What are the admissions criteria for this program? What are the minimum TOEFL, IELTS, GRE, and GPA scores for your program? How competitive is the selection process?
The MCDS program is highly competitive, with a typical acceptance rate of less than ten percent. Qualified applicants generally have a bachelor’s degree in computer science or a related field. Regardless of your undergraduate major, a strong background in computer science and mathematics is a prerequisite for acceptance.
English language competency is strongly correlated to success in the program. The MCDS program intends to have at least 90% of its students meet or exceed the following TOEFL scores:
103 Total Score, 25-Listening, 25-Reading, 25-Writing, 22-Speaking.
The degree program does not have a minimum GRE or GPA requirement. However, previous academic performance is the strongest predictor of success in the program.
I have an undergraduate degree in a field outside of computer science. Am I eligible to apply to the MCDS program with this degree? Will a computer science undergraduate have an advantage over me?
Most of the courses in MCDS require an undergraduate-level background in statistics or computer science. Thus, the applicant must show evidence of mastery of this material. This evidence is automatically available for students with an undergraduate degree in CS from top universities. Most students with non-CS degrees haven't taken four or more courses in computer science. But if you have, make this evidence explicitly clear in your application.
The application requires a statement of purpose. What makes a good essay?
We are looking for strong, experience-based evidence that you can do well in our degree program and that you “fit” based on our areas of focus. For example, a description of a large software or research project, your involvement in the project, and the impact of the research is good evidence. An explanation of what drew your interest to the MCDS program and how it relates to your professional goals is also useful. You may also take this opportunity to explain any apparent weaknesses in your application. Although details regarding your personal interests and background can be helpful, they are not part of our admissions criteria and should not constitute the bulk of your statement of purpose. Most importantly, your statement of purpose should be written by you and provide an accurate representation of your experiences and goals.
The application requires letters of recommendation. What makes a good letter?
The strongest letters come from respected advisors and managers who know you well and have experience directly supervising your work. They often focus on your specific accomplishments while working under them, and what specific traits, skills or achievements make you remarkable. A letter from a professor who taught you in a class is acceptable, but often does not provide great depth of detail. Letters from people who know you only in a personal capacity and cannot comment on your academic or professional work are not appropriate.
The application process asks for research publications. Are these required?
No, publications are not required, but they are perhaps the best evidence that you can do high-quality research. Some of our admitted students have publications already; many do not. Publications in lesser-known conferences are still valuable, although all publications should be easily verifiable if not directly linked in your application. If you have any doubts about what constitutes a peer-reviewed publication, ask someone with lots of publications.
The application asks for work experience. Is this required?
No, work experience is not required. However, we value some types of work experience highly, particularly if it is similar to the type of work our graduates perform, or highly relevant to your interest in the program.
I applied but I did not get in. Can you tell me why?
Unfortunately, the number of available slots in our program and the high volume of applicants dictate that many qualified applicants will not be accepted. Due to the large number of applicants, we are unable to respond individually to applicants that were not accepted. That said, previous applicants are not prohibited from re-applying in future cycles.
I applied but did not get in, and I have new evidence for you. Will you reconsider my application?
Unfortunately, no supporting documents or information can be submitted after the application deadline. If you feel that your qualifications have significantly improved in light of recent developments, you may choose to reapply in the next admissions cycle.
What is the difference between various CMU Masters degrees?
For a description of the various Masters degrees offered in the School of Computer Science, view the school’s program’s page.
Can I continue to the PhD program after I graduate from the MCDS program? I found there is no PhD in computational data science.
There is no “CDS” PhD program. However, successful completion of the MCDS program would likely strengthen your application to any PhD program in a related field, and although the MCDS degree is professionally-focused, some of our graduates do continue on to highly competitive PhD programs.
What about internships?
All students enrolled in the 16 or 20 month timelines of the program are required to complete an internship. Internships provide an opportunity for an industrial development or industrial research experience before graduation. This experience is a vital component in learning to utilize the skills you develop in the program in “real world” applications, while also providing valuable access to the company sponsoring the internship and generally improving your employment prospects.
How easy is it to get an internship?
CMU students are in high demand. Hundreds of companies (e.g., Apple, Amazon, Bank of America, Booz Allen, Ebay, Google, Intel, Microsoft, Morgan Stanley, MITRE, Motorola, Paypal, Salesforce.com, UBS, VMware, Yahoo, etc.) perform on-campus interviewing at CMU for internships, so with minimal effort a student can typically secure an internship with a Fortune 1000 company or with a highly promising start-up.
From the curriculum, I have to complete 9 courses (5 cores, 2 concentrations, the seminar, and 1 elective) and a project to earn the master's degree. Can I complete more than 9 courses by selecting more than 1 elective course?
Because of the difficulty of the curriculum, we do not recommend taking more than 4 courses in a semester, and any courses you take outside of the standard curriculum may delay your graduation and/or incur additional tuition expenses. That said, students may take as many electives as they choose.
According to the program curriculum page, this program is typically completed within 16 months. Can I expand my study to 2 years?
Yes, the degree can be completed in a longer time frame with permission of the MCDS director. You need to inform us as soon as possible about your intention to stay longer and your intended date of completion. In addition, you (or your sponsor) will have to pay additional tuition.
Can I take courses in other parts of CMU (Heinz College, Tepper School of Business, etc.)
Yes, with permission from the MCDS director. However getting into the course may be difficult, depending on demand. Each school always gives priority to its own students over students from other schools within the university.
Is there a comprehensive exam or graduation exam outside of regular coursework required for the program?
There are no comprehensive exams in the MCDS program. The student integrates their academic experience with practical application via the capstone project.
What percentage of MCDS students graduate with a degree? What is the withdrawal rate of this program?
Our selective admission process is designed to only admit students who can handle the high course load of the degree. To date, all our students have either received a degree, are on track to receive a degree, or left the program due to a job offer.
Does this degree study data mining? If not, how different is it from data mining?
The degree program deeply emphasizes three areas that are fundamental to all aspects of data mining: machine learning, information retrieval and databases. In addition, students can choose projects in data mining and take specialist courses in data mining to further pursue this particular area of study.
What support do you provide for women in computing?
Women@SCS' mission is to create, encourage, and support women's academic, social and professional opportunities in the computer sciences and to promote the breadth of the field and its diverse community. The Women @ SCS Advisory Committee consists of undergraduate students, graduate students, and faculty within the School of Computer Science.
What is the program’s Return on Investment?
To date, almost all program graduates have been highly successful in securing jobs. Graduates report that hiring salaries, though surely dependent upon location, are above $100,000/year, plus signing bonuses and additional perks. Most students receive more than one job offer.
Where can I find out more about graduate education at Carnegie Mellon University?
Visit the Carnegie Mellon University Graduate Education website.
To earn an MCDS degree, student 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.
MCDS students must also pass the undergraduate course 15-513 Introduction to Computer Systems (6 units), typically in the summer before their program commences. The student must pass with a grade of B- or better. Failure to pass the course means that the student takes 15-213 during either the fall or spring semester. Note that in both cases the units do not count toward the 144 eligible units of study.
Some example courses of study are included below.
Example 1: Analytics Major, 16 Months
Data Science Seminar
Machine Learning for Text Mining
Advanced Machine Learning
Design and Engineering of Intelligent Information SystemsBig Data Analytics
Data Science Seminar
Capstone Planning Seminar
Machine Learning with Big Data Sets
Information Systems Project
Multimedia Databases and Data MiningLarge Scale Multimedia Analysis
Data Science Analytics Capstone
Example 2: Systems Major, 16 Months
Computational Data Science Seminar
Advanced Storage Systems
Computational Data Science Seminar
Parallel Computer Architecture and Programming
Computational Data Science Systems Capstone
Operating Systems or Web Applications
Example 3: Human-Centered Data Science Major, 16 Months
Empirical Analysis of Interactive Systems
Interactive Data Science
Social Web Analytics & Design
Interactive Data Science
Educational Software Design
|Learning with Peers|
Psych Found for Design Impact
ML with Big Data
ML with Text Analysis