Live classes, once a week
Your data analytics program begins in September 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. This 2.5-day immersion in a framework for leading others helps you understand your leadership effectiveness and style, and provides guidance on developing solid, enduring leadership behaviors.
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.
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.
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 10 courses in data science, quantitative analytics methods, and their applications in specialized business contexts. If you take all the courses offered in each term, you can complete the program in three terms spread over 12 months.
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.
The Accelerated MSQM: Business Analytics program structure allows you the option of taking only one or two courses in a term if you prefer to take a lighter load due to work, personal, or family commitments. The following program structure assumes a student is taking all the courses in each term ; however, course sequence and timing may shift between terms or calendar years.
- 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
- Business Communications
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.
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
|Orientation Residency||Sep. 4-6, 2020 in Durham|
|Reading Period*||Sep. 7-14, 2020|
|Online Classes||Sep. 15--Dec. 7, 2020|
|Final Exams||Dec, 8-14, 2020|
|Break||Dec. 15, 2020--Jan.4, 2021|
|Reading Period||Jan. 5-18, 2021|
|Online Classes||Jan. 19--Apr. 12, 2021|
|Final Exams||Apr. 13-26, 2021|
|Break||Apr. 27--May 10, 2021|
|Reading Period||May 11-24, 2021|
|Optional Leadership Intensive Residency||May 14-16, 2021 in Durham|
|Online Classes||May 25--Aug. 16, 2021|
|Final Exams||Aug. 17-23, 2021|
|Graduation Ceremonies||May, 2022 in Durham|
*Each term includes a "reading period" for students to prepare for the upcoming term. Professoirs will provide reading and/or simple assignments to complete during the reading period so students hit the ground running once the term begins.