The University of Maryland offers a Master of Science in Applied Machine Learning through its Science Academy in the College of Computer, Mathematical, and Natural Sciences.
The 30-credit, non-thesis program focuses specifically on the technical side of machine learning. Students study probability, statistics, data science, optimization, computing systems, algorithms, and machine learning before choosing advanced electives.
Classes meet in person at the College Park campus, primarily in the evenings. The schedule makes the program a strong option for working professionals in the Washington, D.C.–Maryland area who want a technical machine learning degree without leaving the workforce.
Quick Facts
| Degree | M.S. in Applied Machine Learning |
| Location | College Park, Maryland |
| Format | Campus |
| Credits | 30 |
| Courses | 10 |
| Program Type | Non-thesis, professional |
| Time to Complete | Less than 2 years |
| 2026–27 Tuition | Approximately $44,840 before fees |
| Minimum GPA | 3.0 |
| GRE | Optional |
| Schedule | Primarily evening classes |
Program Overview
UMD’s M.S. in Applied Machine Learning is a professional graduate program built around the development and application of machine learning models.
The program requires 10 courses totaling 30 credits. Six courses form the required technical core, while students select four electives based on their interests.
Unlike a research-oriented master’s program, the degree does not include a thesis or research requirement. UMD specifically describes the program as focused on practical knowledge rather than research.
Students can apply what they learn to fields such as finance, healthcare, telecommunications, engineering, security, biology, and information technology.
Visit the University of Maryland M.S. in Applied Machine Learning program page.
Curriculum
Students complete six required courses:
- MSML 601 – Probability and Statistics
- MSML 602 – Principles of Data Science
- MSML 603 – Principles of Machine Learning
- MSML 604 – Introduction to Optimization
- MSML 605 – Computing Systems for Machine Learning
- MSML 606 – Algorithms and Data Structures for Machine Learning
Together, these courses provide a strong base in mathematics, statistics, programming, algorithms, computing systems, and machine learning.
Students then complete four electives.
Available electives include:
- Deep Learning
- Computer Vision
- Natural Language Processing
- Robotics
- Cloud Computing
- Big Data Analytics
UMD also lists Digital Signal Processing among its Applied Machine Learning course offerings.
The elective options are one of the program’s strongest features. Students can move beyond general machine learning into areas such as deep learning, language models, computer vision, robotics, and large-scale data processing.
More about the curriculum on the course catalog page.
Full-Time and Part-Time Options
UMD provides sample plans for both full-time and part-time students.
The part-time plan generally has students take two courses per semester across five semesters, including summer study.
The full-time plan starts with three courses in the first fall and spring semesters and can be completed in four semesters, including summer.
UMD states that the degree can be completed in less than two years.
Most classes meet in the evening at the College Park campus. This structure makes the program particularly useful for students who work full time in the Washington, D.C. region.
Admissions Requirements
Applicants must hold a four-year bachelor’s degree from an accredited U.S. institution or an equivalent international degree.
UMD requires a minimum 3.0 GPA in prior undergraduate and graduate coursework.
Applicants should also have a strong quantitative and programming background. UMD specifically looks for prior coursework that demonstrates preparation in areas such as:
- Calculus II
- Linear algebra
- Statistics
- Programming
Python, MATLAB, and R are among the programming languages identified by the program. Applicants can demonstrate programming ability through previous coursework or substantial software development experience.
The application also requires materials including:
- Statement of purpose
- Transcripts
- CV or resume
- Description of research or work experience
- English proficiency scores when required for international applicants
The GRE is optional.
Students without a solid mathematics and programming background may find this program difficult. This is a technical machine learning degree rather than an introductory AI or business analytics program.
Tuition and Fees
For the 2026–27 academic year, University of Maryland lists tuition for its Science Academy master’s programs at $4,484 per course.
With 10 courses required, estimated base tuition for the M.S. in Applied Machine Learning is:
$4,484 × 10 courses = $44,840
The Science Academy uses a flat tuition rate for its designated program sections, so Maryland residents and non-residents pay the same program tuition rate.
Mandatory university fees are additional and depend on the number of credits taken and the semester.
Students should therefore budget more than the $44,840 base tuition figure for the complete degree.
[View current UMD Science Academy tuition and fees.]
What Makes the UMD Program Different?
Strong Technical Core
This is a machine learning degree rather than a broad data science program with a few ML courses. Required coursework includes machine learning, optimization, algorithms, computing systems, statistics, and data science.
Advanced ML Electives
Students can use four electives to study areas such as deep learning, natural language processing, computer vision, robotics, cloud computing, and big data analytics.
Built for Working Professionals
Most classes take place in the evening. UMD’s Science Academy specifically structures its professional master’s programs so students can continue working while earning their degrees.
No Thesis Requirement
The program is entirely coursework based. Students who want industry-focused technical training can complete the degree without writing a thesis.
College Park Location
The campus location provides access to the broader Washington, D.C.–Maryland technology market. The format is especially practical for professionals who already live or work in the region.
Is the University of Maryland M.S. in Applied Machine Learning Worth It?
UMD is a particularly strong choice for students who want a technical, applied machine learning master’s degree and can attend classes in College Park.
The curriculum goes deeper into machine learning than many general data science degrees. Required courses in optimization, algorithms, computing systems, and machine learning are paired with advanced electives such as deep learning, NLP, computer vision, and robotics.
The program should be especially attractive to:
- Working professionals in Maryland and the Washington, D.C. area
- Students interested in machine learning engineering
- Applicants with existing mathematics and programming skills
- Students who prefer applied coursework over academic research
- Students who want to study advanced ML areas without completing a thesis
The main limitation is delivery format. This is a face-to-face program, so students looking for a fully online machine learning master’s should consider other schools.
The roughly $44,840 base tuition also puts UMD above some lower-cost online programs. Students are paying in part for a specialized ML curriculum, in-person instruction, and access to UMD’s faculty and College Park location.
See the official tuition page for more info.
Who Is This Program Best For?
Best for: Working professionals who want advanced, technical machine learning training and can attend evening classes in College Park.
Consider another program if: You need a fully online degree, want a research-based master’s with a thesis, or do not yet have a solid background in mathematics and programming.
Related Machine Learning Programs
Students comparing UMD with other programs can also explore: