Machine Learning & Data Science
Online Graduate Certificate
Next Start Date
May 2026
Program Length
12 months
Taught By
School of Computer Science
Application Deadlines
Final: April 8, 2026
ML, From the Birthplace of AI.听
Machine Learning now shapes how decisions are made, systems are built, and how work gets done. Building real understanding means learning the fundamentals from the faculty at the School of Computer Science, ranked #1 in the nation for AI graduate programs.
"Because of this program, I developed the ability to translate complex technical concepts into business language, demonstrate how models can be applied across real-world use cases, and collaborate effectively with stakeholders to quickly prototype and validate ideas before they go into production."
Karla Turcios
Founder Teknolog IO LLC
Who is this Program For?
The program is designed for software engineers, data analysts, engineers, scientists, and other technically trained professionals who want to build a rigorous foundation in machine learning and data science.
What You Will Learn
By the end of this certificate, you'll have a strong foundation in the mathematics, algorithms, and computational methods behind modern AI systems, preparing you for continued technical growth in this rapidly evolving field.
The CMU Difference
Learn from the School of Computer Science faculty who are shaping the field of artificial intelligence. This online experience is built using CMU's signature approach to online learning, ensuring complex generative concepts are taught with the same rigor and depth as on-campus study.听
Curriculum Highlights
Build the technical foundation that powers modern machine learning and data science. Coursework is carefully designed to help you:
- Develop strong programming fluency using industry-standard tools and practices to work with real-world data
- Master the mathematical foundations of machine learning, including probability, linear algebra, and multivariate calculus
- Build computational thinking for ML systems, focusing on algorithms, optimization, and complexity
- Integrate computing, analytics, and visualization, applying these skills to real-world problems such as natural language processing and computer vision
Together, these courses provide a rigorous foundation in programming, mathematics, and computation, and applied data science, preparing you for advanced study and technically-demanding roles in machine learning and data-driven fields.听
Course Descriptions
Practice the necessary mathematical background for further understanding in machine learning. You will study topics like probability (random variables, modeling with continuous and discrete distributions), linear algebra (inner product spaces, linear operators), and multivariate differential calculus (partial derivatives, matrix differentials). Some coding will be required; ultimately, you will learn how to translate these foundational math skills into concrete coding programs.
This course is taught in a 7-week mini-semester (half a semester).
Practice the necessary computational background for further understanding in machine learning. You will study topics like computational complexity, analysis of algorithms, proof techniques, optimization, dynamic programming, recursion, and data structures. Some coding will be required; ultimately, you will learn how to translate these computational concepts into concrete coding programs.
This course is taught in a 7-week mini-semester (half a semester).
Master the concepts, techniques, skills, and tools needed for developing programs in Python. You will study topics like types, variables, functions, iteration, conditionals, data structures, classes, objects, modules, and I/O operations while also receiving hands-on experience with development environments like Jupyter Notebook and software development practices like test-driven development, debugging, and style. Course projects include real-life applications on enterprise data and document manipulation, web scraping, and data analysis. These courses can be waived for computer science professionals already fluent in Python.
This course is taught in a 7-week mini-semester (half a semester).
Learn foundational concepts related to the three core areas of data science: computing systems, analytics, and human-centered data science. In this course, you will acquire skills in solution design (e.g. architecture, framework APIs, cloud computing), analytics algorithms (e.g., classification, clustering, ranking, prediction), interactive analysis (Jupyter Notebook), applications to data science domains (e.g. natural language processing, computer vision(, and visualization techniques for data analysis, solution, optimization, and performance measurement on real-world tasks.听
This course is taught in a 7-week mini-semester (half a semester).
Learn foundational concepts related to the three core areas of data science: computing systems, analytics, and human-centered data science. In this course, you will acquire skills in solution design (e.g. architecture, framework APIs, cloud computing), analytic algorithms (e.g., classification, clustering, ranking, prediction), interactive analysis (Jupyter Notebook), applications to data science domains (e.g. natural language processing, computer vision), and visualization techniques for data analysis, solution optimization, and performance measurement on real-world tasks.
This course is taught in a 14-week semester.听
Students who already have proficient skills in either math or programming may waive the following courses upon successful completion of an exemption exam(s):
- Math Fundamentals of Machine Learning (11-960) and Computational Fundamentals of Machine Learning (11-961)听
- Python for Data Science I (11-904) and Python for Data Science II (11-905)
The exemption exam(s) will be administered to admitted students only. Students who are interested in taking the exam(s) should indicate their interest in the application when applying to the program. Once admitted, additional information about sitting for the exam(s) will be provided. 听
Upon successful completion of one, or both, of the exemption exams, students will only complete the remaining courses to qualify for the certificate. No credit will be earned, nor tuition will be assessed, for the waived courses. 听
Please note: Foundations of Computational Data Science is not eligible for a waiver.
For more information about course waivers, contact an admissions counselor today.
Quality Online Learning for Working Professionals
Mastering the foundations of machine learning and data science is analytical, iterative and demanding 鈥� and it requires a learning environment that supports depth, rigor and flexibility.
Rigor 鈥� Expect a rigorous learning experience with the same high academic standards as our on-campus offerings. It won鈥檛 be easy, but it will be worth it.
Flexibility 鈥� Complete the program in less than a year through a combination of live online classes and self-paced activities that fit your schedule.
Live, online classes meet weekly with CMU faculty after work hours for interactive discussion, problem solving and collaborative learning.
Self-paced activities - readings, short lectures and applied exercises allow you to master concepts on your own timeline with ongoing faculty support.
World-Class Faculty
From the School of Computer Science
Professor, Language Technologies & Human-Computer Interaction
Ph.D., 好色先生TV
Research Focus: 听Sociotechnical AI for human鈥揂I collaboration, communication, and learning.
Principal Systems Scientist, Language Technologies Institute
Ph.D., 好色先生TV
Research Focus: Example-based machine translation
Teaching Professor, Language Technologies & Human-Computer Interaction
Ph.D., 好色先生TV
Research Focus: Computational morphology, natural language processing (NLP) for low-resource languages, and the intersection of language technologies with large-scale AI systems.
Application Requirements
Designed for professionals with strong quantitative and technical backgrounds, this graduate certificate prepares learners to master the mathematical, computational, and programming foundations required for advanced study. Successful applicants have:
- A STEM bachelor鈥檚 degree (engineering, science, technology, or math)
- Professional experience in computer programming or related technical work (internships or other work is acceptable).
- Demonstrated proficiency in mathematics, including calculus, linear algebra, and statistics.
- Competence in programming Python, R, or an analogous language, with experience writing at least 1000 lines of code.
- A forward-thinking mindset - we find that success comes from a drive to learn and apply new skills immediately.
We encourage you to apply even if your background does not perfectly align with every requirement listed above. In some cases, preparatory or refresher work may be recommended to help ensure your academic success.听
Ready to Build Your Future?
Tuition
We know that a graduate-level certificate represents a significant investment of both time and money. But we also know the impact of investing in your own professional growth.听
See below for a full breakdown of tuition and more details on payment options. 听听
A limited number of partial scholarships are still available. Apply by the final deadline to be considered for these awards.
You will be notified of your award amount in your admission letter. 听
| Term | Course | Investment |
|---|---|---|
| Summer 2026 | Mathematical Foundations of Machine Learning | $4,242 |
| Summer 2026 | Computational Foundations of Machine Learning | $4,242 |
| Fall 2026 | Python for Data Science 1 | $4,242 |
| Fall 2026 | Python for Data Science 2 | $4,242 |
| Spring 2027 | Foundations of Computational Data Science | $8,484 |
| Total Investment | $25,452 |
Financing Your Future
To help make the financial commitment more manageable, we offer a limited number of scholarships and flexible monthly payment plans. Students also use employer tuition reimbursement benefits, and the G.I. Bill to cover tuition costs. See below for more details on ways to make an investment in your future a reality.
Additional Fees & Notes
- A $240 technology fee will be assessed each semester (subject to change).
- Tuition rates are for the current academic year only. If the certificate is not completed within that time frame, tuition may increase slightly for the following academic year.
Funding Information and Resources
All applications received by the priority deadline are eligible for a partial scholarship award; those received later may be eligible if funds are still available. You will be notified at the time of admission of any awards. Scholarships are applied by course and are non-transferrable between courses or semesters.
The majority of our students use tuition reimbursement benefits from their company. While some policies won't cover certificate programs, since this certificate is credit-bearing and a verifiable credential, many organizations will allow tuition benefits.
And remember, fall enrollment will maximize benefits since most benefit plans are based on calendar year. Enroll in Fall 2026 and you will use both your 2026 and 2027 benefits to cover the program cost.听
If your employer is uncertain about providing financial support, or if you need specific documents to proceed with enrollment, contact a Program Specialist who will help highlight the value and benefits of completing an online certificate at Carnegie Mellon. Visit this webpage to see examples of how employer tuition reimbursement can be structured throughout the semester.听
A monthly payment option is available to break tuition into manageable installments. Managed by Nelnet, students can enroll online.
Visit this webpage to explore available payment options and see examples of how tuition can be structured throughout the semester.
好色先生TV provides services to veterans and their dependents who are eligible for Veterans Education Benefits under the Montgomery G.I. Bill庐, Post-9/11 G.I. Bill, and the Vocational Rehabilitation and Employment Program. Please note that our online graduate certificates are not currently eligible for the Yellow Ribbon program.
The process begins with an application directly to Veterans Affairs. Once approved, you will provide your Certificate of Eligibility to the Carnegie Mellon Veterans Affairs Coordinator. Contact information and additional details about the process can be found here.听
Students eligible for GI Bill funding may receive scholarship awards prior to full GI Bill funding confirmation. Scholarship awards will be adjusted to reflect GI Bill funding and cannot exceed the cost of tuition and fees.
All CMU Online graduate certificates are eligible for CMU tuition remission. Review the听CMU tuition remission policy听to check your eligibility.
Students pursuing a graduate certificate are not eligible to receive federal financial aid. However, private loans are a viable alternative to consider, offering competitive interest rates and borrower benefits. See , a free loan comparison service to easily research options.
Start Your Application
Ready to Apply? Here's what you'll need to complete the application process for the Machine Learning & Data Science Foundations Online Graduate Certificate.
Complete the Online Application
Submit your application via the .
Submit Your Resume/CV听
Tell us more about your employment history, academic background, technical skills and professional achievements.
Submit Your Transcripts听
Upload unofficial copies from schools where a degree was earned or significant coursework was taken. Transcripts must include:
- Your name
- College or university name
- The degree awarded (along with the conferral date)
- All courses taken and grades earned
Upload a Statement of Purpose听
In 500 words or less, tell us why you are interested in this certificate program and how you anticipate using it in your professional capacity.
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