Carnegie Mellon University

MADS Curriculum

Program Design

Our courses are carefully crafted to assure that our students develop industry-valued competencies and a strong statistical foundation. Among many areas, our students will develop skills in R, Python, PySpark, PyTorch, SQL, Spark, and other industry-valued applications. There is no thesis requirement for our program. Please see the Schedule of Courses to view the course descriptions.

To learn more about the pedagogy and design of the MADS curriculum, check out our article in The American Statistician: On Teaching Statistical Practice: From Novice to Expert.

Fall Schedule Core Curriculum (required)

  • Professional Skills for Statisticians I 
  • Data Visualization
  • Data Engineering
  • Applied Linear Models
  • Statistical Computing

Electives* (one of two):

  • Statistical Methods in Finance
  • Text Analysis

Spring Schedule Core Curriculum (required)

  • Professional Skills for Statisticians II
  • Statistical Machine Learning
  • Time Series 
  • Statistical Practice

Special Topics: Sports Analytics (Elective*) or Special Topics:  Computational Public Health (Elective*) or (2 minis) - Software for Large-Scale Data AND Experimental Design

Students who took Statistical Learning (36-462/36-662) would need to select one of the Special Topics AND Software for Large-Scale Data and Experimental Design

*Electives are offered on a rotating basis. MADS students are typically not permitted to take courses outside of the Department of Statistics & Data Science. Normally, all the MADS students take core requirements together as a cohort. 

Alternative courses within the Department of Statistics & Data Science may be allowed as a substitute should a comparable course of study already have been successfully completed prior to entry into the MADS program — any substitutions are considered on a case-by-case basis and must be approved by the program director.

Hallmark Courses: We Practice What We Teach

Professional Skills for Statisticians I and Professional Skills for Statisticians II

Taught by Jamie McGovern, MADS director, special faculty, the objective of this course is to help you develop the professional skills you need to successfully navigate employment opportunities and delivery-oriented workplace environments. This course will help you manage your career effectively, developing skills relevant to job acquisition, career development, and performance management processes. Highly-valued client-facing and colleague collaboration skills will be emphasized. Through Jamie, a valued industry leader, you will learn the power of storytelling through resume writing, how to work with clients, how to effectively communicate in the workplace, and how to deliver quality work to a non-statistical audience.

Statistical Practice

Taught by a collective of our faculty, the focus of Statistical Practice is a consulting project. Our students will participate in meetings with industry and academic clients. These are real projects, new each year, with clients who are interested in the results, and no predetermined "solutions". In this culminating capstone project, our students are taught how to structure a consulting session, elicit and diagnose a problem, manage a project, and report an analysis.