Program Overview

Overview of the Online Master of Computer Science Program

The online Master of Computer Science (MCS) program, offered through Arizona State University's School of Computing and Augmented Intelligence, is designed for individuals interested in expanding their knowledge of computer science and computation. This program provides an advanced understanding of topics such as artificial intelligence, cybersecurity, and big data, while strengthening skills through technical projects.

Program Details

• Total classes: 10
• Weeks per class: 7.5
• Total credit hours: 30
• Next start date: 01/12/2026

Career Opportunities

The program prepares students for in-demand, high-paying jobs in the field of computer science. According to the U.S. Bureau of Labor Statistics, employment for computer and information research scientists is expected to grow by 23% from 2022 to 2032, which is much faster than average for all occupations. Computer and information research scientists made a median annual salary of $136,620 in May 2022.

Skills Developed

Upon graduation, students will have a variety of skills, including:

• Designing and analyzing computers
• Implementing computational processes
• Improving software reliability, network security, and information retrieval systems
• Inventing next-generation computer systems, computer networking, biomedical information systems, gaming systems, and more
• Transferring and transforming information

Customized Studies

The program allows students to create a customized plan that aligns with their career goals. A majority of the courses will be electives, giving students the opportunity to explore their interests in various topics, such as artificial intelligence, blockchain, and software engineering.

Concentrations

Two available concentrations are:

• Big Data Systems: This concentration focuses on creating scalable systems to manage, interpret, and analyze large amounts of data.
• Cybersecurity: In this concentration, students gain the skills needed to safeguard information systems, develop solutions, and mitigate risk.

Professional Certification and Nondegree Enrollment Opportunities

As a nondegree graduate student, individuals can take master's-level computer science courses without being admitted to the program. This provides the opportunity to establish a high graduate GPA, try out courses, meet the English proficiency requirement, or earn a professional certification credential.

Faculty

The program is taught by award-winning faculty members in the field of computer science, with many having been honored with the highest awards in their fields.

Admission Requirements

• GPA requirements: A minimum cumulative GPA of 3.00 in the last 60 credit hours of a four-year undergraduate degree.
• Math course requirements: Two semesters of advanced math in Calculus I and Calculus II, as well as a background course in discrete math.
• Pre-requisite course requirements: Programming knowledge in a variety of languages, including C/C++, Java, Python, and HTML, as well as courses in calculus and discrete math.
• English proficiency: If all college degrees are from a country outside of the U.S., students may need to demonstrate English proficiency.

Tuition

The total cost of the degree program is $15,000, or $1,500 per 3-credit course. There are no textbooks required for the courses, and no additional fees.

Courses

Some of the courses offered in the program include:

• Bio-Inspired Computing: This course explores computational methods based on biological processes and how to apply them to solve computational problems.
• Foundations of Algorithms: This course covers several different algorithms and enables students to explain how they work and when they are considered good.
• Knowledge Representation and Reasoning: This course introduces fundamental concepts and surveys recent research and developments in the field of knowledge representation and reasoning.
• Advanced Computer and Network Security: This course focuses on applied cryptography, system security, and the principles and practices of network security.
• Applied Cryptography: This course covers the design and usage of cryptographic protocols for online and offline computing applications.
• Distributed and Multiprocessor Operating Systems: This course teaches both the fundamental concepts and principles of distributed systems and the practical skills for developing distributed systems.
• Information Assurance and Security: This course provides an overview of the historical underpinnings and the current, global landscape of information assurance and security.
• Mobile Computing: This course provides an in-depth understanding of the fundamental concepts and challenges in mobile computing, as well as existing and proposed solutions for these challenges from research and development perspectives.

Learning Outcomes

Upon completing the program, students will be able to:

• Demonstrate familiarity with applications of bio-inspired computing in engineering
• Discuss and use new biological concepts and applications
• Solve computational problems with bio-inspired algorithms
• Use biological concepts and knowledge in algorithms
• Apply knowledge of algorithms in multiple contexts using programming languages
• Evaluate the correctness and efficiencies of algorithms
• Identify and apply algorithmic techniques to solve problems
• Explain the foundations of knowledge representation and reasoning
• Assess the trade-off between representation and reasoning
• Identify which knowledge-based techniques are appropriate for which tasks
• Apply knowledge representation and reasoning systems to challenging real-world problems
• Recognize common security threats and attacking attempts
• Identify typical vulnerabilities in programs
• Develop secure programs
• Analyze legal and ethical concerns of computer security activities
• Launch attacks in ethical hacking environments
• Design a context-aware application
• Identify the advantages of using context in applications
• Explore the challenges arising due to changes in the environment in which computation is performed
• Define smartness and identify salient features that distinguish smart applications from traditional ones
• Describe key features of the Internet of Things (IoT) and design a distributed smart application using IoT
• Analyze nonfunctional requirements of smart mobile applications, such as safety, security, and sustainability
• Apply popular tools, such as machine learning, security protocols, AI, and software testing, to validate safety, security, and sustainability of smart mobile applications
• Acquire programming skills on popular mobile platforms, such as Android
• Develop, end-to-end, a sensor-enabled smart autonomous practical application

Technology Requirements

• Hardware: Microphone, personal computer with a major operating system, reliable internet connection, and webcam
• Software: Various software and tools, including Python, Java, C#, C++, Linux, and virtual machine software

Conclusion

The online Master of Computer Science program at Arizona State University provides students with a comprehensive education in computer science, preparing them for in-demand, high-paying jobs in the field. With a focus on artificial intelligence, cybersecurity, and big data, students can customize their studies to align with their career goals. The program is taught by award-winning faculty members and offers a range of courses, including bio-inspired computing, foundations of algorithms, knowledge representation and reasoning, and more. Upon completing the program, students will have a variety of skills, including designing and analyzing computers, implementing computational processes, and improving software reliability, network security, and information retrieval systems.