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School of Science, Technology, Engineering & Math (STEM)

Computer Science

Online Master of Science in Computer Science (MS)

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$0 Application Fee
$0 Transfer Credit Evaluation

0 Entrance Exams
No GRE/GMAT Required

About This Computer Science Master's Program

Develop advanced knowledge and skills as you learn how to solve real-world problems using the latest technologies. This Master of Science in Computer Science program at American Public University (APU) emphasizes career-readiness with a comprehensive curriculum that integrates cases studies and hands-on projects.

Core courses examine computer science theory to prepare students to design and evaluate scalable, secure, and sustainable computer systems. The General concentration track provides a deeper dive into computer science principles.

You will explore a broad range of applications for machine learning and artificial intelligence (AI) tools, considering both their technical capabilities and their societal and ethical implications. Coursework provides insight into the algorithms and learning techniques that power AI-driven systems.

Through class discussions and assignments, you will sharpen your communication skills and refine your ability to explain complex technical concepts to diverse audiences. Courses also foster proficiency in programming languages and software engineering practices.

Graduates emerge from this online computer science master's program prepared to leverage technology to address technical and societal challenges across industries.

Spanish language learners may complete the Computer Science program through select courses.

What You Will Do

  1. Lead the design, development, and evaluation of secure, scalable software systems and computing applications
  2. Apply advanced computer science principles and engineering methods to analyze and solve complex problems
  3. Communicate technical and research findings clearly and effectively
  4. Uphold ethical and legal responsibilities in computer science practice with awareness of societal impact
  5. Collaborate in teams to deliver innovative, high-quality computing solutions for industry and academia

Degree at a Glance

Number of Credits
36
Transfer up to 15 credits1
Cost Per Credit
$455 | $250*
$386.75** | $409.50***
*with Preferred Military Rate
**with Veteran Grant
***with APUS Opportunity Grant
Courses Start Monthly
Online
and vary from 8 to 16 weeks

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Program Requirements Printable Catalog Version

Students must choose a concentration for this degree program:

This computer science concentration equips graduate students to engineer secure, scalable, and user-focused computing systems across the full stack. Coursework integrates cybersecurity, software engineering, DevSecOps, human-computer interaction, cloud computing, computer architecture, and operating systems. Students gain hands-on experience with network security, data science, and automation techniques to design reliable and defensible systems.

Through applied projects, students learn to implement machine learning for anomaly detection, design cloud-native applications, and optimize performance from hardware through runtime environments. Emphasis is placed on formal methods, measurement-based validation, and alignment with recognized security frameworks.

Graduates will be prepared for careers in secure software engineering, cloud architecture, cybersecurity engineering, UX engineering, and systems development, with the ability to integrate advanced computing concepts into practical, scalable, and human-centered technology solutions.

Objectives:

Upon successful completion of this concentration, the student will be able to:

  • Design, secure, and optimize cloud-native systems using cybersecurity and network defense strategies.
  • Apply DevSecOps and automation principles to enhance reliability and scalability.
  • Evaluate usability and human-computer interaction (HCI/UX) through empirical research.
  • Integrate machine learning and data-driven approaches for threat-informed decision-making.
  • Employ computer architecture and operating systems knowledge to improve system performance and security.

Must take all courses for this section.

Course ID: 5547

|
This advanced cybersecurity course examines strategies, tools, and techniques used in cybersecurity and network defense. Students learn to identify, analyze, and respond to cyber threats through applied training that includes intrusion detection, penetration testing, threat detection, and continuous monitoring. The course explores security controls, information security practices, and policies to mitigate attacks and manage risk across digital systems and enterprise environments. Emphasis is placed on both technical knowledge and practical skills, with hands-on experiences using real-world scenarios. Additional topics include cryptography, malware analysis, and the role of machine learning in advancing cyber defense. By integrating applied methods with broader information and security architecture, the course strengthens expertise for students and professionals pursuing careers in the program of computer science and related fields. (Prerequisite: CSCI510)

Course ID: 5548

|
This advanced software engineering course provides a rigorous exploration of modern software engineering principles, practices, and emerging trends. Emphasis is placed on agile development, DevSecOps, and devops methodologies, highlighting their integration throughout the software development life cycle. Students study both theoretical foundations and applied techniques in software architecture, application development, system architecture, and requirements analysis, while also addressing software security, security testing, and related security best practices. Topics include continuous integration, continuous deployment, and CI CD pipelines, along with cloud computing, cloud services, and modern development environments. Through hands-on projects using industry-standard tools, students gain skills and knowledge essential to contemporary software development and information technology within the broader computer science discipline. (Prerequisite: CSCI505 or CSCI510)

Course ID: 5549

|
This human computer interaction course explores methodologies, tools, and techniques for designing effective and intuitive interactive systems. The course covers human computer interaction principles, user centered design, user interface design, interaction design, and human centered design, emphasizing both theoretical concepts and practical application. Students study usability testing, visual design, design thinking, and UX research to better understand user needs and how people interact with computer technology. Through hands on projects and case studies, students gain skills and knowledge in user experience design, building a solid foundation in applying UX design principles to interactive systems. The course situates human factors and interaction within the broader computer science discipline while preparing learners to apply best practices to diverse design processes and professional career pathways. (Prerequisite: CSCI510)

Course ID: 5550

|
This advanced cloud computing course provides a comprehensive study of cloud computing, addressing both foundational concepts and advanced topics in cloud technologies. The course examines cloud architecture, cloud infrastructure, cloud applications, and cloud solutions, as well as deployment models that support modern enterprise business processes. Students gain knowledge of serverless computing, distributed systems, virtual machines, and data management, while also exploring emerging cloud technologies. Emphasis is placed on cloud security, compliance, and best practices for deploying and managing cloud computing services. Through hands-on projects, students apply skills and techniques using modern software tools to explore the benefits and challenges of cloud service environments. The course situates cloud computing within the broader computer science discipline, reinforcing understanding of critical practices and applications for academic and professional contexts at the university level. (Prerequisite: CSCI530)

Course ID: 5551

|
This advanced computer architecture course provides a rigorous study of computer architecture and the design, analysis, and functionality of modern computer systems. The course emphasizes both theoretical concepts and practical techniques, covering advanced computer architecture topics such as instruction set design, instruction level parallelism, parallel architectures, and processor design, including out of order processors, branch prediction, and speculative execution. Students examine memory systems, including cache structures, cache coherence, memory hierarchies, and virtual memory, as well as interconnection networks and system-level design approaches. Additional areas of focus include optimization, performance, and efficiency in hardware and software solutions, reinforcing connections to algorithms, engineering, and computer science. Through applied analysis of principles and operation, students gain advanced knowledge needed to explore and develop effective designs for contemporary and emerging computer systems. (Prerequisite: CSCI520)

Course ID: 5552

|
This advanced operating systems course provides a comprehensive understanding of modern operating systems principles and operating system design strategies. It prepares students to address real-world challenges through modern techniques and the latest developments in the field. The course will cover various topics: process management, memory management, advanced file systems, distributed systems, optimization techniques, I/O systems, and security. A comprehensive survey of various operating systems, including Unix, Linux, MacOS, Android, real-time and embedded systems, and Windows, will provide a robust foundation for comparative analysis and performance optimization. In addition, the course material emphasizes key concepts in system-level communication, research, and applied problem solving, ensuring that students gain both theoretical knowledge and practical skills relevant to graduate-level program outcomes in computer science and artificial intelligence. (Prerequisite: CSCI550)

Must take all courses for this section.

Course ID: 5543

|
This course serves as an essential primer for students in computer science, providing the foundations for advanced computer science study and subsequent work in CSCI505, CSCI510, and CSCI520. It develops core knowledge and skills in data structures, algorithms, machine learning, and big data analytics. Emphasis is placed on applying theory to computational systems and software development challenges, while introducing techniques that support deeper understanding of advanced computational problems, machine learning, artificial intelligence, and big data analytics. The course also highlights connections to engineering concepts and professional practice within the field. These elements strengthen the subject foundations and align with program outcomes, ensuring students have the resources needed for progression within the Master of Computer Science degree.

Course ID: 5544

|
This course explains the design, analysis, and implementation of data structures and algorithms essential for solving computational problems in computer science. Building upon foundational knowledge, students explore and implement advanced data structures and advanced algorithms, including binary search trees, linked lists, graphs, and hash tables. The course also addresses data storage methods, external storage techniques, sorting strategies, and a range of algorithmic design paradigms such as dynamic programming. Emphasis is placed on applying theory through programming languages like Python and other high-level tools to support software development and systems development. By working with these concepts, students strengthen their skills in analysis, implementation, and optimization, aligning with program outcomes in the broader subject of computer science. (Prerequisite: CSCI500)

Course ID: 5545

|
This course offers a rigorous exploration of machine learning and artificial intelligence, focusing on both theoretical concepts and practical applications. Students study the mathematical and statistical foundations of machine learning models, including supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning. The course emphasizes an advanced understanding of neural networks, artificial neural networks, and deep learning architectures, along with optimization techniques and their use in domains such as natural language processing, computer vision, robotics, and healthcare. Through hands-on development, students gain skills in implementing these models using modern tools and frameworks while engaging in projects that address real-world applications of AI. The course also examines ethical issues and the societal impact of AI technologies, reinforcing critical knowledge within the broader computer science program and aligning with graduate-level outcomes in the subject area. (Prerequisite: CSCI500)

Course ID: 5546

|
This course provides an in-depth study of big data mining and analytics, emphasizing advanced techniques and practical applications across multiple domains. Students examine methods for data analysis, data processing, and data management with both structured and unstructured data, including large datasets, data warehouses, and data lakes. The curriculum covers statistical analysis, machine learning algorithms, feature engineering, and pattern recognition to support informed decision making in areas such as business, healthcare, and science. Through hands-on projects, students develop skills in using modern software, programming languages, and distributed computing frameworks to address real-world information challenges. This course strengthens knowledge within the computer science discipline, preparing learners to explore and apply analytics in diverse professional contexts while aligning with graduate-level program outcomes. (Prerequisite: CSCI500)

Must take all courses for this section.

Course ID: 5553

|
This capstone course is designed to integrate knowledge and skills from the cutting-edge technologies and future trends shaping the field of computer science. Students will engage with the latest research and advancements, applying their comprehensive knowledge from previous coursework to real-world problems and case studies. The course offers direct access to industry challenges and opportunities, exposing innovative ideas. This course represents the initial phase of the Capstone project pathway. Within this course, students will engage in the selection of their project topic and the development of preliminary proposals, all under the guidance of their faculty members. (Prerequisites: CSCI505, CSCI510, and CSCI520)

Course ID: 5554

|
CSCI602 is the final stage of the graduate capstone project pathway, where students will implement their proposals developed in CSCI601. This capstone course represents the concluding stage of the capstone project pathway. This course emphasizes the practical application of research methodologies, data collection, or program development, and the integration of findings into a comprehensive written paper. Additionally, they will begin preparing for their final presentations, which will be based on their written work, and ultimately deliver these presentations as the culmination of their efforts. This course aims to develop students’ ability to conduct independent research, synthesize information, and communicate their findings effectively. (Prerequisite: CSCI601)

Courses Start Monthly

Next Courses Start Feb 2
Register by Jan 30
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Admission Requirements

  • All APU master's degree/graduate certificate programs require a bachelor’s degree (or higher) from an institution whose accreditation is recognized by the Council for Higher Education Accreditation (CHEA®). Please read all graduate admission requirements before applying to this program and be prepared to submit the required documentation.
  • There is no fee to complete the APU admission application for this program. View steps to apply.

CHEA® is a registered trademark of the Council for Higher Education Accreditation. 

Materials Cost

Technology fee: $85 per course 

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1The University reserves the right to accept or deny credits according to policies outlined on our University website. Please see the University's transfer credit policy webpage for complete information.

*Cost Per Credit Hour

The Preferred Military Rate is $250 per credit hour for undergraduate and master's-level courses. This rate is available to all U.S. active-duty servicemembers, National Guard members, Reservists, and military families, including parents, spouses, legal partners, siblings, and dependents.

See all military student benefits.

Cost of Attendance

Learn more about American Public University's cost components and full cost of attendance.