Applied Mathematics and Statistics, Master of Science in Engineering
Program Overview
Overview of the Master of Science in Engineering in Applied Mathematics and Statistics
The Master of Science in Engineering (M.S.E.) in Applied Mathematics and Statistics is a graduate program offered by the Whiting School of Engineering at Johns Hopkins University. This program requires a minimum of two semesters of registration as a full-time resident graduate student.
Program Requirements
To obtain departmental certification for the masters degree in Applied Mathematics and Statistics, students must:
- Complete satisfactorily at least eight one-semester courses of graduate work in a coherent program approved by the Department Head.
- Most 3- or 4-credit AMS Department 600-level and 700-level courses are acceptable.
- Certain courses in other departments are also acceptable, but must be fully approved in advance.
- At most 3 courses outside the department may be counted toward the 8 (or 10) courses used toward Master's degree requirements.
- Non-JHU (transfer) courses may not be used toward degree requirements.
- JHU courses listed as 2-credit courses (with the exception of research/internship courses) may count only as one-half course.
- JHU Public Health courses may count only as one-half course.
- JHU 1-credit courses may not be used.
- Meet either of the following options:
- Submit an acceptable research report based on an approved project.
- Complete satisfactorily two additional one-semester graduate courses (with the same restrictions listed in section 1) and as approved by the faculty advisor and Department Head.
- Satisfy the computing requirement by receiving a grade of B- or better in one of the following courses:
- AS.110.445: Mathematical and Computational Foundations of Data Science
- EN.553.600: Mathematical Modeling and Consulting
- EN.553.613: Applied Statistics & Data Analysis I
- EN.553.632: Bayesian Statistics
- EN.553.633: Monte Carlo Methods
- EN.553.634: Elements of Statistical Learning
- EN.553.635: Bayesian Statistics for the Physical Sciences
- EN.553.636: Introduction to Data Science
- EN.553.650: Computational Molecular Medicine
- EN.553.669: Large-Scale Optimization For Data Science
- EN.553.681: Numerical Analysis
- EN.553.683: Numerical Methods for Partial Differential Equations
- EN.553.688: Computing for Applied Mathematics
- EN.553.689: Software Engineering for Data Science
- EN.553.693: Mathematical Image Analysis
- EN.601.675: Machine Learning
- EN.601.682: Machine Learning: Deep Learning
- Complete an area of focus by taking three courses in one of the following areas:
- Probability Theory
- Statistics and Statistical Learning
- Optimization and Operations Research
- Computational and Applied Mathematics
- Discrete Mathematics
- Complete training on the responsible and ethical conduct of research.
- Receive a Passing grade in the mandatory Graduate Academic Ethics course, EN.500.603 (01).
- Students may also be required to complete an English language course.
- Students in the AMS MSE program are strongly encouraged to register in EN.553.801 Department Seminar in at least one semester of their program.
Minimum Academic Performance Expectations
- An overall unofficial GPA (calculated by the department) of 3.0 must be maintained in courses used to meet the program requirements.
- At most two course grades of C or C+ are allowed to be used towards degree requirements, and the rest of the course grades must be B- or better.
Additional Information
Each candidate for the masters degree must submit to the department for approval a written program stating how they plan to meet their degree requirements. This should be done early in the first semester of residence. Doctoral students in other departments may concurrently undertake a masters program in Applied Mathematics and Statistics with the permission of the AMS department through an application review. Application information is available on the department website.