Equip yourself with high-demand tech skills tailored to today’s tech landscape with OU’s online Master of Science in Applied Computing. This program can be completed in as little as 12 months and provides intensive training in advanced programming concepts, computational analysis, software architecture, and cutting-edge development tools, preparing graduates to design innovative solutions that address real-world technology challenges.
This program welcomes students from all academic backgrounds —granted they have prior programming experience and have completed Calculus I.
Hands-on coursework focused on solving real-world problems using the latest tools and coding languages.
Learn from accomplished scholars pushing boundaries in applied computing research and education.
100% online format allows students to earn this degree in just 12 months while working and balancing other responsibilities.
The program’s easy online application process with no GRE/GMAT scores or letters of recommendation.
Include a 750-word purpose statement on the Dissertation project.
Students should have earned a conferred bachelor’s degree.
Calculus I is required.
No minimum years of experience is required.
Earn your M.S. in Applied Computing from the University of Oklahoma to pursue impactful roles in tech and software. Capitalize on the high demand for technology professionals with sophisticated development skills. OU’s online MSAC program prepares graduates to pursue high-level roles, driving innovation across industries and leveraging their newfound knowledge and leadership skills to foster organizational success.
Total Credit Hours: 6
Total Credit Hours: 6
This course will begin by introducing Data Security and Information Security. Discussions about Risk Management, its principles, methods, and types will be included in the course. This course will explain the different ways of securing and protecting data on both hardware and software platforms. Network Security will cover various security issues and vulnerabilities in various network layers. The course will go through aspects of system, email, and internet security. The course will also cover the security problems introduced by the combination of the Internet with Intranets, mobile devices, and sensors.
Total Credit Hours: 6
This course introduces the concepts, practices, and technologies to design, develop, and manage cross-platform websites and applications running on modern mobile devices. The students will gain plenty of experience from hands-on exercises. The course also provides a higher-level survey of technologies, principles, strategies, and frameworks for mobile device software development. The class will focus on UI design and programming as well. By the end of the course, students will be able to plan, design, and implement a functioning mobile application.
This course will introduce concepts in programming web application servers. At the conclusion of this course, you will understand the fundamental concepts of software engineering as it is applied to web application design and programming, will know the modern tools used to program web application servers, and will be able to produce substantial web applications as part of a team. This course will teach students both front‐end and back‐end techniques necessary to build web applications. Students will learn how to make websites interactive, how to structure and manage content for websites in databases, and how to create data‐driven web applications.
Total Credit Hours: 6
This course gives students an overview of the field of Cloud Computing, its enabling technologies, main building blocks, and hands-on experience through projects utilizing public cloud infrastructures. Cloud computing services are being adopted widely across a variety of organizations and in many domains. Simply, cloud computing is the delivery of computing as a service over a network, whereby distributed resources are rented, rather than owned, by an end user as a utility.
Prerequisite: Graduate Standing and ACS 5213. Machine learning is the data-driven process of constructing mathematical models that can be predictive of data observed in the future. In this course, we will study the use of a range of supervised, semi-supervised and unsupervised methods to solve both classification and regression problems.
Total Credit Hours: 6
Total Credits for the Program: 30