phd in computer science at brown university

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The department of Computer Science offers two graduate degrees in computer science. The Master of Science (Sc.M.) degree for those who wish to improve their professional competence in computer science or to prepare for further graduate study, and the Doctor of Philosophy (Ph.D) degree.

For more information on admission, please visit the following website:

http://www.brown.edu/academics/gradschool/programs/computer-science

Ph.D. Requirements

Requirements for the Ph.D. program can be found at  https://cs.brown.edu/degrees/doctoral/reqs/reqs_phd.2015.pdf

Requirements for the Masters Degree

The requirements consist of a basic component and an advanced component. All courses must be at the 1000 level or higher. All courses must be completed with a grade of B or better.

The courses in student's program must be approved by the director of the Master's program (as well as by the student's advisor).

Basic Component

The basic component consists of six courses. None of these courses may be reading and research courses such as  CSCI 2980 .

The six courses are chosen as follows:

• Two must be CS courses that form a pathway (see the explanation of pathways at https://cs.brown.edu/degrees/undergrad/concentrating-in-cs/concentration-requirements-2020/pathways-for-undergraduate-and-masters-students/
• One must be a CS course in an area that’s not listed in the chosen pathway (it must not be a core course, must not be a grad course, and must not be a related course of the pathway).
• The three additional courses must be in CS or related and must be approved by your advisor or the director of graduate studies (master’s). Getting this approval will require you to show that the courses are relevant to your CS interests. In general, the more non-CS courses you wish to take, the stronger your justification must be. 

Advanced Component

The advanced component requires the student to complete one of the following six options. Reading and research courses (such as CSCI 2980 ) may be used as part of options 1, 2, 3, and 4, but not as part of options 5 and 6. An “advanced course,” as used below, is either a 2000-level CS courses or a 1000-level CS courses that includes a Master's supplement. Master's supplement are nominally half-credit courses, but students may do the work of these courses without officially registering for them. Examples of such supplements are CSCI 1234 (supplementing CSCI 1230 ), CSCI 1690 (supplementing CSCI 1670 ), and CSCI 1729 (supplementing CSCI 1730 ).

“Internships”, as used below, must be approved by the student's advisor and are paid work in the area of the student's master's studies. They may be full, or part time. A full-time internship must last at least two months but no more than four months. A part-time internship must last at least four months but no more than six months. Normally the internship will be performed between the student's second and third semesters in the program.

The six options are:

• Complete a thesis supervised by her or his advisor and approved by a committee consisting of the advisor and at least one other faculty member.
• Complete a thesis supervised by her or his advisor and approved by a committee consisting of the advisor and at least one other faculty member, and complete an internship.
• Complete a project supervised and approved by her or his advisor.
• Complete a project supervised and approved by her or his advisor, and complete an internship.
• Complete two advanced courses.
• Complete two advanced courses and complete an internship.

Students entering the Master's program typically have one of two goals: they intend to pursue research in Computer Science and are preparing themselves to enter Ph.D. programs, or they intend to become professional computer scientists and pursue careers in industry. In both cases, students should take collections of courses that not only give them strength in particular areas of Computer Science, but also include complementary areas that familiarize them with other ways of thinking about the field. For example, a student whose interests are in the practical aspects of designing computer systems should certainly take courses in this area, but should also be exposed to the mindset of theoretical computer science. In a rapidly changing discipline, there is much cross-fertilization among areas and students should have some experience in doing advanced work in areas not directly related to their own.

A student whose goal is a research career should become involved as quickly as possible with a research group as part of their Master's studies, and demonstrate and learn about research by participating in it. The resulting thesis or project report will serve to establish her or his suitability for entering a Ph.D. program.

A student whose goal is to be a professional computer scientist should have some professional experience as part of her or his preparation. A certain amount of coursework is required before a student can qualify for a pedagogically useful internship. Students with limited experience in Computer Science should take a few advanced Computer Science courses before embarking on an internship. Other students, particularly those whose undergraduate degrees were at Brown, will have had internship experiences while undergraduates. Internships provide insights for subsequent courses and project work at Brown. Students without such experiences are at a disadvantage with respect to their peers. Thus we strongly encourage students who have not had such experience to choose of of options 2, 4, and 6, for which internships are required.

Note that these internships are not courses and the work is not evaluated as it would be for a course. Students' advisors will assist them in choosing and obtaining internships, but it is up to students themselves to ensure that they get as much benefit as possible from their experiences. They must be able to take advantage of these experiences while completing their Master's projects – we expect as high-quality work from them as we do from students who entered the program with prior internship experiences.

A Master's degree normally requires three to four semesters of full-time study, depending upon one's preparation. 

Concurrent ScB (NUS) and ScM in Computational Biology (Brown University)

The School of Computing at National University of Singapore and The Department of Computer Science at Brown have established a concurrent Bachelor’s and Master’s degree program in Computational Biology. After having first completed four years of under- graduate study at National University of Singapore (NUS), qualified students will attend Brown University to complete their fifth and final year of study in computational biology. After the successful completion of requirements set forth by both universities, the students will simultaneously earn both their Sc.B. and Sc.M. degrees. The Sc.B will be awarded by the National University of Singapore, while the Sc.M. is awarded by Brown University.

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Brown University PhD in Computer Science

Computer Science is a concentration offered under the computer science major at Brown University. We’ve pulled together some essential information you should know about the doctor’s degree program in computer science, including how many students graduate each year, the ethnic diversity of these students, and more.

If there’s something special you’re looking for, you can use one of the links below to find it:

• Graduate Cost
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Featured Programs

Learn about start dates, transferring credits, availability of financial aid, and more by contacting the universities below.

AS in Computer Science

Learn the applied programming skills needed to fill in-demand tech roles when you earn your online AS in Computer Science at Southern New Hampshire University.

BS in Computer Science

Learn the front-end design and back-end development skills employers look for in full stack software developers with this online bachelor's degree in computer science from Southern New Hampshire University.

BS in Computer Science - Software Engineering

With a software engineering degree, you'll learn the fundamental concepts and principles – a systematic approach used to develop software on time, on budget and within specifications – throughout your online college classes at SNHU.

How Much Does a Doctorate in Computer Science from Brown Cost?

Brown graduate tuition and fees.

During the 2019-2020 academic year, part-time graduate students at Brown paid an average of $0 per credit hour. No discount was available for in-state students. Information about average full-time graduate student tuition and fees is shown in the table below.

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MS in Information Technology - Software Application Development

Learn to manage the development process for a software program with this specialized online master's from Southern New Hampshire University.

Does Brown Offer an Online PhD in Computer Science?

Brown does not offer an online option for its computer science doctor’s degree program at this time. To see if the school offers distance learning options in other areas, visit the Brown Online Learning page.

Brown Doctorate Student Diversity for Computer Science

Male-to-female ratio.

About 44.4% of the students who received their PhD in computer science in 2019-2020 were women. This is higher than the nationwide number of 19.1%.

Racial-Ethnic Diversity

Of those graduates who received a doctor’s degree in computer science at Brown in 2019-2020, 11.1% were racial-ethnic minorities*. This is about the same as the nationwide number of 10%.

*The racial-ethnic minorities count is calculated by taking the total number of students and subtracting white students, international students, and students whose race/ethnicity was unknown. This number is then divided by the total number of students at the school to obtain the racial-ethnic minorities percentage.

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More about our data sources and methodologies .

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Data Science Institute

Data science institute at brown.

The mission of the Data Science Institute (DSI) at Brown is to stimulate innovation and support people aspiring to improve lives in our data-driven world.

DSI engages people across campus and beyond, to: 

• Educate all in data fluency and advanced area-specific applications of data science methods 
• Stimulate large-scale multidisciplinary research developing and applying data science methods to multiple data modalities
• Ensure that the power of data be leveraged toward a more equitable society

Opportunities at DSI

• Faculty Position: Professor of the Practice of Data Science

Upcoming Events

Recent news, best paper award for dsi's cristina menghini and cs colleagues stephen bach and yong zheng-xin, old concept, new implications: brown scholars interrogate how ai is changing the world, dsi's scientific machine learning research group gets published in nature, academic programs.

Undergraduate Programs

Data Science options for undergraduates include a Certificate in Data Fluency and the Data Science Fellows program trains undergraduates to collaborate with faculty to build more data science into course curricula.

Graduate Programs

DSI offers a master's degree in Data Science and a doctoral certificate, designed for students from a broad range of educational and work backgrounds.

Graduate Programs

Biostatistics.

The doctoral program in Biostatistics provides the training necessary to carry out independent research in theory, methodology and the application of statistics to important problems in biomedical research, including research biology, public health and clinical medicine.

The Ph.D. program is administered by an active, expanding and highly interdisciplinary faculty in the Department of Biostatistics. Major areas of research activity include Bayesian inference, analysis of biomarkers and diagnostic tests, causal inference and missing data, time series and functional data analysis, modeling of social networks, bioinformatics, longitudinal data, and multilevel modeling. Faculty collaborate actively with investigators in the areas of cancer prevention and screening, behavioral sciences, HIV/AIDS, health care policy, genetic epidemiology, neuroscience, and genomics.

Additional Resources

All PhD graduate students are provided with a new laptop computer and office space.  Students also have access to the computing infrastructure at the Center for Statistical Sciences, a high-end, continuously updated computing environment featuring both Unix and PC/MAC networks, with access to all major software for data analysis and numerical computing. CSS also maintains a considerable collection of statistics texts and journals in the Walter Freiberger Biostatistics Library.

Application Information

MCAT or LSAT tests cannot be substituted for the GRE. Applicants to the Ph.D. program should have taken courses in calculus (three semesters), and advanced undergraduate courses in linear algebra and probability. Experience with numerical computing is also recommended. Applications from students in applied fields such as biology, biochemistry, economics, and computer science are strongly encouraged, with the understanding that necessary mathematical coursework may have to be completed before or soon after enrollment in the program.

Applicants to this School of Public Health program should apply through  SOPHAS , a centralized application service for accredited schools and programs in public health. Brown University School of Public Health GRE reporting code: 7765.

Application Requirements

Gre subject:.

Not required

GRE General:

Official transcripts:, letters of recommendations:.

(3) Required

Personal Statement:

Additional materials:.

Application Fee

Additional Requirements:

International applicants.

• Language Proficiency (TOEFL or IELTS if applicable)
• Transcript Evaluation (if applicable)

Dates/Deadlines

Application deadline, completion requirements.

For all Ph.D. students, 24 credits are required of students matriculating in the program without a master's degree; 16 are required beyond the master's. For those with a related master's degree, up to eight units can be transferred. Both written and oral exams, plus a dissertation comprising an original contribution to the field, also are required. Students are expected to participate in academic activities such as the Statistics Seminar and faculty–organized working groups.

Alumni Careers

Contact and Location

Department of biostatistics, mailing address.

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Graduate Programs

The graduate program provides students the opportunity to perform research in cutting-edge areas of contemporary physics. The Department of Physics offers graduate student research opportunities in theoretical and experimental physics in condensed matter, high energy and particles, cosmology, astrophysics and biophysics.

Opportunity and Community

The graduate program comprises more than 100 graduate students from many different countries and backgrounds. We offer responsive advising throughout the duration of the program, from academic advising in the early stages to career counseling and post-graduation opportunities. In addition, the Graduate Program is enriched with multiple seminars, colloquia, workshops, and conferences that provide an opportunity for students to engage with visiting scholars.

Our graduate students train with 30 physics professors and 12 joint and affiliated faculty, primarily in engineering, applied mathematics, biology and chemistry . Multidisciplinary inquiry is encouraged. The academic program is rigorous yet flexible, combining strong core training with multiple options for more specialized studies. We foster a strong sense of community not always found in larger departments. Brown’s affiliations provide national and international research opportunities . Easy access to seminars and courses of the greater Boston area universities enriches our intellectual life.

The department is the host of the  Center for the Fundamental Physics of the Universe  and the  Brown Theoretical Physics Center . Several department members participate in large national and international collaborations, such as the Large Hadron Collider. 

Program Leaders

Director of graduate studies (dgs).

James Valles, Jr.

Professor Valles handles all Ph.D. program and student issues, including degree requirements and milestone completion, transfer credit, etc.

Professor Valles is an experimental condensed matter physicist. He studies superconductivity and electron correlation effects in disordered metals and nanostructures. He also investigates effects of strong magnetic fields in cell biology and bio-polymerization.

Director of the Master's Program (DMP)

Professor Tang handles all Sc.M. program and student issues, including admission, advising, degree requirements, etc.

Professor Tang is an experimental biological physicist. His research focuses on cell mechanics and mobility and addressing outstanding questions on morphology, pattern formation, force generation and mobility of bacteria and other cells.

Graduate Students of Color in STEM at Brown University

GSOCnSTEM is a student-driven graduate organization that hosts social events, seminar series and outreach activities focusing on the advancement of graduate students of color in STEM at Brown University.

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PhD student receives fellowship from Apple Scholars program

Nataliya Nechyporenko, a computer science Ph.D. student, has received a PhD fellowship in AI and Machine Learning (AIML) through the Apple Scholars program . The program was created by Apple to recognize the contributions of emerging leaders in computer science and engineering at the graduate and postgraduate level. 

The fellowship provides Nechyporenko support for her research and academic travel for two years, internship opportunities and a two-year mentorship with an Apple researcher. 

Let's learn more about Nechyporenko's research aims and her perspective on the future of robotics research: 

What research do you hope to accomplish through this fellowship?

Think about how you might manually feel around an object to understand its shape, weight, and texture. Or if something is in your way, you'd just push it aside without overthinking it. If you drop something, you'll persistently keep trying to pick it up from different angles until you get it. As you're doing these everyday tasks, you're constantly building up an intuitive sense of your surroundings through trial-and-error. That's the kind of resourceful, flexible, multi-sensory approach I want robots to have when manipulating things – rather than just blindly following a fixed routine. 

The goal is for robotic arms to move and behave with that same kind of curious, improvisational, problem-solving spirit we take for granted as humans. As an Apple AIML scholar, I hope to gain insights into this problem with the help of a fresh network of mentors and collaborators.  

Is this an extension of work you are already doing in your lab? If so, how?

Driven to establish contact-rich planning as a dominant feature in robotics, I focused the first two years of my PhD on analyzing the methods used by state-of-the-art planners and solving the shortcomings leading to the lack of physical robot interaction. 

I have started to extend this work by integrating the empirical formulation of machine learning with model-based algorithmic approaches. I believe this is the path to making robots more adaptable to chaotic human environments. I will continue this work as an Apple scholar. 

What do you think of the current hype around AI and ML? What do you wish people understood about this research area?

The AI and machine learning hype trains have been barreling full steam ahead lately. But robotics? That's an entirely different beast that doesn't follow the overnight disruption narratives. It's a synergy of achievements in areas like materials, manufacturing, sensing, controls theory, and others aligning to reshape the physical world. 

The robotics future will reshape industries and labor concepts, but it will be catalyzed through the patient advancement of many disciplines.

How did you come to study at CU Boulder?

I spent a couple years in the trenches, getting my hands dirty actually building and deploying robots in industry. But after a while, I got this craving -- like there was so much more potential waiting to be unlocked if I could really dive into the deep scientific questions around robotics. That's why I decided to take the plunge back into academia.

What is one of your plans or hopes for the future, either professionally or personally?

I hope to be an expert, a leader, a thinker and a builder. Outside of research endeavors, I aim to be a leader and educator for the robotics and the AI community. Previously, I’ve led volunteering activities, mentored students, and co-organized events that foster discussions around AI. I hope to continue to do so in the future at a larger scale. 

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Nataliya Nechyporenko

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U.S. News Ranks UT Austin Computer Science Among Best in Graduate Program Rankings

The 2024-2025 rankings tout computer science at The University of Texas at Austin as among the seven best nationally.

U.S. News and World Report graduate rankings

The University of Texas at Austin continues to be one of the premier schools for graduate studies, according to U.S. News & World Report’s partial release of its most recent “Best Graduate Schools.” UT made gains in several disciplines, including computer science.

Overall, the University has 42 graduate schools and specialty programs ranked in the top 10 when combined with previous years, including a dozen in the College of Natural Sciences. The publication updates some of its specialty rankings each year and republishes the most recent rankings in other areas. Additionally, U.S. News delayed release of some rankings.

“These numbers are meaningful. Having more than 40 schools, programs and specialties ranked in the top 10 in this partial release alone, including several that are the best in the country, if not the world, is reflective of our ability to continue to attract exceptional faculty and students,” said President Jay Hartzell. “Our talent is what puts UT at the leading edge of discovery in AI and robotics, life sciences, population research, and many other disciplines that are at the forefront of solving many of the world’s most pressing problems and bettering society.”

The College of Natural Sciences has 12 programs and specialties ranked among the top 10 in the most recent ranking for a discipline, the most of any college or school at UT Austin. Computer Science (No. 7) scored top 10 rankings in all four discipline’s specialties that are ranked within departments. 

U.S. News & World Report’s graduate rankings, which are published separately from the magazine’s yearly ranking of undergraduate programs, are considered the gold standard of graduate and professional rankings. They are based on surveys of academic leaders and, for select programs, additional quantitative measures including placement test scores, student/faculty ratios, research expenditures and job placement success.

UT Austin graduate schools, programs and specialties within Natural Sciences that U.S. News & World Report ranked this year or last are listed below.

Chemistry – 16*

• Analytical – 4*
• Inorganic – 14*
• Organic – 20*
• Physical – 14*

Computer Science – 7

• Artificial Intelligence – 9
• Programming Language – 7
• Systems – 10

Mathematics – 13*

• Algebra / Number Theory / Algebraic Geometry – 19*
• Analysis – 8*
• Applied Math – 7*
• Topology – 8*

Physics – 13*

• Cosmology/Relativity/Gravity – 10*
• Condensed Matter – 22*

Statistics – 27* 

* Ranking not revised for 2024-25.   In the most recent life science rankings from U.S. News, UT Austin ranked in the top 25 for biological sciences, including ranking 8th in ecology/evolutionary biology; in the most recent ranking for plasma physics, UT ranked third.

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Announcements

New Advanced Quantum Science Institute Will Bridge Basic Research and Applied Science

April 5, 2024 • by Marc Airhart

Top Prize Image in Visualizing Science Contest Captures Research Tied to the Sun

March 26, 2024 • by Steven E. Franklin

Undergraduate Researchers Help Unlock Lessons of Machine Learning and AI

March 20, 2024 • by Amelia Engstrom

• Equity & Inclusion

U.S. News & World Report ranks UC Berkeley computer science graduate program No. 1

UC Berkeley’s computer science graduate program was ranked first in the nation for the second year in a row by U.S. News & World Report , according to 2024 rankings  released April 8.

Berkeley’s program in the Department of Electrical Engineering and Computer Sciences shared the top spot with computer science programs at the Massachusetts Institute of Technology, Stanford University and Carnegie Mellon University. 

Several other Berkeley graduate programs in business, public health, public affairs and more were listed in the top 20 for their disciplines. These rankings are based on a survey of academics at peer institutions, according to U.S. News .

Berkeley’s Department of Electrical Engineering and Computer Sciences is shared by the College of Computing, Data Science, and Society and the College of Engineering. Learn more about Berkeley’s computer science graduate program.

PhD student James Madeley awarded Internet Society fellowship

Computer Science PhD student James Madeley will spend the next six months working on an exciting project with the Internet Society after being awarded a fellowship.

Computer Science PhD student James Madeley recently celebrated success after being awarded the Pulse Research Fellowship from the Internet Society.

James, who studied his bachelor's degree in Computer Science and is currently in the third year of his doctoral degree, both at Loughborough University, will be working with the Internet Society Pulse Research team to develop his project titled: LocalViz: Measuring and Visualizing Internet Traffic Locality.

Talking about the announcement, James said: "I was thrilled to find out that I was awarded the fellowship. The Internet Society does a lot of great work, so being able to take part in research working towards their 50/50 Vision is an exciting prospect."

James' project will focus on measuring how much internet traffic remains in the country it originates from. He will aim to measure how much traffic a country produces, where this traffic goes, and how the results can be clearly communicated. James explains that this is key because local traffic is cheaper, faster, and leads to improved resilience.

He added: "For example, if you are accessing government or news websites from your own country, it makes sense to go direct to the data, rather than sending the data across expensive international links to end up back in the country you started from. This is easily done in countries with lots of infrastructure but can be very challenging in countries that are less developed. Understanding the current state of traffic is a key step towards increasing locality for countries that need it most."

James said he is excited to be working on a project that aligns with Loughborough's strategic theme of creating 'vibrant and inclusive communities' and its overall strategy of ' Creating Better Futures. Together. '

James explains: "My project fits perfectly within this strategy, aiming to deliver meaningful and impactful research that can go on to provide global benefits. Understanding the current state of traffic on the Internet is crucial to shaping how it develops and, although a six-month fellowship is only a small part of the bigger picture, Loughborough is a fitting place to start such a journey."

James hopes to publish at least one academic paper during his fellowship and will provide updates through blog posts as the project progresses, as well as creating measurement tools and a visualisation platform that can be used by the Internet Society for their longer-term research goals.

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Master of Computational Data Science

The Master of Computational Data Science (MCDS) program focuses on engineering and deploying large-scale information systems, and includes concentrations in Systems, Analytics, and Human-Centered Data Science.

Requirements

The MCDS program offers three majors: Systems, Analytics, and Human-Centered Data Science. All three require the same total number of course credits, split among required core courses, electives, data science seminar and capstone courses specifically defined for each major. The degree can also be earned in two different ways, depending on the length of time you spend working on it. Regardless of the timing option, all MCDS students must complete a minimum of 144 units to graduate.

Here are the options:

• Standard Timing — a 16-month degree consisting of study for fall and spring semesters, a summer internship, and fall semester of study. Each semester comprises a minimum of 48 units. This timing is typical for most students. Students graduate in December.
• Extended Timing — a 20-month degree consisting of study for fall and spring semesters, a summer internship, and a second year of fall and spring study. Each semester comprises a minimum of 36 units. Students graduate in May.

Core Curriculum

All MCDS students must complete 144 units of graduate study which satisfy the following curriculum:

• Five (5) MCDS Core Courses (63 units)
• Three courses (3) from one area of concentration curriculum (36 units)
• Three (3) MCDS Capstone courses (11-635, 11-634 and 11-632) (36 units)
• One (1) Electives: any graduate level course 600 and above in the School of Computer Science (12 units)

Area of Concentration

• During the first two semesters in the program, all students take a set of five (5) required core courses: 11-637 Fundamentals of Computational Data Science, 15-619 Cloud Computing, 10-601 Machine Learning, 05-839 Interactive Data Science, and 11-631 Data Science Seminar.
• By the end of the first semester, all students must select at least one area of concentration — Systems, Analytics, or Human-Centered Data Science — which governs the courses taken after the first semester.
• To maximize your chances of success in the program, you should consider which concentration area(s) you are best prepared for, based on your educational background, work experience, and  areas of interest as described in your Statement of Purpose.
• You are strongly encouraged to review the detailed curriculum requirements for each concentration area, in order to determine the best fit given your preparation and background.

For a complete overview of the MCDS requirements read the  MCDS Handbook .

To earn an MCDS degree, students must pass courses in the core curriculum, the MCDS seminar, a concentration area, and electives. Students must also complete a capstone project in which they work on a research project at CMU or on an industry-sponsored project.

In total, students must complete 144 eligible units of study, including eight 12-unit courses, two 12-unit seminar courses, and one 24-unit capstone course. Students must choose at minimum five core courses. The remainder of the 12-unit courses with course numbers 600 or greater can be electives chosen from the SCS course catalog. Any additional non-prerequisite units taken beyond the 144 units are also considered electives.

Students who plan to select the Systems concentration may wish to enroll in 15-513 “Introduction to Computing Systems” during the summer session preceding their enrollment in the program; this course is a prerequisite for many advanced Systems courses, so it should be completed during Summer if you wish to enroll in advanced Systems courses in the Fall.

Click here   to see the MCDS Course Map.

Some example courses of study are included below.

Example 1: Analytics Major, 16 Months

Example 2: Systems Major, 16 Months

Example 3: Human-Centered Data Science Major, 16 Months

Carnegie Mellon's School of Computer Science has a centralized  online application process . Applications and all supporting documentation for fall admission to any of the LTI's graduate programs must be received by the application deadline. Incomplete applications will not be considered.  The application period for Fall 2024 is now closed. Information about the Fall 2025 admissions cycle will be available in summer 2024.

Application Deadlines

Fee Waivers

Fee waivers may be available in cases of financial hardship, or for participants in select "pipeline" programs. For more information, please refer to the  School of Computer Science Fee Waiver page .

The School of Computer Science requires the following for all applications:

• A GPA of 3.0 or higher.
• GRE scores: These must be less than five years old. Our Institution Code is 2074; Department Code is 0402. (This requirement is waived for CMU undergrads.)
• The GRE At Home test is accepted but we prefer you take the GRE at a test center if possible.
• Unofficial transcripts from each university you have attended, regardless of whether you received your degree there.
• Current resume.
• Statement of Purpose.
• Three letters of recommendation
• A short (1-3 minutes) video of yourself. Tell us about you and why you are interested in the MCDS program. This is not a required part of the application process, but it is STRONGLY suggested.  
• Proof of English Language Proficiency

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.

Applicants applying to MCDS are required to submit scores from an English proficiency exam taken within the last two years. Scores taken before Sept. 1, 2021, will not be accepted regardless of whether you have previously studied in the U.S. For more information about their English proficiency score policies, visit the  MCDS  admission website.  Successful applicants will have a minimum TOEFL score of 100, IELTS score of 7.5, or DuoLingo score of 120. Our Institution Code is 4256; the Department Code is 78. Additional details about English proficiency requirements are provided on the  FAQ  page. 

Applications which do not meet  all  of these requirements by the application deadline (see above) will not be reviewed.

For more details on these requirements, please see the  SCS Master's Admissions page.

In addition to the SCS guidelines, the LTI requires:

• Any outside funding you are receiving must be accompanied by an official award letter.

No incomplete applications will be eligible for consideration.

For specific application/admissions questions, please contact  Jennifer Lucas  or Caitlin Korpus .

Program Contact

For more information about the MCDS program, contact Jennifer Lucas or Caitlin Korpus

Jennifer Lucas

Caitlin korpus, online graduate certificate program, program handbook.

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Graduate Diploma in Computer Science

Change is the only constant in the world of computing. If you're a computing professional looking to upgrade, update or deepen your knowledge of rapidly evolving technologies – this program is for you.

The Graduate Diploma of Computer Science is designed for applicants with a bachelor's degree in computer science or information technology (or a related field). There are other ways to meet admission requirements – see Entry Requirements.

You can focus on one or several areas of interest when choosing from the range of computer science courses, including an advanced research project at masters level.

You will be taught by a mix of internationally renowned lecturers, industry professionals and leading researchers. Our learning spaces are some of the most innovative in the world, allowing students to share ideas, help each other and socialise.

Join a growing industry

• Demand for technology workers will grow by 100,000 between 2018 and 2024 (ACS Australia’s Digital Pulse 2019, Deloitte)
• Computer science research jobs will grow 19% by 2026 (Bureau of Labor Statistics)

Program highlights

• Complete your choice of courses that cover topics from advanced computer science, software engineering, information systems, communication systems, interaction design, research and more. In total, there are nearly 50 courses to choose from.
• Undertake a research project that addresses a specific topic or problem from the broad fields of electrical, computer systems or software engineering.
• Benefit from a program that offers a flexible study plan. Tailor your studies to suit your interests, your industry, or your career goals.

1 in Queensland for computer science and information systems

QS World University Rankings 2024

1 in Queensland for mathematics

How you'll learn

Your learning experiences are designed to best suit the learning outcomes of the courses you choose.

• Research experience
• Laboratory work

What you'll study

At UQ, degrees are called 'programs' and subjects are called 'courses'. Here's a sample of the courses you could study in this program:

• Algorithms and Data Structures
• Artificial Intelligence
• Advanced Topics in Security
• Machine Learning

See courses and program structure

Career possibilities

Postgraduate study can take you anywhere. Here are some of the careers you could be on your way to:

• Business analyst
• Data scientist
• Digital analyst
• Market analyst
• Big data architect
• Data migration specialist
• Social media data strategist
• Information architect
• Cloud architect
• IT support officer

Graduate salary

Computing & information systems (postgraduate)

compared.edu.au

Next steps after graduation

The Graduate Diploma in Computer Science equips students with advanced-level knowledge and skills in relevant areas, such as information systems, software engineering, distributed systems, networks, research and security.

Graduates work across a variety of fields and professions.

Some graduates choose to study higher degrees and go on to research positions at universities or other major research organisations. Other graduates work in industry – as analysts, engineers, administrators, developers, project managers and in specialist roles – with an increasing number of graduates employed in banking, finance and insurance.

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Entry requirements

To be eligible for entry, you'll need:

• a bachelor's degree (or equivalent) in computer science or software engineering, or
• a bachelor's degree (or equivalent) which includes all of the relevant discipline content (see below), or
• to have completed post-secondary studies and 2 years full-time equivalent relevant work experience (see below). Applications based on post-secondary study and/or work experience will be individually assessed.

Relevant disciplines for previous qualifications

If your bachelor's degree was not awarded in computer science or software engineering, you must have successfully completed all of the following discipline content in your tertiary studies:

• data structures and algorithms
• at least 2 programming courses
• discrete mathematics or algebra
• at least 3 from the following:
• computer organisation or computer architecture or computer systems
• computer networks or communication networks
• operating systems
• databases or information systems
• probability and statistics

Relevant work experience

Relevant work experience includes professional experience in software development or engineering, cyber security analysis or architecture, data engineering or science, machine learning, computer networks or statistical analysis that involves programming experience and work experience in at least two of the following areas:

• probability and statistics 

This will need to be supported with evidence. 

Evidence of relevant work experience should include a letter from your employer (and/or previous employers) clearly stating the following:

• That you work (or worked) within the specified organisation
• The nature of your work, detailing any relevant duties and responsibilities to the entry criteria above
• The length of time you were in your role/s (i.e demonstrating minimum length for entry) and whether this was full-time, part-time, or casual
• Any further bespoke conditions listed by the entry criteria

Letters will typically be expected to be presented on company letterhead and signed by a manager or HR representative. A CV or resume is not a sufficient document on its own, and must be accompanied by a supporting letter as described above.

All applications based on work experience are subject to an individual assessment.

Entry into a program through work experience does not necessarily provide a pathway into further study in a Masters.

GPA equivalent

Select where you studied and your qualification to see the GPA equivalent you need to be considered for this program.

Use the GPA equivalent as a guide. When you apply, we’ll calculate your GPA using the UQ grading scale. Any failing grades will be included. Entry requirements are subject to change.

Equivalent subjects

Related programs.

Depending on your previous qualifications and current goals, you might want to consider one of these related programs:

• Master of Computer Science
• Master of Computer Science (Management)
• Graduate Certificate in Computer Science

English language requirements

IELTS overall 6.5; reading 6; writing 6; speaking 6; listening 6. For other English Language Proficiency Tests and Scores approved for UQ

TOEFL iBT (including Paper Edition) - Overall 87, listening 19, reading 19, writing 21 and speaking 19.

PTE Academic - Overall Score of 64 and 60 in all sub bands.

BE - A minimum overall grade of 4 plus a minimum grade of C in all macro skills.

CES - Overall 176 and 169 in all sub bands.

OET is not accepted.

There are other ways to meet the English language requirements. For some programs, additional conditions apply.

Learn how to meet the English language requirements

Student visas

International students who are accepted into full-time study in the Graduate Diploma in Computer Science are eligible to apply for an Australian student visa (subclass 500).

There are a number of requirements you must satisfy before a visa is granted, including the Genuine Student (GS) requirement.

Learn more about student visas

Fees and Scholarships

Indicative annual fee.

Approximate yearly cost of tuition (16 units). Your fees will vary according to your selected courses and study load. Fees are reviewed each year and may increase.

Fee information for 2025 is not yet available. Fee information displayed is for 2024.

Learn more about postgraduate fees

Approximate yearly cost of full-time tuition (16 units). Your fees will vary according to your study load. Fees are reviewed each year and may increase.

AUD $53,760

Government assistance, financial aid.

As an international student, you might be eligible for financial aid – either from your home country, or from the Australian Government.

Learn more about financial aid

Domestic places in the Graduate Diploma in Computer Science are Commonwealth Supported. This means the cost of your education is shared between you and the Australian Government.

Instead of tuition fees, Commonwealth Supported students pay what are called student contribution amounts.

HECS-HELP is an Australian Government loan scheme to assist eligible students with the cost of their student contribution amounts.

Learn more about HECS-HELP

Centrelink support

The Australian Government offers a number of income-support payments to eligible Australian university students.

Learn about Centrelink payments for students

Scholarships

You may be eligible for more than 100 scholarships, including:

Applying online

All international applications should be submitted to UQ. If you prefer, you can use an  approved UQ agent in your country .

The program code for the Graduate Diploma in Computer Science is  5520 .

Find out more about applying for postgraduate coursework study

All domestic applications should be submitted to UQ.

The program code for the Graduate Diploma in Computer Science is 5520 .

Important dates

The closing date for this program is:

• To commence study in semester 2 - May 31 of the year of commencement.
• To commence study in semester 1 - November 30 of the previous year.

To learn more about UQ dates, including semester start dates, view the Academic Calendar .

• To commence study in Semester 1 - January 31 of the year of commencement.
• To commence study in Semester 2 - June 30 of the year of commencement.

Aboriginal and Torres Strait Islander applicants

For support with applying – or if you have any questions about university life – get in touch with our Aboriginal and Torres Strait Islander Studies Unit.

Contact the ATSIS Unit

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