Cutting-Edge Curriculum
Transforming professionals into data-driven decision makers
At Carnegie Mellon University, we believe that anyone can harness the power of data - from the seasoned programmer in financial services to the non-technical manager in HR. To transform professionals into data-driven decision makers, our faculty have designed the coursework for this certificate with evidence-based pedagogical practices in mind.
These practices stem from the research conducted in CMU’s world-renowned Statistics Pedagogy Lab Group, a group that seeks to modernize the statistics curriculum and spearhead the development of pedagogical tools and practices that benefit students from all backgrounds.
Curriculum Overview
The online Graduate Certificate in Foundations of Data Science includes five graduate-level, credit-bearing courses taught by expert CMU faculty and features the following course progression:
For Fall 2025 Start:
Semester |
Fall 2025 |
Spring 2026 |
Summer 2026 |
---|---|---|---|
Course |
Telling Impactful Stories with Data Visualization Introduction to Data Science Computing Workflows |
Probability & Statistics for Data Science Gaining Insights Through Statistical Modeling |
Applications of Real-World Data Science: A Capstone Experience |
For Spring 2026 Start:
Semester |
Spring 2026 |
Summer 2026 |
Fall 2026 |
---|---|---|---|
Course |
Probability & Statistics for Data Science Gaining Insights Through Statistical Modeling |
Introduction to Data Science Computing Workflows Telling Impactful Stories with Data Visualization |
Applications of Real-World Data Science: A Capstone Experience |
Each course will appear on your Carnegie Mellon transcript with the grade earned. To earn the certificate, you must successfully complete all courses in the program. If you are only interested in one course, however, you may complete that course only and it will show on your transcript with the grade earned.
Course Descriptions:
Probability & Statistics for Data Science
Gaining Insights through Statistical Modeling and Machine Learning
Telling Impactful Stories with Data Visualization
Introduction to Data Science Computing Workflows
Applications of Real-World Data Science: A Capstone Experience
Meet Our World-Class Faculty

Education: Ph.D., University of Chicago
Research Areas: Astrostatistics, Statistics Pedagogy, Statistics for Physical Sciences

Education: Ph.D., Carnegie Mellon University
Research Areas: Sports Analytics, Statistical Genetics, Selective Inference
The Building Blocks of Our Curriculum

Spiral Learning
Spiral learning is an evidence-based pedagogical practice that helps students develop a deep understanding of data science in a short period of time. This approach emphasizes the importance of progressive learning instead of immediate proficiency in core concepts. Throughout the curriculum, our professors revisit or ‘spiral back’ to key topics continuously, each time encouraging a deeper understanding of the material. By repeatedly discussing topics in greater detail, you will start to build mastery in fundamental data science skills that you can apply in the future.

Experiential Learning
The Graduate Certificate in Foundations of Data Science is anything but traditional. Here, you will learn how to think like a data scientist by immersing yourself in a rich environment filled with hands-on experiences. Throughout the curriculum, you will practice statistical analysis techniques on real-world datasets; use programming languages like R and Python to create statistical graphs; and learn how to communicate your findings to various stakeholders. In the capstone course, you will work with real world data under the guidance of subject matter experts to apply the skills you have gained throughout the program.

Real-World Context
While it’s important to develop technical skills in statistical analysis, data visualization and computational thinking, we also believe in the power of application. How can data science be used to solve real societal and organizational issues? In our program, students from all industries—whether it be finance, marketing, healthcare and beyond—are empowered to approach problems with a confident, data-centric mindset. With fundamental knowledge in data science, you’ll have the skills to apply data in meaningful ways for your team and organization.