Live classes, once a week
Your data analytics program begins in August with a 2.5-day launch experience where you’ll meet your professors, network with classmates, and build relationships with the members of your learning team. This weekend residency requires you to be physically present on Duke University’s campus in Durham, North Carolina. From there, your program moves online. Over the next 12 months, you’ll work through course modules--including online readings and pre-recorded video lectures--on your own schedule, complete individual and team assignments, and join your class in real-time video classes each week.
After two terms, you may choose to return to Duke’s campus for an optional working professional leadership intensive. Held over a weekend, this in-person immersion helps you understand your leadership style, and provides guidance on developing solid, enduring leadership behaviors.
Collaborative environment
Fuqua’s difference comes from our supportive culture and collaborative environment. You’ll be working closely with other students who are working professionals with expertise in different functions and markets in this nurturing environment. Even in an online learning environment, you are never alone because of our unique collaborative and high-touch approach.
Our Faculty
As with our other programs, the Accelerated MSQM: Business Analytics program is taught by a team of world-renowned faculty—scholars recognized for excellence in their academic area and their research as well as their industry expertise, with a passion for teaching. Your professors are authorities in core business functions as well as in quantitative data analytics. They will challenge you with a rigorous curriculum and bring real-world insights that will give you new perspectives on your professional work.
Classroom Dynamics
Professors foster active in-class debates that draw insights from the range of experience in your cohort, so class discussions engage professionals from different sectors. Our learning method draws from cases and exercises that challenge you to tackle issues from multiple perspectives and give you practice in structuring data science problems based on multiple sources of data, including big data, and presenting concise recommendations. The academic rigor and fast pace will ensure your time is well spent.
Your program will consist of 9 courses in data science, quantitative analytics methods, and their applications in specialized business contexts.
Each term will have a pre-reading period for you to prepare for the upcoming term. Your professors will give some reading or simple assignments to complete during the pre-reading period so you can hit the ground running once the term starts. You’ll have sufficient down time between terms and during holidays to re-energize.
Program Launch in Durham, NC (2.5 days)
Term 1 - Online (12 weeks)
- Programming for Analysis and Visualization
- Decision Models
- Data Analytics and Applications
Term 2 - Online (12 weeks)
- Advanced Data Analytics and Applications
- Empirical Analysis for Business Strategy
- Digital Marketing
- Optional Leadership Intensive in Durham, NC (2.5 days)
Term 3 - Online (12 weeks)
- Financial Risk Management
- Fraud Analytics
- Ethics and Legal Issues in Business Analytics
Sample Schedule
Each course will include six live virtual classes, held biweekly. A typical term schedule would look like this:
|
Saturday Class Schedule (Wks 1, 3, 5, 7, 9, 11) |
Saturday Class Schedule (Wks 2, 4, 6, 8, 10, 12) |
|
Programming for Analysis & Visualization 9:30 - 10:45 am |
Data Analytics & Applications 9:30 - 10:45 am |
|
Break 10:45 - 11:00 am |
|
|
Decision Models 11:00 am - 12:15 pm |
A one-week final exam period will follow the last class.
Between classes, you'll watch recorded lectures, read cases and/or textbook or other recommended materials, work on individual or team assignments, and prepare questions or discussion topics for the next live-virtual class. You will typically be given one course assignment (individual or team) after every class, due the next live virtual class day or the subsequent Monday. Office hours are available for your professors throughout the term.
Digital Learning
Combining independent study, live classes and collaborative assignments, the Accelerated MSQM: Business Analytics curriculum is delivered in a sophisticated and user-friendly online learning environment. The online platform serves as a repository for self-study materials such as pre-recorded video lectures, readings, and interactive exercises. It also enables face-to-face interaction, discussion of business and analytics case elements, and debate of relevant data science topics with your classmates during live classes.
A balance of self-study and live classes
For each subject in the curriculum, you’ll work through a set of online course materials on your own schedule. In addition, you will attend live, 75-minute online class sessions with the rest of your class, during which your professor will give lectures, conduct case discussions, or ask students to give presentations. The blend of the self-paced and live class elements of each online course provides you the flexibility to balance program requirements around your professional and personal commitments while still allowing you to develop and maintain close connections with other students and the faculty. While you should expect to spend at least 15-20 hours a week on your data science schoolwork, you can schedule these elements of your program around other obligations.
One Platform
Throughout the program, you’ll use your digital learning platform to:
- Submit assignments
- Download business-analytics course materials
- Interact with classmates
- Read class and team online bulletin boards
- Take exams
- Contribute to course discussion boards
- Share documents
| Term 1 | Fall 2021 (1780) |
| Orientation Residency (online) | September 3-5, 2021 |
| Classes and Reading Period Begins | September 7-13, 2021 |
| Classes | September 14 - December 6, 2021 |
| Final Exams | December 7-13, 2021 |
| Break | December 14, 2021- January 10, 2022 |
| Term 2 | Spring 2022 (1790) |
| Classes and Reading Period Begin | January 11-17, 2022 |
| Classes | January 18 - April 11, 2022 |
| Final Exams | April 12-25, 2022 |
| Break | April 26 - May 9, 2022 |
| Term 3 | Summer 2022 (1810) |
| Classes and Reading Period Begin | May 10-23, 2022 |
| Leadership & Data Visualization Intensives | May 21-22, 2022 |
| Classes | May 24 - August 15, 2022 |
| Final Exams | August 16-22, 2022 |
*Each term includes a "reading period" for students to prepare for the upcoming term. Professors will provide reading and/or simple assignments to complete during the reading period so students hit the ground running once the term begins.
| Term 1 | Fall 2022 (1820) |
| Orientation | August 26-28, 2022 |
| Classes and Reading Period Begin | August 30 - September 12, 2022 |
| Classes | September 13 - December 5, 2022 |
| Final Exams | December 6-12, 2022 |
| Break | December 13, 2022 - January 5, 2023 |
| Term 2 | Spring 2023 (1830) |
| Classes and Reading Period Begin | January 6-16, 2023 |
| Classes | January 17 - April 10, 2023 |
| Final Exams | April 11-17, 2023 |
| Break | April 18 - May 8, 2023 |
| Term 3 | Summer 2023 |
| Classes and Reading Period Begins | May 9-22, 2023 |
| Leadership Intensive | May 20-21, 2023 |
| Classes | May 23 - August 14, 2023 |
| Final Exams | August 15-21, 2023 |
* Each term includes a "reading period" for students to prepare for the upcoming term. Professors will provide reading and/or simple assignments to complete during the reading period so students hit the ground running once the term begins.