Foundations of Data Science
Online Graduate Certificate
Data Literacy Defines Career Success.
The world has changed. As data becomes the language of work, those who don’t speak it are left out of the conversation.
That’s why understanding data fundamentals is no longer optional – no matter your industry or role. If you want to keep up, you must build your own data fluency.
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| "The coursework was directly applicable to my day-to-day work in UX and AI design. From building regression models to analyzing large datasets, I could immediately translate what I learned into actionable insights. " Jen Kelleman |
Who is this Program For?
Professionals and recent graduates who want to build a data-driven mindset, collaborate effectively with data teams, and use data to make smarter, more efficient decisions - whether advancing in their current role or preparing for graduate study in data science.
What You Will Learn
By the end of this certificate, you’ll be confident using data to make better decisions in your organization – not just collecting numbers, but understanding what they mean and how to act on them.
The CMU Difference
All online certificate programs are not the same. Our online learning experiences use evidence-based learning science to support clarity, retention, and real-world application. All taught by CMU's world class faculty in live-online classes.
Class Profile
AVERAGE AGE
INDUSTRIES REPRESENTED
JOB FIELD
Curriculum
Transition from knowing data matters to using it confidently - no technical background required. Coursework is carefully designed to teach you how to:
- Interpret data in Statistics & Statistical Modeling
- Analyze information in Computing Workflows
- Communicate insights in Data Visualization
- Apply learnings in the Capstone
Together, these courses provide a foundation in the core skills of data science - equipping you to thoughtfully engage with data and use it to make informed recommendations and decisions.
Course Descriptions
Learn how to interpret, understand and correctly apply fundamental terminology and techniques in future data analysis situations. Explore the theoretical aspects of probability and statistical inference, including basic probability, random variables, univariate and bivariate probability distributions, statistics, likelihood, point and interval estimation, hypothesis testing, and the frameworks underlying linear and logistic regression and Naive Bayes. Mathematical details are supplemented with computer-based examples and exercises (e.g. visualization and simulation).
Designed to teach you how to approach, analyze and interpret data, topics include data input/output, processing, exploratory analysis, clustering, common regression and classification models (including those of classical statistics and of machine learning), and experimental design. Practice using these methods on real-world data and subsequently apply them when analyzing data in the program's Data Science Capstone course.
Prerequisite: Probability & Statistics for Data Science
Explore the most common forms of graphical displays and their (mis)uses. Learn how to create well-designed graphs and understand them from a statistical perspective, while working with increasingly common, complex data structures (temporal, spatial, and text data). All assignments will be completed in R. Throughout the course, communication skills will play an important role.
Learn how to apply computational thinking to data processing and analysis problems through R programming language. Topics include defining and manipulating vectors, lists, and data frames; processing strings and applying regular expressions in string searches; input and output data; writing functions; applying numerical methods such as integration and optimization; working with date-and-time-based data; and applying unit testing.
In the capstone course, work with real-world data to apply the skills and knowledge acquired throughout the program. Supported by subject matter experts, you will have the opportunity to practice synthesizing and communicating results in a clear and concise manner.
World Class Faculty
From the Department of Statistics and Decision Sciences
Dr. Peter Freeman
Associate Teaching Professor
Ph.D., University of Chicago
Research Focus: Astrostatistics
Dr. Ron Yurko
Assistant Teaching Professor
Ph.D., Carnegie Mellon University
Research Focus: Sports Analytics
Dr. Alex Reinhart
Assistant Teaching Professor
Ph.D., Carnegie Mellon University
Research Focus: Natural Language Processing & LLM's
Dr. Zach Branson
Associate Teaching Professor
Ph.D., Harvard University
Research Focus: Causal Inference & Statistical Machine Learning
Julia Walchessen
Special Faculty
Post Doctoral Fellow, Carnegie Mellon University
Research Focus: Statistical Machine Learning
Application Requirements
Designed for any professional, from the seasoned programmer in financial services to a non-technical manager in human resources. Successful applicants have:
- A bachelor’s degree from an accredited college or university in any subject
- Basic knowledge of statistics and calculus
- Exposure to programming languages (Python, R, Java or MATLAB)
- 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 you don't have a background in math or programming. However, we may require or recommend preparatory work to ensure your academic success.
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.
See below for a full breakdown of tuition and more details on payment options.
Scholarships
Applicants who apply by the Priority Deadline are eligible for a partial scholarship award.
You will be notified of your award amount in your admission letter. Apply today!
| Term | Course | Investment |
|---|---|---|
| Spring 2026 | Probability & Statistics for Data Science | $4,242 |
| Gaining Insights Through Statistical Modeling | $4,242 | |
| Summer 2026 | Introduction to Data Science Computing Workflows | $4,242 |
| Telling Impactful Stories with Data Visualization | $4,242 | |
| Fall 2026 | Application of Real-World Data Science: A Capstone Experience | $4,242 |
| Total Investment | $21,210 | |
Additional Fees & Notes
- CMU measures coursework in units. Three units are equivalent to one credit hour.
- $240 technology fee will be assessed each semester (subject to change).
- Tuition rates are for the 2025/2026 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 applicants who apply by the priority deadline are eligible for a partial scholarship award. Applications recieved after the priority deadline may be eligible if funds are still available. Applicants are notified at the time of admission of scholarship awards. Scholarships are applied by course and are non-transferrable between courses or semesters.
All CMU alumni are eligible for a 20% scholarship.
The majority of our students take advantage of tuition reimbursement benefits at their company. While some policies won't cover certificate programs, since our are credit-bearing and results in a verifiable credential, many organizations will allow tuition benefits to apply.
Fall enrollment will help you maximize your tuition benefits. Most tuition benefit programs are based on calendar year so if you enroll in Fall 2026, you can use both your 2026 AND 2027 benefits to cover the program cost.
If your employer is uncertain about providing financial support, download this guide that highlights the value and benefits of completing an online certificate at Carnegie Mellon. Need specific documents to proceed with enrollment? Contact a Program Specialist for assistance. If you're ready to make more data-informed decisions, we're here to help you make that a reality.
CMU provides a monthly payment option, managed by Nelnet Campus Commerce, designed to help students spread out tuition payments into manageable monthly installments. This plan also offers the ease of online enrollment. Should you be admitted and choose to join us, we recommend registering for this plan early to fully benefit from the range of payment options available.
Please note: Nelnet payment plans do not carry over from one semester to the next. Therefore, students must re-enroll and establish a new payment plan at the beginning of each semester.
Download this guide to explore available payment options and see examples of how tuition can be structured throughout the semester.
Carnegie Mellon University provides services to veterans and their dependents who are eligible for Veterans Education Benefits under the Montgomery G.I. Bill®, Post-9/11 G.I. Bill, and Vocational Rehabilitation and Employment Program. Please note, our online graduate certificates are not currently eligible for the Yellow Ribbon program.
The process starts with an application directly to Veterans Affairs and 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.
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/fees.
All CMU Online graduate certificates are eligible for CMU tuition remission. Review the CMU tuition remission policy 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 with competitive interest rates and borrower benefits. See FastChoice, a free loan comparison service to easily research options.
Quality Online Learning for Working Professionals
Building data fluency is analytical, iterative, and demanding—and it requires a learning environment designed to support both rigor and flexibility.
Rigor – expect a rigorous learning experience with the same high academic standards as our on-campus offerings. It won’t be easy, but it will be worth it.
Flexibility – complete the program in less than a year with a combination of live-online classes coupled with self-paced activities you can complete when it’s most convenient for you.
| 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 learn-by-doing practices allow you to prepare, reflect, and master concepts on your own timeline, while ongoing faculty support ensures you remain connected. |
Start Your Application
Ready to Apply? Here's what you'll need to complete the application process for the Foundations of Data Science Online Graduate Certificate.
Complete the Online Application
Submit your application via the online portal.
Submit Your Resume/CV
Tell us more about your employment history, academic background, technical skills and professional achievements.
Submit Your Transcripts
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
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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By the Numbers
# 5
Nationally
for graduate statistics programs
21
Research Areas
and lab groups dedicated to real-world applications of statistics research