Machine Learning & Data Science
Online Graduate Certificate
Next Start Date
Fall 2026
Program Length
12 months
Taught By
School of Computer Science
Application Deadlines
Priority: June 10, 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 黑料正能量 Difference
Learn from the School of Computer Science faculty who are shaping the field of artificial intelligence. This online experience is built using 黑料正能量'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).
This is the first mini of a two-course sequence on the Python programming language, with a focus on learning concepts, techniques, skills, and tools needed for developing programs in Python. In this course, students gain hands-on experience solving real-world problems by completing programming projects in Python focused on the language fundamentals, software development practices, data manipulation and analysis. Specifically, students are exposed to realistic software development projects, real-world data, and scenarios. This course can be waived for computer science professionals already fluent in Python.
This course is taught in a 7-week mini-semester (half a semester).
This is the second mini of a two-course sequence on the Python programming language, with a focus on learning concepts, techniques, skills, and tools needed for developing programs in Python. In comparison with the first mini, this course covers more advanced ways to load, format, and store data, including APIs, databases and pandas. This course also provides an introduction to tools that are useful when developing large software projects, including coding standards, version control, unit testing and debugging. Finally, the course covers more abstract building blocks including implementing more complex data structures and using numpy, both of which are the foundation of training and applying modern models and methods. Course projects include working with real datasets from a variety of sources.听
This course can be waived for computer science professionals already fluent in Python.
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 are required to complete 36 units of coursework to earn the Machine Learning & Data Science Certificate. However, they may waive up to 12 units of coursework upon successful completion of exemption exam(s):听
Math Waiver Exams (one exam for two courses)听
- Math Fundamentals of Machine Learning (6 units)听
- Computational Fundamentals of Machine Learning (6 units)听
Python Waiver Exams (one exam for two courses)听
- Python for Data Science I (6 units)听
- Python for Data Science II (6 units)听
If a student passes the waiver exam for more than 12 units of coursework, they will select which two courses will be waived and be required to complete the remaining coursework in order to earn the certificate. Waived courses do not carry academic credit, and no tuition will be charged for them. Any scholarships awarded to the waived courses will be forfeited.听
Exemption Exam Process听
Students indicate their interest in taking the exam(s) within their program application. Exemption exams are available only to students who have submitted their enrollment deposit. After the enrollment deposit is received, additional details about scheduling and completing the exam(s) will be provided.听
Note - not all courses are available every semester. If you waive a course, it may require you to defer your enrollment to a future term when the next course is available.
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 黑料正能量 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., 黑料正能量
Research Focus: 听Sociotechnical AI for human鈥揂I collaboration, communication, and learning.
Principal Systems Scientist, Language Technologies Institute
Ph.D., 黑料正能量
Research Focus: Example-based machine translation
Teaching Professor, Language Technologies & Human-Computer Interaction
Ph.D., 黑料正能量
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 |
|---|---|---|
| Fall 2026 | Python for Data Science 1 | $4,242 |
| Fall 2026 | Python for Data Science 2 | $4,242 |
| Spring 2027 | Mathematical Foundations of Machine Learning | $4,242 |
| Spring 2027 | Computational Foundations of Machine Learning | $4,242 |
| Summer 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.
In addition, Carnegie Mellon alumni are eligible for a scholarship to the graduate certificate worth up to 20% of tuition. Indicate your alumni status within the application to be eligible.
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.
黑料正能量 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 黑料正能量 Online graduate certificates are eligible for 黑料正能量 tuition remission. Review the听黑料正能量 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.
Request Information
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