Applied mathematics and statistics

The Bachelor of Science in Applied Mathematics and Statistics at Johns Hopkins University offers students a rigorous and comprehensive education designed to prepare them for a wide range of careers in industry, government, and academia. This program combines advanced coursework in mathematical theory, computational methods, and statistical analysis to equip students with the analytical skills necessary to solve complex real-world problems. Throughout the program, students gain a solid foundation in core mathematical disciplines such as calculus, linear algebra, differential equations, and numerical analysis, alongside specialized studies in statistical inference, data analysis, and probabilistic modeling. The curriculum emphasizes practical applications, encouraging students to develop proficiency in programming languages like R, Python, and MATLAB, which are essential tools in data-driven fields. Students are also exposed to data science, machine learning, and optimization techniques, enabling them to analyze large datasets and generate actionable insights. Designed with a balance between theory and practice, the program provides opportunities for experiential learning through research projects, internships, and collaboration with industry partners. Students are encouraged to participate in research initiatives within the university's renowned departments, working alongside faculty members on cutting-edge projects that address real-world challenges. The program is suitable for those interested in pursuing careers as data analysts, statisticians, operations researchers, or advanced studies in applied mathematics or statistics at the graduate level. Graduates emerge with the quantitative expertise, programming skills, and critical thinking abilities necessary to thrive in a data-driven world. Johns Hopkins University's emphasis on interdisciplinary learning ensures that students are prepared to apply mathematical and statistical techniques across diverse sectors, including healthcare, finance, technology, and public policy. Additionally, students benefit from the university's strong connections with industry and government agencies, providing valuable networking and employment opportunities upon graduation. With a dedicated faculty committed to research and mentoring, students receive personalized academic guidance to help them achieve their professional goals. The Applied Mathematics and Statistics program at Johns Hopkins University is designed to foster analytical thinking, innovative problem-solving, and lifelong learning, preparing students to make meaningful contributions in their chosen fields.

Students may work toward either the master of arts (M.A.) degree or the master of science in engineering (M.S.E.) degree in applied mathematics and statistics. All master’s degrees in applied mathematics and statistics ordinarily require a minimum of two semesters of registration as a full-time resident graduate student.

To obtain departmental certification for the master’s degree in Applied Mathematics and Statistics, the student must:

1. Complete satisfactorily at least eight one-semester courses of graduate work in a coherent program approved by the faculty advisor. All 600-level and 700-level courses (with the exception of seminar and research courses), and some 400-level courses in the department are satisfactory for this requirement.  Certain courses in other departments are also acceptable.  At most 3 courses outside the department may be counted toward the Master's degree requirements.
2. Meet either of the following options:
   • (a) submit an acceptable research report based on an approved project; or
   • (b) complete satisfactorily two additional one-semester graduate courses, as approved by the faculty advisor.
3. Satisfy the computing requirement by receiving a grade of B- or better in one of the following courses:

   EN.550.400	Mathematical Modeling and Consulting	4.00
   EN.550.413	Applied Statistics and Data Analysis	4.00
   EN.550.415	Practical Scientific Analysis of Big Data	3.00
   EN.550.433	Monte Carlo Methods	3.00
   EN.550.436	Data Mining	4.00
   EN.550.443	Financial Computing in C++	4.00
   EN.550.450	Computational Molecular Medicine	4.00
   EN.550.487	Numerical Methods for Financial Mathematics	3.00
   EN.550.493	Mathematical Image Analysis	3.00
   EN.550.632	Bayesian Statistics	3.00
   EN.550.643	Graphical Models	4.00
   EN.550.653	Commodities and Commodity Markets	3.00
   EN.550.661	Foundations of Optimization	3.00
   EN.550.662	Optimization Algorithms	3.00
   EN.550.680	Shape and Differential Geometry	3.00
   EN.550.681	Numerical Analysis	4.00
   EN.600.475	Machine Learning	3.00

4. Complete an area of focus by taking three courses in one of the following areas. A list of courses that can be counted toward each area of focus will be maintained and updated every year.  Some courses from other departments can be eligible to count toward area of focus.  They can be used within the three-course limit specified in point 1, above. This list of courses is based on recent offerings. Not all classes are available every year and substitute classes may be accepted if approved by the advisor and the Academic Affairs Committee.  Higher level classes (700 or 800) can be accepted if given a letter grade.

   Probability Theory
   EN.550.426	Introduction to Stochastic Processes
   or EN.550.427	Stochastic Processes and Applications to Finance
   EN.550.428	Stochastic Processes and Applications to Finance II
   EN.550.433	Monte Carlo Methods
   EN.550.620	Probability Theory I
   EN.550.621	Probability Theory II
   EN.550.622	Introduction to Stochastic Calculus
   EN.550.663	Stochastic Search & Optimization
   EN.550.664	Modeling, Simulation, and Monte Carlo
   Statistics and Statistical Learning
   EN.550.413	Applied Statistics and Data Analysis
   EN.550.415	Practical Scientific Analysis of Big Data
   EN.550.434	Nonparametric Statistics
   EN.550.436	Data Mining
   EN.550.439	Time Series Analysis
   EN.550.450	Computational Molecular Medicine
   EN.550.630	Statistical Theory
   EN.550.631	Statistical Theory II
   EN.550.632	Bayesian Statistics
   EN.550.633	Advanced Topics in Bayesian Statistics
   Optimization and Operations Research
   EN.550.461	Optimization in Finance
   EN.550.453	Mathematical Game Theory
   EN.550.463	Network Models in Operations Research
   EN.550.661	Foundations of Optimization
   EN.550.662	Optimization Algorithms
   EN.550.663	Stochastic Search & Optimization
   EN.550.665	Convex Optimization
   EN.550.666	Combinatorial Optimization
   Computational and Applied Mathematics
   EN.550.443	Financial Computing in C++
   EN.550.492	Mathematical Biology
   EN.550.493	Mathematical Image Analysis
   EN.550.680	Shape and Differential Geometry
   EN.550.681	Numerical Analysis
   EN.550.692	Matrix Analysis and Linear Algebra
   EN.550.695	Advanced Parameterization in Science and Engineering
   Discrete Mathematics *
   EN.550.471	Combinatorial Analysis
   EN.550.472	Graph Theory
   EN.550.666	Combinatorial Optimization
   EN.550.671	Combinatorial Analysis
   EN.550.672	Graph Theory
   EN.600.463	Algorithms I
   EN.600.464	Randomized and Big Data Algorithms
   EN.600.469	Approximation Algorithms
   EN.600.470	Combinatorics & Graph Theory in Computer Science
   EN.600.471	Theory of Computation

   *

   The Discrete Mathematics area of focus requires a minimum of one listed course taken within the Applied Mathematics and Statistics department, but the other two courses may include the listed Computer Science offerings.  These courses can be used within the three-course limit specified in point 1, above.

5. Complete training on the responsible and ethical conduct of research, if applicable.  Please see WSE Policy on the Responsible Conduct of Research.
6. Complete training on academic ethics.

An overall GPA 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 and the rest of the course grades must be B- or better.

Each candidate for the master’s 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 master’s program in Applied Mathematics and Statistics with the permission of the AMS department and an application review. Application forms and information are available in the department office.

• Letters of Recommendation (3),
• GRE,
• TOEFL/IELTS,
• Statement of Purpose addressing your interest in graduate study in applied mathematics at JHU or another topic of your choice,
• Transcripts,
• GRE Subject (optional)

The Applied Mathematics and Statistics program at Johns Hopkins University offers diverse financing options to support students throughout their studies. Financial aid opportunities include scholarships, graduate fellowships, teaching assistantships, research assistantships, and external funding sources. Scholarships are awarded based on academic merit, achievements, and potential contributions to the university community, providing partial to full tuition coverage. Graduate fellowships are available for qualified students, offering stipends and tuition assistance, often in exchange for research or teaching responsibilities. Teaching assistantships (TAs) and research assistantships (RAs) provide valuable financial support while granting practical experience in instructional and research activities; these positions typically include a stipend and tuition remission. The university also encourages students to seek external scholarships, grants, and fellowships from governmental agencies, private foundations, and industry partners, which can substantially offset educational costs. Johns Hopkins University maintains a comprehensive financial aid office dedicated to assisting students in identifying and applying for various funding sources tailored to graduate studies in applied mathematics and statistics. Prospective and current students are advised to review the specific eligibility criteria, application deadlines, and award durations for each financial aid option. Tuition fees and estimated living expenses are regularly updated on the university's official website, ensuring transparency and planning accuracy. Financial aid packages may sometimes be supplemented by departmental funding or fellowships specific to the program. Additionally, students are encouraged to explore loan options through federal or private lenders if necessary. The university’s commitment to affordability and access emphasizes providing a supportive financial environment so students can focus on their academic and research pursuits without undue financial stress. Overall, the Johns Hopkins University applies a multifaceted approach to student financing, aiming to create equitable opportunities and foster academic excellence in applied mathematics and statistics.

The Applied Mathematics and Statistics program at Johns Hopkins University is designed to provide students with a comprehensive education in the theoretical foundations and practical applications of mathematics and statistics. The program emphasizes developing skills in mathematical modeling, statistical analysis, computational techniques, and data interpretation, preparing graduates for careers in industries such as finance, technology, healthcare, government, and research. Students have the opportunity to engage in a rigorous curriculum that combines coursework in calculus, linear algebra, differential equations, probability theory, statistical inference, and data science. The program often includes options for specialization, allowing students to focus on areas like computational mathematics, applied statistics, or data analytics. Johns Hopkins University is renowned for its strong emphasis on research and real-world problem solving, and students can benefit from access to state-of-the-art laboratories, collaborations with industry partners, and internships that provide practical experience. Faculty members in the department are leading experts in their fields, contributing to advancements in statistical methods, mathematical modeling, and data analysis techniques. The program also encourages interdisciplinary approaches, enabling students to work on projects that intersect with fields like public health, engineering, economics, and environmental science. Graduates of the Applied Mathematics and Statistics program are well-equipped to pursue advanced degrees or enter the workforce as data scientists, quantitative analysts, statisticians, or mathematical consultants. The university's commitment to diversity, innovation, and excellence ensures that students receive a holistic education that prepares them for successful careers and lifelong learning in a rapidly evolving data-driven world. The program’s curriculum is regularly updated to incorporate emerging technologies and methodologies, ensuring students are prepared for the challenges of modern data analysis and mathematical applications.