Carnegie Mellon University
Home › Curriculum

Cutting-Edge Curriculum

The Power of Data Grounded in Computer Science 

Our Philosophy

Artificial intelligence is transforming how all industries and organizations operate. Now, more than ever, there is increasing demand for data scientists and engineers who are experts in machine learning. To drive efficiency, create technological advancements, gain insights for the future, and win in the marketplace, the world needs data professionals who can develop algorithms and create intelligent machines. 

Carnegie Mellon is one of the top universities in the nation for learning computational data science. Our certificate program is taught by leading data science researchers and focuses on applying AI to solve real-world industry problems.

Industry Impact

Everything we teach offers significant impact. Our approach is built for the large scale data problems that organizations are currently facing and addresses the cloud-based technologies needed to solve real-world data problems.   

You will learn how to apply relevant mathematical and computational concepts and skills to create solutions and innovations. With a solid background in computational data science, you will be able to solve problems across a variety of industries.    


Our program is practical and interactive, featuring collaborative coursework and hands-on training. After completing the certificate program, you will have the ability to: define the analytical requirements of a data science problem, design a data gathering plan, build and deploy models using the right analytic algorithms, and improve models to achieve organizational objectives for the future.  


At Carnegie Mellon, multi-disciplinary work is part of who we are, and this program is no exception. Our program taps into expertise from the Language Technologies Institute, Computer Science department, Human-Computer Interaction Institute, and Machine Learning department. Bringing together diverse perspectives helps us foster more powerful and challenging discussions. When you enroll in our certificate program, you can trust that you will learn computational data science from all angles. 

Curriculum Overview

As a student in the Computational Data Science Foundations certificate, you will complete the following graduate-level, credit-bearing courses over three semesters. All completed courses will show on your Carnegie Mellon transcript with the grade earned. 

Mathematical Foundations of Machine Learning (6 units;  10-680)

This course offers the necessary mathematical background to understand machine learning. Topics will include probability, linear algebra, and multivariate differential calculus. Students will also learn how to translate these foundational math skills into concrete coding programs.

Computational Foundations for Machine Learning (6 units;  10-681)

This course offers the necessary computational background for studying machine learning. Topics include computational complexity, analysis of algorithms, proof techniques, optimization, dynamic programming, recursion, and data structures.

Python for Data Science (delivered in two parts, 6 units each;  11-604 & 11-605)

This course teaches the concepts, techniques, skills, and tools needed for developing programs in Python. Topics include types, variables, functions, iteration, conditionals, data structures, classes, objects, modules, and I/O operations. This course can be waived for computer science professionals who are already fluent in Python.

Foundations of Computational Data Science (delivered in two parts, 6 units each;  11-671 & 11-672)

This course offers a hands-on introduction to foundational computational data science concepts, including computing systems, analytics, and human-centered data science. Upon completing the coursework, students will have the necessary skills to obtain further graduate education in data science and/or artificial intelligence.

Course Waivers

Students who already have proficiency in either math or programming may waive the following courses upon successful completion of an exemption exam:

  • Math Fundamentals of Machine Learning AND Computational Fundamentals of Machine Learning
  • Python for Data Science

The exemption exam will be administered to admitted students only. Students who are interested in sitting for the exam should apply to the program and indicate within the application their interest in taking the exam. Once admitted, additional information about sitting for the exam will be provided.  

Upon successful completion of one, or both, exemption exams, students will only complete the remaining courses to qualify for the certificate. No credit will be earned, nor will tuition be assessed, for waived courses.  

For more information about course waivers, contact an admissions counselor today.