should be submitted prior to registering for the independent study.