Exploring the Prerequisites for the Master’s in Machine Learning: Applied Study at CMU

When contemplating advancing your education with a Master’s in Machine Learning: Applied Study at Carnegie Mellon University (CMU), it’s essential to understand the various prerequisites and admissions criteria. This comprehensive guide offers a detailed look into what you need to pave your way into this exciting field.

Do I Need an Undergraduate Degree in Computer Science?

One of the standout features of the CMU program is its inclusivity regarding academic backgrounds. While many candidates come from computer science, an undergraduate degree in this field is not a strict requirement. Instead, the program welcomes applicants from diverse educational paths who demonstrate a strong foundation in computer science principles—making it accessible to a broader range of aspiring students.

The Importance of a Strong Computer Science Background

Even though a specific degree is not mandated, incoming students must possess a robust background in essential areas of computer science. The curriculum anticipates that students have:

• A solid grasp of complexity theory
• Good programming skills: Familiarity with languages like Java and Python is particularly emphasized, with experience in Matlab, R, or Scipy-Numpy viewed favorably.
• Mathematics proficiency: First-year courses assume familiarity with college-level probability and statistics, as well as matrix algebra and multivariate calculus.

To gauge your readiness, the program offers a helpful self-assessment test for its introductory machine learning course.

Required Test Scores for Admission

Standardized test scores provide another layer of insight into applicants’ readiness for a graduate-level program. For the upcoming fall 2025 cohort, the average test scores for accepted applicants in the Master’s in Machine Learning: Applied Study were noteworthy:

• Overall Undergraduate GPA: 3.9/4.0 or 9.5/10.0
• GRE Quantitative: 169 (88th percentile)
• GRE Verbal: 160 (80th percentile)
• GRE Analytical Writing: 4.1 (63rd percentile)
• TOEFL: 111

It’s critical to note that these scores vary widely among applicants and are just one part of the application package. CMU evaluates candidates holistically, considering experiences, skills, and background.

Are GRE Scores Required?

If you’re worried about the GRE, you should know that for applications to the M.S. in Machine Learning – Applied Study program in Fall 2025, GRE scores are optional. Applicants are not required or expected to take a GRE Subject Test, removing an additional hurdle for many aspiring students.

Flexibility in Study Format: Full-Time vs. Part-Time

Online Degrees

Currently, CMU does not offer online or distance-learning options for this program. If you’re looking to get the most out of your experience, being physically present in Pittsburgh and attending classes on campus is a must.

Part-Time Study

If you have commitments that prevent full-time study, you can pursue the program on a part-time basis. However, it’s essential to attend classes, which typically occur during weekdays. Be mindful that international students must comply with visa regulations that generally require full-time enrollment, completing the program within three semesters.

Application Timing and Transfer Policies

Spring Entry

It’s important to note that applications are only accepted once a year, typically in December, and students must begin the program in the subsequent August. Because of the structure of core courses, there are no possibilities for entry in the spring.

Transfer Policies

If you’re currently enrolled in another program at CMU or another university, transferring into the Master’s in Machine Learning: Applied Study is not straightforward. You must apply as a new candidate, adhering to the same application standards as all applicants. In certain situations, course waivers may be granted, but transfer credits from other institutions will not be accepted.

For Applicants with Previous Degrees

If you already hold a master’s degree, you are still welcome to apply. The admissions team values diverse experiences and perspectives. Your statement of purpose should clearly articulate how an additional master’s degree aligns with your personal and professional goals.

Understanding Program Structure

The Master’s in Machine Learning: Applied Study is distinct yet similar to CMU’s other graduate programs in machine learning. The applied study track is perfect for students who aspire to work in industry settings, focusing more on practical development, internships, and real-world applications compared to traditional academic research seen in other programs.

Is the Master’s in Machine Learning a STEM Program?

Yes, the Master’s in Machine Learning program at CMU is categorized as a STEM program. This distinction is vital for international students since it can influence employment opportunities after graduation.

Career Outcomes for Graduates

While the Master’s in Machine Learning: Applied Study began only in 2020, CMU’s Career and Professional Development Center compiles post-graduation statistics that provide valuable insights into the career trajectories of graduates. You can find this information here.

More Information

Curious to learn more about specific application dates or program details? You can find all the necessary information and updates on the SCS Master’s Admissions page.

With such a unique approach to admissions and a commitment to fostering diverse skilled professionals, CMU’s Master’s in Machine Learning: Applied Study program stands out. Whether you’re from a CS background or another field entirely, there are clear pathways to achieving your dreams in this dynamic sector.