phd computer science carnegie mellon

Carnegie Mellon University School of Computer Science

Machine Learning - CMU

Phd program in machine learning.

Carnegie Mellon University's doctoral program in Machine Learning is designed to train students to become tomorrow's leaders through a combination of interdisciplinary coursework, hands-on applications, and cutting-edge research. Graduates of the Ph.D. program in Machine Learning will be uniquely positioned to pioneer new developments in the field, and to be leaders in both industry and academia.

Understanding the most effective ways of using the vast amounts of data that are now being stored is a significant challenge to society, and therefore to science and technology, as it seeks to obtain a return on the huge investment that is being made in computerization and data collection. Advances in the development of automated techniques for data analysis and decision making requires interdisciplinary work in areas such as machine learning algorithms and foundations, statistics, complexity theory, optimization, data mining, etc.

The Ph.D. Program in Machine Learning is for students who are interested in research in Machine Learning.  For questions and concerns, please   contact us .

The PhD program is a full-time in-person committment and is not offered on-line or part-time.

PhD Requirements

Requirements for the phd in machine learning.

• Completion of required courses , (6 Core Courses + 1 Elective)
• Mastery of proficiencies in Teaching and Presentation skills.
• Successful defense of a Ph.D. thesis.

Teaching Ph.D. students are required to serve as Teaching Assistants for two semesters in Machine Learning courses (10-xxx), beginning in their second year. This fulfills their Teaching Skills requirement.

Conference Presentation Skills During their second or third year, Ph.D. students must give a talk at least 30 minutes long, and invite members of the Speaking Skills committee to attend and evaluate it.

Research It is expected that all Ph.D. students engage in active research from their first semester. Moreover, advisor selection occurs in the first month of entering the Ph.D. program, with the option to change at a later time. Roughly half of a student's time should be allocated to research and lab work, and half to courses until these are completed.

Master of Science in Machine Learning Research - along the way to your PhD Degree.

Other Requirements In addition, students must follow all university policies and procedures .

Rules for the MLD PhD Thesis Committee (applicable to all ML PhDs): The committee should be assembled by the student and their advisor, and approved by the PhD Program Director(s).  It must include:

• At least one MLD Core Faculty member
• At least one additional MLD Core or Affiliated Faculty member
• At least one External Member, usually meaning external to CMU
• A total of at least four members, including the advisor who is the committee chair

Financial Support

Application Information

For applicants applying in Fall 2024 for a start date of August 2025 in the Machine Learning PhD program, GRE Scores are OPTIONAL. The committee uses GRE scores to gauge quantitative skills, and to a lesser extent, also verbal skills.

Proof of English Language Proficiency If you will be studying on an F-1 or J-1 visa, and English is not a native language for you (native language…meaning spoken at home and from birth), we are required to formally evaluate your English proficiency. We require applicants who will be studying on an F-1 or J-1 visa, and for whom English is not a native language, to demonstrate English proficiency via one of these standardized tests: TOEFL (preferred), IELTS, or Duolingo.  We discourage the use of the "TOEFL ITP Plus for China," since speaking is not scored. We do not issue waivers for non-native speakers of English.   In particular, we do not issue waivers based on previous study at a U.S. high school, college, or university.  We also do not issue waivers based on previous study at an English-language high school, college, or university outside of the United States.  No amount of educational experience in English, regardless of which country it occurred in, will result in a test waiver.

Submit valid, recent scores:   If as described above you are required to submit proof of English proficiency, your TOEFL, IELTS or Duolingo test scores will be considered valid as follows: If you have not received a bachelor’s degree in the U.S., you will need to submit an English proficiency score no older than two years. (scores from exams taken before Sept. 1, 2023, will not be accepted.) If you are currently working on or have received a bachelor's and/or a master's degree in the U.S., you may submit an expired test score up to five years old. (scores from exams taken before Sept. 1, 2019, will not be accepted.)

Graduate Online Application

• Admissions application opens September 4, 2024
• Early Application Deadline – November 20, 2024 (3:00 p.m. EST)
• Final Application Deadline - December 11, 2024 (3:00 p.m. EST)

Algorithms, Combinatorics and Optimization (ACO)

Carnegie Mellon University offers an interdisciplinary Ph.D program in Algorithms, Combinatorics, and Optimization (ACO). 

This program is the first of its kind in the United States. It is administered jointly by the  Tepper School of Business  (Operations Research group), the  Computer Science Department  ( Theory & Algorithms & Complexity Groups ), and the  Department of Mathematical Sciences  (Discrete Mathematics group).

The mathematics used by computer scientists and operations researchers overlap to a large extent. The boundaries between Operations Research and Computer Science have become blurred. Important new theories and whole fields, like polyhedral combinatorics, have been and are being developed jointly by computer scientists, operations researchers, and applied mathematicians who consider themselves a little bit of both. Presentations of new results on graphs and matroid theory can be heard at Operations Research conferences, while papers on linear programming, network flows, and matchings in graphs are frequently presented at Computer Science conferences. The mathematical content of the papers has become greater and more diverse. Yet, in spite of this, few Ph.D students graduate with an equally solid knowledge of all three areas.

The Ph.D program in Algorithms, Combinatorics, and Optimization at Carnegie Mellon is intended to fill this gap. The program brings together the study of the mathematical structure of discrete objects and the design and analysis of algorithms in areas such as graph theory, combinatorial optimization, integer programming, polyhedral theory, computational algebra, geometry, and number theory.

How to Apply

You may apply to the Ph.D. Program in Algorithms, Combinatorics, and Optimization through any of the three participating departments.

To apply for the ACO program though the Computer Science Department you need to apply via the  School of Computer Science  online application . Apply for the Ph.D. in Computer Science and  select the interdisciplinary program in the appropriate section of the online application .

Applicants will be selected for admission by the ACO faculty in consultation with committees in each home department. Financial support for students admitted into this program is available under the same conditions as for the other Ph.D. Programs at Carnegie Mellon.

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• Ph.D. in Computer Science
• Ph.D. in ACO
• Doctoral - How to Apply
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• Other SCS Doctoral Programs
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Ph.D. in HCI

CMU’s Ph.D. program in human-computer interaction is rigorous, creative, and deeply interdisciplinary .

The small and select group of students that we admit each year study with both the founders of the field of HCI and the newest generation of top scholars. Learn more about our program.

Our doctoral students engage in research from the moment they arrive, and take courses from across the computer sciences, the behavioral sciences, and the field of design.

The HCII doctoral program offers an inspiring, collaborative, and supportive atmosphere for graduate study. Ph.D. students with a range of backgrounds and interests are challenged with tracks allowing for specialization. HCII graduates have become the face of HCI across the world, pushing the boundaries of the kinds of problems that HCI addresses, and inventing the tools and methods used to address those problems. Our graduates carry out this mission through faculty positions in the top-ranked academic departments and positions in the major industry research laboratories.

Learn About Our Ph.D. Program

We invite you to learn more about our Ph.D. Program by visiting the following pages:

• Ph.D. Program Requirements

Emphasis Areas

• Ph.D. Program FAQ

Becoming part of the Ph.D. program means becoming part of our exceptional community. Please explore this website, contact our faculty, and apply to become part of our program.

Ph.D. Program

Current Students

Frequently Asked Questions

Program Requirements

Resources for Current Students

Outgoing Students & Postdocs

Ph.D. in Human-Computer Interaction Carnegie Mellon University 5000 Forbes Avenue Pittsburgh, PA 15213-3891

Leah Buffington Ph.D. Program Manager Phone: 412-268-5037 Email us

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Computer Science

Carnegie Mellon University's Ph.D. in Computer Science is, above all, a research degree. When the faculty award a Ph.D., they certify that the student has a broad foundation and awareness of core concepts in computer science, has advanced the field by performing significant original research and has reported that work in a scholarly fashion.

Carnegie Mellon University Multiple locations Pittsburgh , Pennsylvania , United States Top 0.5% worldwide Studyportals University Meta Ranking 4.0 Read 7 reviews

When you begin our Computer Science Ph.D. program at Carnegie Mellon University, you’ll take the Introductory Course for Doctoral Students — an intense two week program that orients you to the department, introduces you to research and education topics our faculty are interested in, helps you find a faculty advisor and familiarizes you with Carnegie Mellon’s resources. 

Features 

• Next, you’ll gain a broad understanding of fundamental research issues in major areas of computer science through coursework and original research. 
• Finally, you’ll write and orally defend a thesis that guarantees you understand the area well enough to advance the state of knowledge in the field.

Programme Structure

Curriculum: 

• As a Ph.D. student in computer science at CMU, you'll spend roughly five years acquiring a body of technical knowledge that includes a familiarity with the breadth of the field, as well as a deep understanding of your research area. 
• From your second month in the program, you'll work closely with your faculty advisor, who is charged with guiding your education and monitoring your progress through the program. 
• You'll take courses, teach and perform directed research — all to ensure that you leave Carnegie Mellon as an expert in your field.

Key information

• 120 months

Students will complete all requirements for the Ph.D. degree within a maximum of ten years from original matriculation as a doctoral student, or less

Start dates & application deadlines

• Apply before 2024-12-13 00:00:00

Disciplines

Academic requirements.

We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.

English requirements

We are not aware of any English requirements for this programme.

Student insurance

Make sure to cover your health, travel, and stay while studying abroad. Even global coverages can miss important items, so make sure your student insurance ticks all the following:

• Additional medical costs (i.e. dental)
• Repatriation, if something happens to you or your family
• Home contents and baggage

We partnered with Aon to provide you with the best affordable student insurance, for a carefree experience away from home.

Starting from €0.53/day, free cancellation any time.

Remember, countries and universities may have specific insurance requirements. To learn more about how student insurance work at Carnegie Mellon University and/or in United States, please visit Student Insurance Portal .

Other requirements

General requirements.

• Graduate Record Exam (GRE): GRE scores are highly recommended. If GRE scores are not submitted, please briefly explain in the statement of purpose section of your application.
• Language Exams: If you are an international applicant and your native language (language spoken from birth) is not English, an official copy of an English proficiency score report is required. The English proficiency requirement cannot be waived. 
• Transcripts: A PDF of your most recent transcript from each college and/or university you attended, even if no degree was granted.
• Resumé/CV:
• Statement of Purpose

Tuition Fee

Living costs for pittsburgh.

The living costs include the total expenses per month, covering accommodation, public transportation, utilities (electricity, internet), books and groceries.

In order for us to give you accurate scholarship information, we ask that you please confirm a few details and create an account with us.

Scholarships Information

Below you will find PhD's scholarship opportunities for Computer Science.

Available Scholarships

You are eligible to apply for these scholarships but a selection process will still be applied by the provider.

Read more about eligibility

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Carnegie Mellon University PhD in Computer Science

Featured programs, how much does a doctorate in computer science from carnegie mellon cost, carnegie mellon graduate tuition and fees.

Related Programs

Does carnegie mellon offer an online phd in computer science, carnegie mellon doctorate student diversity for computer science, male-to-female ratio.

Of the students who received their doctor’s degree in computer science in 2019-2020, 21.7% of them were women. This is higher than the nationwide number of 19.1%.

Racial-Ethnic Diversity

Racial-ethnic minority graduates* made up 17.4% of the computer science doctor’s degrees at Carnegie Mellon in 2019-2020. This is higher than the nationwide number of 10%.

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Electrical and Computer Engineering graduate programs

Carnegie Mellon’s Department of Electrical and Computer Engineering  (ECE) stands at the forefront of today’s rapidly evolving technology landscape. It equips students to emerge as leaders in the field by honing their engineering skills, fostering their creativity, and providing them with practical insights essential for innovating impactful solutions. The department actively contributes to advancing and sharing knowledge in diverse areas such as energy, healthcare, mobile systems, smart infrastructure, nanotechnology, storage systems, cyber-physical systems, data and network science, and more.

The ECE department offers a wide range of comprehensive graduate programs, including a doctor of philosophy and several master of science programs. The department’s reach spans well beyond Pittsburgh, with offerings in Africa , Portugal , Thailand , Silicon Valley , and Washington, D.C.

• Admission requirements
• Application deadlines

Doctor of philosophy program

• Doctor of Philosophy in Electrical and Computer Engineering  (Ph.D. in ECE) The Ph.D. in ECE program guides students through research-intensive study of electrical and computer engineering fundamentals. With the help of a faculty advisor, students define an education and research program consistent with their background and career goals. This program is offered at several locations, including Pittsburgh, Portugal, Thailand, and Washington, D.C.

Master’s programs

• Master of Science in Electrical and Computer Engineering  (MS in ECE) The department’s MS in ECE program provides students with a thorough background in the fundamentals of ECE, as well as the opportunity for in-depth specialization in specific areas of the field. This program is offered at several locations, including Pittsburgh, Africa, Thailand, and Silicon Valley.
• Master of Science in Artificial Intelligence Engineering - Electrical and Computer Engineering (MS in AIE - ECE) The MS in AIE - ECE is a three-semester program that gives students the opportunity to gain state-of-the-art knowledge of artificial intelligence from an engineering perspective. Today, AI is driving significant innovation across products, services, and systems in every industry, and tomorrow’s AI engineers will have the advantage.
• Master of Science in Software Engineering The MS in Software Engineering is a unique program offered exclusively at CMU’s Silicon Valley campus. It emphasizes a rigorous foundation in the core disciplines of software engineering. The program provides students with fundamental knowledge, skills, and first-hand experience in software engineering by balancing theory and practice, engaging active learning, and encouraging collaboration on projects drawn from real-world contexts.
• Dual Master of Science in Engineering and Technology Innovation Management  (MS in ETIM) The MS in ETIM program cultivates next-generation innovation leaders. Here, engineers and scientists develop the specialized business skills, frameworks, and technical acuity necessary to create and capture value from innovative technologies. Join an exceptional multi-disciplinary group of peers and professors who will help you shape the future.

Research areas

Healthcare and quality of life

Mobile systems

Smart infrastructure

Nanotechnology

Storage systems

Intelligent physical systems

Data and network science

Secure systems

Research facilities and engagements

Student experience

ECE graduate students join a global community of scholars and researchers, fostering diversity and collaboration at all levels. Students are encouraged to enhance their professional and technical skills through active participation in Carnegie Mellon’s student organizations .

• ECE Graduate Organization
• Carnegie Mellon Racing
• CMU Robotics Club
• Institute of Electrical and Electronics Engineers
• W3VC - Radio Club
• Society of Women Engineers
• National Society of Black Engineers
• Society of Hispanic Professional Engineers
• Society of Asian Scientists and Engineers
• Graduate Student Assembly

News & Events

Engineering students awarded Fulbright Scholarships

Six students and alumni from the College of Engineering will research and study abroad on Fulbright program scholarships.

Introduction to Amateur Radio course teaches history, culture, and science of radio technology.

Amateur radio for aspiring professionals

Undergraduates present research at Meeting of the Minds 2024

Engineering undergraduate students had a wonderful showing at Meeting of the Minds, displaying posters, giving presentations, and demonstrating projects they have worked on this past academic year.

CMU names University Professors

Three College of Engineering faculty members have been elevated to the rank of University Professor, the highest distinction a faculty member can receive at Carnegie Mellon.

Reeja Jayan named faculty director of the Center for Faculty Success

The relaunched Center for Faculty Success will provide professional development, training, and leadership opportunities that empower faculty to succeed throughout their academic careers.

Parry receives Goldwater Scholarship

Katherine Parry, a junior in electrical and computer engineering, has received the 2024 Barry Goldwater Scholarship to support her pursuit of a research career.

Honoring our educators

Six members from the College of Engineering were recognized at CMU’s annual Celebration of Education Awards.

Carnegie Mellon University has awarded professorships to five exceptional faculty members in the College of Engineering.

Engineering faculty awarded professorships

Grover inducted into AIMBE College of Fellows

The American Institute for Medical and Biological Engineering (AIMBE) has announced the induction of Pulkit Grover, professor of electrical and computer engineering, to its College of Fellows.

Health & Biomedicine

How does learning something new not overwrite what we know?

Researchers from Carnegie Mellon University and University of Pittsburgh examine what happens in the brain when it’s presented with learning a new task, but also asked to recall a familiar one.

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Energy & Environment

CMU partners to reimagine energy in the region

Faculty from Carnegie Mellon University will collaborate with West Virginia University and University of Pittsburgh on a National Science Foundation Regional Innovation Engines program.

2024 NSF CAREER Awards

The National Science Foundation (NSF) has awarded Giulia Fanti, Guannan Qu, and Akshitha Sriraman, all assistant professors of electrical and computer engineering, the NSF Faculty Early Career Development (CAREER) Award.

Xu Zhang received an NSF career grant for his work on device fabrication and system-level applications of atomically thin 2D materials.

Zhang receives NSF CAREER Award

Artificial Intelligence

PennDOT Secretary meets Carnegie Mellon transportation experts

PennDOT Secretary Michael Carroll visited CMU facilities at Mill 19 to meet transportation researchers and learn about collaboration opportunities.

New center to investigate quantum computing

A new National Science Foundation Industry-University Cooperative Research Center at CMU will create an ecosystem that advances quantum computing and information technologies.

Detecting brain tsunamis

Researchers from Carnegie Mellon University, the University of Pittsburgh, and the University of Cincinnati have combined their expertise in engineering and medicine to create a noninvasive method for detecting worsening brain injuries before they happen. This advancement could reshape neurocritical care.

Faculty and alumnus inducted into the National Academy of Engineering

College of Engineering dean, professor, and alumnus inducted in the National Academy of Engineering.

Relationships are key to the research and the researchers

Zeynep Ozkaya’s work in Jana Kainerstorfer’s biophotonicslab has helped her to better understand the signal processing principles she is learning in her electrical engineering courses.

Electrical and Computer Engineering

College of engineering, ms in artificial intelligence engineering.

The Master of Science in Artificial Intelligence–Electrical and Computer Engineering is a three-semester (97-unit) program that offers students the opportunity to gain state-of-the-art artificial intelligence knowledge from an engineering perspective. Today, AI is driving significant innovation across products, services, and systems in every industry, and tomorrow’s AI engineers will have the advantage.

ECE students within the program will learn how to design and build AI-orchestrated systems capable of operating within engineering constraints. At Carnegie Mellon, we are leading this transformation by teaching students how to simultaneously design a system’s functionality and supporting AI mechanisms, including both its AI algorithms and the platform on which the AI runs, to produce systems that are more adaptable, resilient, and trustworthy.

Students pursuing the MS in AIE will be able to:

• Demonstrate knowledge of artificial intelligence methods, systems, tool chains, and cross-cutting issues, including security, privacy, and other ethical, societal, and policy challenges
• Apply ECE concepts and tools to enable AI systems and produce AI tools
• Be informed practitioners of AI methods to solve ECE and related problems, applying ECE domain knowledge whenever possible to enhance AI effectiveness
• Understand the limits of AI systems and apply these techniques within these limits
• Evaluate trade-offs involving technical capabilities and limitations, policy, and ethics in artificial intelligent systems

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Endless Opportunities

Whether pursuing academia or industry, this degree uniquely positions students for the future of research and high-demand careers with a mastery of integrating engineering domain knowledge into AI solutions.

For additional information about this college-wide initiative, please visit the College of Engineering's  MS in AI Engineering website .

Carnegie Mellon University School of Computer Science

Master's programs.

SCS offers a wide range of professional and academic master's programs across its seven departments. Admissions and requirements vary by program and are determined by the program's home department.

Links to all departments and master's programs appear below. Additionally, our Master's Programs Comparison Data includes statistics, facts and other information for each program.

If you're interested in applying, be sure to visit our Graduate Admissions Overview page or read our Frequently Asked Questions .

All Master's Programs by Department

Ray and stephanie lane computational biology department, master of science in automated science: biological experimentation.

The M.S. in Automated Science program is the first of its kind and provides training for students to play roles in the development of highly automated systems for doing science. It provides training in the principles and hands-on use of robotic laboratory equipment, the fundamental computational biological methods for constructing predictive models in biology and medicine, and the methods of active machine learning and AI for automatically and iteratively choosing experiments to achieve a given goal. The program is designed for a diverse applicant pool and will be especially valuable to students with undergraduate degrees in biology seeking to gain advanced computational skills for jobs in the laboratory automation industry. Opportunities also exist for successful graduates to transition to Ph.D. programs.

Master of Science in Computational Biology

The M.S. in Computational Biology program seeks to train the world's best computational biologists at the master's level. The curriculum provides both breadth and depth of training in computational biology, and is built on a solid foundation of biology, computer science, statistics and machine learning (data sciences). The program is designed for students with backgrounds in quantitative and/or life sciences. Students often participate in summer research internships in life sciences, industry or academic research laboratories. MSCB graduates are prepared for rewarding jobs in industry or to pursue their doctoral degrees at top universities.

Computer Science Department

Fifth year master's in computer science.

The Fifth Year Master's in Computer Science is a direct master's program for students receiving a bachelor of computer science from Carnegie Mellon. The purpose and goal of the program is to encourage our very brightest undergraduates to become involved with research that broadens their often hectic undergraduate experience.

Master of Science in Computer Science

The Master of Science in Computer Science (MSCS) program offers students with a bachelor's degree the opportunity to extend their training with advanced study in computer science. Applicants should possess basic analytic skills and a strong aptitude for mathematics, programming and logical reasoning. A bachelor's degree in computer science is not required, but some scientific, engineering or mathematical background is an important predictor of success.

Human-Computer Interaction Institute

Accelerated master of human-computer interaction.

The Accelerated Master of Human-Computer Interaction program provides CMU undergraduate HCI majors with an opportunity to complete a master's in human-computer interaction in an additional two semesters following graduation. Accepted students join the MHCI capstone in the spring semester of their senior year, graduate in May with their undergraduate degree, and then go right into being a graduate student in the summer while completing their capstone project with MHCI. The fall semester allows them to complete their electives for the master's portion of the program. Students should apply by Nov. 1 of their senior year.

Master of Educational Technology and Applied Learning Science (METALS)

This interdisciplinary program trains students to design, develop and evaluate evidenced-based programs for learning in traditional and nontraditional settings. Graduates will be prepared to take key positions in corporations, universities and schools as designers, developers and evaluators of educational technologies, as well as learning engineers, curriculum developers, learning technology policy-makers and even chief learning officers.

Master of Human-Computer Interaction

The Master of Human-Computer Interaction (MHCI) program is the first in the world dedicated to preparing professionals for careers related to human-computer interaction, user-experience design and user-centered research. The MHCI program integrates service and design thinking into a rigorous HCI curriculum that prepares our students to design and guide the future of human and technology interactions.

Master of Science in Product Management

This 12-month master's program, a joint effort with the university's Tepper School of Business, provides both the technical skills and business acumen students need to be successful in this high-demand area. A required internship and capstone project supply the practical skills students need to return to industry prepared for their new careers.

Language Technologies Institute

Master of computational data science.

The Master of Computational Data Science (MCDS) concentrates on applying the scientific method to very large data systems. The degree focuses on scientific experimental design, data collection, data modeling and analysis, problem solving, and human-computer interaction. These problem areas are addressed through a core computer science curriculum consisting of software engineering, machine learning, statistics, large scale distributed systems, storage systems, etc. The degree trains technologists to create new large scale data science systems.

Master of Science in Artificial Intelligence and Innovation

The Master of Science in Artificial Intelligence and Innovation (MSAII) equips you to identify potential artificial intelligence applications, and develop and deploy AI solutions to large practical problems. Students work in teams to implement AI systems that are responsive to market needs.

Master of Science in Intelligent Information Systems

The Master of Science in Intelligent Information Systems (MIIS) degree focuses on recognizing and extracting meaning from text, spoken language, video, and other forms of unstructured information. It provides deep exposure to content analysis and machine learning.

Master of Science in Language Technologies

The Master of Science in Language Technologies is a research-oriented degree in the areas of speech processing, language processing, information retrieval, machine translation and machine learning. Most MLT students are affiliated with an advisor's research project, in which they gain hands-on experience with advanced research and state-of-the-art software. An optional master's thesis project may also be chosen.

Online Graduate Certificate in Machine Learning and Data Science Foundations

Organizations know how important data is, but they don’t always know what to do with the volume of data they have collected. That’s why CMU designed the online Graduate Certificate in Machine Learning and Data Science Foundations — to teach technically savvy professionals how to leverage AI and machine learning technology to harness the power of large scale data systems. This 12-month, 100% online program will prepare participants for the staggering amount of data generated by today’s rapidly changing world. 

Machine Learning Department

Fifth year master's in machine learning.

The Fifth Year Master's in Machine Learning allows Carnegie Mellon undergraduates to earn an MS degree in one additional year by taking some of the required ML courses as an undergraduate.

Master of Science in Machine Learning

The world's first and top-ranked machine learning program gives students the tools they need to solve real-world problems by using advanced machine learning techniques and developing their own learning algorithms. This program includes three semesters of courses, plus an internship in industry or research with our world-class, interdisciplinary faculty. It strengthens students' skills in computer science and statistics to provide exceptional training for future leaders in the field.

Robotics Institute

Master of science in computer vision.

Computer vision is the study of acquiring and interpreting visual imagery. As the technology matures, its applications in industry continue to expand exponentially in areas of great commercial value. The goals of the 16-month (three semesters plus summer) MSCV program are to provide a robust set of courses encompassing current and emerging state-of-the-art computer vision topics that prepare students for careers in this field, and to facilitate hands-on experience through real research and development projects addressing current applications.

Master of Science in Robotics

The robotics master of science program brings together areas of robotics research that would otherwise be spread across different departments or separate universities, preparing students to take a leading role in the research and development of future generations of integrated robotics technologies and systems.

Master's in Robotic Systems Development

The Master's in Robotic Systems Development (MRSD) is an advanced graduate degree with a combined technical/business focus for recent graduates/practicing professionals already engaged in, or wishing to enter, the robotics and automation field as practitioners in the commercial sector.

Software and Societal Systems

Master of science in information technology - privacy engineering.

The Master of Science in Information Technology - Privacy Engineering (MSIT-PE) is a 12- or 16-month program designed for computer scientists and engineers who wish to pursue careers as privacy engineers or technical privacy managers. Designed in close collaboration with industry and government, this program is intended for students who aspire to play a critical role in building privacy into future products, services and processes.

Master of Software Engineering

This program is designed for software professionals with at least two years of experience who want to learn best practices in managing large, diverse software development projects with a focus on software architecture and software project management. The MSE program emphasizes increased industry engagement in small groups with greater elective flexibility.

Master of Software Engineering - Embedded Systems

For entry-level software developers with less than two years of experience, the MSE-ES program focuses on software design for internet of things (IoT) and cyber-physical systems using microcontrollers with real-time actuators and sensors. The program includes a required summer internship and team project with professional mentors.

Master of Software Engineering - Scalable Systems

Designed for entry-level software developers with less than two years of experience, the MSE-SS program focuses on achieving business objectives through high-velocity, continuous integration for large-scale, data-intensive and intelligent systems. The program includes a required summer internship and team project with professional mentors.

Master of Software Engineering Online

This program is for software professionals with at least two years of experience who want to learn best practices in managing large, diverse software development projects with a focus on software architecture and software project management. The MSE Online program is part-time and culminates in a reflective practice thesis.

Our Master's Programs Comparison Data includes statistics, facts and other information for each program.

View our Master's Programs Comparison Data Sheet

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Foundations of Data Science

Online Graduate Certificate

Unleash Your Inner Data Scientist

Everyone can learn to understand and leverage data - even you.

The volume and complexity of data has exploded in recent years, creating new challenges for organizations that want to leverage its power. To stay competitive, organizations need a mixture of data analysts and non-technical leaders who can understand the foundations of data science to collaborate effectively on how to apply it across the organization.

This emphasis on data literacy reveals a promising opportunity for professionals in every department in nearly every industry: with fundamental skills in data science, professionals can make more data-informed decisions and lead with confidence to help their teams (and ultimately, their companies) achieve goals and reach targets more efficiently. 

Data science for all

You don’t need a technical background to think like a data scientist. You just need the right education and support. In Carnegie Mellon’s new online Graduate Certificate in Foundations of Data Science, professionals from all backgrounds (both technical and non-technical) will learn how to unlock the power of data through graduate-level, credit-bearing coursework taught by expert CMU professors. 

By the end of our carefully designed program, you should feel confident: 

• Performing exploratory data analysis, creating high-quality statistical graphs and communicating the ‘story behind the data’ to different audiences.
• Asking the right data questions before using and analyzing that data to solve real-world problems.
• Applying fundamental techniques in probability and statistical inference to real-life data analysis problems.
• Structuring basic data pipelines with a modern coding language, and building, validating and interpreting statistical models and algorithms.

A powerful certificate that flexes with your schedule

The Graduate Certificate in Foundations of Data Science is offered 100% online with a combination of live-online classes with faculty and work you will do on your own time. As a result, it's easy for you to fit the program into your busy, day-to-day life. To earn the certificate, you will complete five rigorous CMU classes over a 12-month period, including a capstone course where you’ll work with real-world data and subject matter experts to apply the skills you’ve gained throughout the program.

For the leaders and innovators 

This cutting-edge certificate is best suited for:

• Recent graduates with a bachelor’s degree from an accredited college or university who want preparation to enroll in a master’s level program that leads to a more lucrative career in data science. 
• Industry professionals in any field who recognize the power of data and would like to communicate better with data scientists in their company and/or adopt a more data-centric mindset when solving problems in their current role. Throughout this program, students will build a foundational level of data fluency that will help them communicate with stakeholders and make more data-informed decisions at work. 
• Managers and supervisors across all industries who want to integrate (more) data into their team’s workflow. By the end of this program, students will have the confidence to approach complex datasets in the workplace and perform statistical analysis to make better decisions that will improve the overall efficiency and performance of their team.

Leaders in Transformative Education

In the Statistics & Data Science department at CMU, our faculty blend evidence-based pedagogical practices with experiential learning opportunities to create an effective learning environment for all students. While our faculty at CMU are known for their expertise in data science, don’t be intimidated - they are also known for using evidence-based teaching practices that support students as they begin their journey into the world of data science. 

At a Glance

Start Date August 2024

Application Deadlines Final: July 30, 2024

A limited number of partial scholarships are still available. Apply by the final deadline to be considered for these awards.

Program Length 12 months

Program Format 100% online

Live-Online Schedule 1x per week for 60 to 90 minutes in the evening

Taught By Dietrich College of Humanities and Social Sciences

Request Info

Questions? There are two ways to contact us. Call 412-501-2686 or send an email to  [email protected]  with your inquiries .

CMU Online Graduate Certificates

Below, explore more online opportunities offered by Carnegie Mellon University.

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Generative AI & Large Language Models Enhance your expertise in the latest techniques in GenAI, deep learning, large language models, and multimodal machine learning with this program from the School of Computer Science.

AI Engineering Fundamentals Have a mechanical engineering degree, a familiarity with Python and an eagerness to design next-generation solutions? This program from the College of Engineering could be for you.

AI Engineering for Digital Twins & Analytics Learn how to lead the implementation of AI + Digital Twins for your organization from world-renowned experts in CMU's College of Engineering.

Managing AI Systems If you are interested in driving the adoption of AI in your organization, then this program from the Heinz School of Public Policy is for you. No technical expertise is required for admission.

On-Campus Degree

Interested in the on-campus Master of Science in Applied Data Science offered by the Dietrich College of Humanities & Social Sciences? Visit the program website for more details.

Number five in the nation for our graduate statistics program.

More than fifty faculty members in the Statistics & Data Science Department

Twenty-one research areas and lab groups dedicated to real-world applications of statistics research.

Language Technologies Institute

School of computer science.

Diaz Inducted into SIGIR Academy

Lti associate professor fernando diaz has been inducted into the academy of the special interest group on information retrieval.

By Bryan Burtner

• bburtner(through)cmu.edu
• 412-268-2805

LTI Associate Professor Fernando Diaz was recently honored with induction into the Special Interest Group on Information Retrieval (SIGIR) Academy . 

The Academy was established " to honor and recognize individuals who have made significant, cumulative contributions to the development of the field of information retrieval (IR)," according to the SIGIR website. Inductees must have made "significant technical contributions (scientific or industrial) and/or significant community service contributions" to the IR community, through cumulative contributions to the field, impact of new research, influence on the work of others, and active participation in SIGIR.

SIGIR is a subgroup of the Association for Computing Machinery (ACM) , and is among the top organizations globally in the field of Information Retrieval.

Diaz, a member of the LTI faculty since 2023, focuses his IR research on the design of search engines that enhance meachine learning systems and support of "tip of the tongue" information needs. He also conducts research in the field of evaluation of language technologies, including the measurement of "unfairness" and other harms in language technologies, and the identification and measurement of the impact of artificial intelligence on cultural industries such as music, film and literature.