Master of Quantitative Finance

Fall 2026 Cohort 
 

*Core Courses
**Required

The Master of Quantitative Finance curriculum is 32 credits. Courses are subject to change.

The standard curriculum is set up to be completed in 4 semesters. Students interested in accelerating to complete the program in 3 semesters should contact their academic advisor.


Fall 2026 Cohort - Accelerated Option

*Core Courses
**Required

The Master of Quantitative Finance curriculum is 32 credits. Courses are subject to change.

The standard curriculum is set up to be completed in 4 semesters. Students interested in accelerating to complete the program in 3 semesters should contact their academic advisor.

Students join the Master of Quantitative Finance program with a variety of technical skills and educational and professional backgrounds. The resources below have been compiled to assist incoming new Master of Quantitative Finance students with preparing for their fall coursework. 

All UMD students have unlimited complimentary access to LinkedIn Learning, an online library of >60,000 videos, courses, and career development paths focused on the latest software, creative, and business skills.

Required Asynchronous Course for Students without Microsoft Excel Knowledge

LinkedIn Learning: Excel Essential Training

Required Pre-Skills for BUFN 610: Financial Management with Professor Yang  

BUFN 610: Financial Management offers an introduction to corporate financial management and the content is a prerequisite for many of the other Master of Quantitative Finance courses. The objective of the course is to understand how to model the monetary implications of a firm’s strategic initiatives by outlining the financial concepts and techniques used to evaluate those corporate decisions. Topics include the time value of money, valuation of common securities, construction of discounted cash flow models, capital structure, and the weighted average cost of capital. There is a limited amount of classroom time during the semester and the course covers a significant amount of material. 

Follow Financial Press 

To prepare for the pace and quantity of information in the Master of Quantitative Finance program, students are strongly encouraged to make financial press part of their daily routine. This could include reading the Wall Street Journal, the Financial Times, or watching networks such as CNBC or Bloomberg. Students who are familiar with the financial issues reported upon in the press will have an enhanced understanding of the course materials. Professor Yang will devote a significant amount of time each week discussing what is taking place in financial markets and the broader economy. Students are expected to come prepared to participate in classroom discussions.

Finance Online Course: Introductory Section (Required for Students New to Corporate Finance; Strongly Recommended for All Other Students) 

“Finance Online Course: Introductory Section” offered by Harvard Business School Publishing (product number 6000-HTM-ENG) will expose students to important background material prior to the start of the course, including time value of money, financial ratios, and financial forecasting. 

• Time estimate: This online course is estimated to take 8 to 10 hours for students with prior familiarity with the material. For students who have never been exposed to finance coursework, the online course could take as long as 20 to 30 hours. 
• Cost: $35, to be paid individually by the student directly to HBSP
• Registration: https://hbsp.harvard.edu/import/1423359 
• Technical Difficulty: Contact the Harvard Business School Publishing Technical Support - https://hbsp.harvard.edu/contact-us.

Questions about the BUFN 610 pre-skills assignments related to course content can be directed to Professor Liu Yang (lyang1@umd.edu).

Required Summer Pre-Skills for BUFN 640: Financial Data Analytics with Professor Kozak 

BUFN 640: Financial Data Analytics introduces the skills and computing languages for analyzing financial data and testing financial models. Familiarity with basic probability theory and basic statistics is essential. Working knowledge of calculus and linear algebra is also useful. Basic experience with Python is helpful but is not required. Professor Kozak will launch course materials through his Canvas course prior to the start of the semester, and will include assignments that will be due by the first day of class focused on probability and statistics, Python, and other key topics that will be part of the coursework.   

Additional Optional Assignments and Reading

Incoming students do not need to be proficient with all of these tools prior to the start of classes, however, having some prior experience could help them learn more effectively.

• Business Writing and Communications
  • LinkedIn Learning Course: Ten Habits of Effective Communicators 
  • LinkedIn Learning Course: Tips for Better Business Writing
  • LinkedIn Learning Course: Communication within Teams 
  • LinkedIn Learning Course: Speaking Confidently and Effectively 
• Tableau
  Access/download at https://www.tableau.com/academic/students; free for academic use when using @umd.edu email address
  • LinkedIn Learning Course: Tableau Essential Training
• Power BI
  • LinkedIn Learning Course: Power BI Essential Training
• Python 
  Access/download at https://www.anaconda.com/download (also available on vSmith at https://go.umd.edu/vsmith-setup) 
  • LinkedIn Learning Course: Python Quick Start 
  • LinkedIn Learning Course: Python Statistics Essential Training 
  • LinkedIn Learning Course: Advanced Python
  • Books
    • Python for Data Analytics: A Business-Oriented Approach (by Daniel H. Groner) 
    • Python for Data Analysis: Data Wrangling with Pandas, NumPy, and Jupyter, 3rd Edition (by Wes McKinney)
• SQL
  Access at http://vsmith.umd.edu
  • LinkedIn Learning Course: SQL Essential Training 
  • LinkedIn Learning Learning Path: Master SQL for Data Science
• R & R Studio 
  Access/download at https://www.rstudio.com/ 
  • LinkedIn Learning Learning Path: Getting Started with R for Data Science

Wednesday, May 27, 2026

Failure to register within one week of receiving instructions may result in the termination of admission to the program. Please review all of the information on this page.

HOW TO REGISTER

Directory ID and password must be set BEFORE registration; see Directions for Setting Up Directory ID and Password.

Step 1: Go to Testudo (Office of the Registrar website) 

http://www.testudo.umd.edu/
Click on: Registration (Drop/Add)
Enter Directory ID and Password
Select: Fall 2026

Step 2: Enter Registration Information

Testudo will not allow students to register for courses individually. All Master of Quantitative Finance students will register for MB11 for the fall semester. Enter the following information in the "Registration (Drop/Add)" screen of Testudo as shown below to register. 

• Course: MSBQ99MB
• Section: MB11
• Grading Method: None
• Credits: [Leave blank] 

Click "Submit Changes" to complete registration. A message may appear stating the course is non-standard; click "Enter" to bypass this message. All graduate-level courses at the Smith School of Business are non-standard.

Step 3: Confirm Courses 

Click "View Schedule" to confirm registration based on the schedule below. 

COURSE SCHEDULE

Registration is set up for a 4-semester program completion (in May 2028). Students who wish to accelerate and complete the program in 3 semesters (in December 2027) should contact Feven Girmay for additional registration guidance.

Courses are completed in 7-week sessions referred to as "terms". Term A meets August through October, and Term B meets October through December; for specific dates, review the Academic Calendar. 

The Master of Quantitative Finance curriculum is 32 credits. 

The standard curriculum is set up to be completed in 4 semesters. Students interested in accelerating to complete the program in 3 semesters should contact their academic advisor.

For general registration information, please see the Registration FAQ.

The schedule subject to change.

Tuition & Fee information, including due dates and residency information can be found at:

Master of Quantitative Finance Tuition & Fees