If you want to become a leader in today’s growing field of information security and cybersecurity, look no further than American University’s master’s degree in Mathematics of Information and Security. The degree combines applied mathematics, data science, and information technology, with courses designed to bridge the gap between theory and practice.
Read on for the top five reasons students are pursuing an MS in Mathematics of Information and Security degree at American University:
A Hot Job Market
Worldwide spending on information security products and services is projected to exceed $100 billion by 2020. Employers are having trouble finding qualified mathematicians with the skills they need. Information security jobs are projected to grow 32 percent from 2018 to 2028, much faster than the average for all occupations.
Prepares You for a Wide Range of Careers
The program prepares students for a wide range of in-demand jobs, including computer and information research scientist, data scientist, data analyst, computer systems analyst, information security analysts, operation research analyst, and more.
You’ll Build Skills and Learn How to Apply Them
Our program starts with solid theory and cutting-edge research. Then we teach students how to apply these skills to actual data problems. Our graduates can cross between theory and practice—the entire program is designed with this principle in mind.
A Deep Math Background Opens Doors
Our degree gives students a broad and deep mathematical background that isn’t typically provided by cybersecurity programs. Thus, the degree is designed for national security or defense industry professionals, especially those who want to work in research and development or other areas that require substantial algorithmic, cryptographic, data analytics, information security, computing, and/or computational skills. It’s also designed to build leaders in the cybersecurity and information security fields.
Learn From Exceptional Faculty
Our program features the research work of very established researchers, each lending their expertise to create a relevant course of study for today’s rapidly changing world. They include Michael Robinson (Computational Topology, Signal Processing, and Computational Science), Stephen Casey (Harmonic and Complex Analysis, Computational Science, and Information Theory), Michael Baron (Sequential Analysis, Change-Point Detection, and Bayesian Inference), Elizabeth Malloy (Functional Data Analysis), John Nolan (Probability, Stable Distributions, and Extreme Event Analysis) and Joshua Lansky (Representation Theory, Number Theory, and Cryptography).