Master of Science in Computer Science

Program Overview

Master of Science in Computer Science | MSCS w/ CPT

Overview

The Master of Science in Computer Science (MSCS) program equips students with the necessary knowledge and skills to thrive in careers as software developers, software engineers, data analysts, cybersecurity specialists, machine learning engineers, artificial intelligence specialists, and more. The MSCS degree is highly valued in the job market and offers graduates opportunities for career growth. Ottawa University Information Science and Technology Institute (ISTI) is dedicated to creating new enrollment opportunities by training highly skilled computer science and business-centric professionals to lead and manage computer systems in organizations of all types.

Where Computer Science | MSCS w/ CPT is offered

• Overland Park, Kansas

Education and Qualifications

The Master of Science in Computer Science (MSCS) program is designed for students seeking computer science and technology positions. This degree offers numerous benefits and prepares students for diverse career options that are currently in high demand (Software Engineer, Data Scientist, Computer Network Architect, Cybersecurity Analyst, etc.).

Careers in Computer Science | MSCS w/ CPT

Recent graduates have an average base starting salary of $95,000, with some earning upwards of $120,000 depending on their field and location. This salary range highlights the high demand for individuals with computer science and machine learning skills and the value that employers place on such a degree. MSCS graduates can expect a promising and prosperous career ahead of them.

Computer Science | MSCS w/ CPT Courses

Required Core Courses

• CST 7010 Advanced Computer Science Topics: Delves into cutting-edge topics and emerging trends in computer science, including artificial intelligence, machine learning, computer vision, natural language processing, big data, and cloud computing. Students will gain an understanding of advanced algorithms, techniques for solving complex computational problems, and modern tools and technologies used in the industry.
• CST 7080 Cloud System Design: Provides students with the knowledge and skills needed to design and implement cloud-based solutions for complex business systems. Topics covered include cloud deployment models, virtualization, containerization, and cloud architecture.
• CST 7090 Advanced Network Design and Deployment: Graduate-level course exploring advanced network design and deployment principles and techniques. This course focuses on advanced topics such as network architecture, design, security, and management. Students will learn about the latest trends and best practices in network design and deployment, including emerging technologies, software-defined networking, cloud computing, and virtualization. Students will gain practical experience in designing and deploying enterprise-level networks, configuring network security, and managing network operations.
• CST 7100 Scalable Computer Architecture: This course thoroughly studies computer architecture principles and techniques for building scalable and high-performance computing systems. The course covers various topics such as parallelism, memory hierarchy, interconnects, and techniques for designing scalable computer systems that can handle large-scale workloads. The course also covers emerging trends and challenges in scalable computing, such as big data analytics, machine learning, and cloud computing.
• CST 7300 Advanced Systems Analysis and Design: Delves into the complexities of the systems development life cycle, mastering advanced methodologies and techniques to design, analyze, and implement complex information systems. Building on foundational principles, the course aims to equip students with the hands-on experience and theoretical knowledge to tackle real-world projects. Using tools and frameworks, students will use case studies, collaborative projects, and simulations to design and analyze system architectures, workflows, and interfaces.
• CST 7500 IT/IS Project Management: Designed to equip students with the skills and methodologies to effectively plan, execute, and oversee information technology and systems projects. Drawing from established project management frameworks such as Agile and Waterfall, the course emphasizes a holistic approach, covering key areas, including scope definition, timeline scheduling, resource allocation, risk assessment, and stakeholder communication.
• CST 7600 Ethics in Computer Science: Explores ethical principles, legal frameworks, and social responsibilities in computer science. Students will examine the impact of technology on society, evaluate the ethical implications of emerging technologies, and learn to apply decision-making frameworks to address ethical challenges. Topics include data privacy, artificial intelligence ethics, bias in algorithms, intellectual property, and professional conduct. The course emphasizes critical thinking and responsible computing practices.

AI and Machine Learning Concentration Courses

• CST 7020 Programming Language Logic: Focuses on programming language logic, including the syntax and semantics of programming languages, the principles of programming language design, and program correctness. Students will learn to reason about programs, write programs that meet certain specifications, and formally verify program correctness. Topics covered include propositional and predicate logic, operational semantics, type theory, and program verification.
• CST 7030 Analysis of Algorithms and Computation: This course delves into the foundational principles of algorithmic problem-solving and computational efficiency. The course explores a range of algorithms, from sorting and searching to graph traversal and dynamic programming, while emphasizing analytical techniques for evaluating their time and space complexities. Students will gain hands-on experience designing, implementing, and critically assessing algorithms for various problems.
• CST 7040 Fundamentals of AI and Machine Learning: Introduces students to the theory and practice of machine learning, covering the basic concepts and techniques of supervised and unsupervised learning, including decision trees, neural networks, clustering, and regression. Students will learn how to apply these techniques to real-world problems in various fields, such as natural language processing, computer vision, and data mining.
• CST 7050 Neural Machine Learning and Data Mining: Provides an in-depth understanding of the concepts, techniques, and algorithms used in modern neural machine learning and data mining applications. Topics covered include deep learning, convolutional neural networks, recurrent neural networks, natural language processing, and data mining algorithms. Students will also gain experience working with tools and frameworks such as TensorFlow, Keras, and PyTorch.
• CST 7060 Data Science for Business Intelligence: Covers the fundamentals of data analysis and how to use data to drive business intelligence. Students will learn how to use data mining techniques, statistical analysis, and data visualization tools to identify trends, patterns, and insights that can help organizations make better decisions. The course also covers data cleaning, preprocessing, and integration.

Cyber Security Concentration Courses

• CST 7070 Information Insurance and Cybersecurity: This course provides an in-depth study of cryptography and computer security's theoretical and practical aspects. Topics covered include classical and modern cryptographic systems, encryption and decryption techniques, authentication, secure communication protocol, digital signatures, access control, security models and policies, and vulnerability assessment and management. Students will also explore emerging trends in cryptography and computer security.
• CST 7110 Cyber Forensics and Incident Response: Provides students with advanced knowledge and skills in digital forensics and incident response. Students will learn to investigate cyber incidents, identify evidence, and preserve digital artifacts. They will also learn to analyze digital evidence and report their findings clearly and concisely. Topics covered in the course include digital forensics methodologies, forensic acquisition and analysis of electronic data, network forensics, mobile device forensics, malware analysis, incident response procedures, and legal and ethical considerations in cyber investigations.
• CST 7200 Cybersecurity Risk Management and Assessment: This advanced course provides students with comprehensive knowledge and practical skills to identify, analyze, and mitigate cybersecurity risks in complex organizational environments. This course covers key concepts of risk management frameworks, and risk mitigation strategies. Students will learn to develop and implement effective cybersecurity policies, conduct risk assessments, and create incident response plans.
• CST 7220 Cybersecurity Risk Management and Assessment: This course explores the cybersecurity aspects of Internet of Things (IoT) devices, artificial intelligence (AI) systems, and cryptocurrency technologies. Students will gain a deep understanding of the security vulnerabilities, threats, and best practices associated with these interconnected domains. The curriculum covers IoT architecture and protocols, AI-driven security solutions, blockchain technology, and cryptocurrency security measures. Through hands-on projects and case studies, students will develop practical skills in securing IoT ecosystems, implementing AI-based threat detection, and safeguarding cryptocurrency transactions.
• CST 7240 Advanced Concepts and Strategies: This graduate-level course provides an in-depth exploration of cloud security principles, challenges, and solutions in modern computing environments. Students will develop a comprehensive understanding of risk management, secure cloud architecture, DevSecOps practices, and security assessment techniques specific to cloud computing.

University Accreditation

Ottawa University, as a whole, is accredited by the Higher Learning Commission.

Specific degree programs within our institution have also been accredited by relevant bodies within the field:

• Accreditation Council for Business Schools and Programs (ACBSP)
• Commission on Collegiate Nursing Education (CCNE)
• National Addiction Studies Accreditation Commission (NASAC)
• Council for the Accreditation of Educator Preparation (CAEP)
• National Council for State Authorization Reciprocity Agreements (NC-SARA)

We are proudly recognized for our commitment to student excellence by the following designations:

• Colleges of Distinction
• GOLD Military Friendly School

Why Choose Ottawa

Almost all courses in Ottawa University’s programs are available online and accredited by The Higher Learning Commission. We make it easy for you to transfer credits in order to help keep tuition costs down. We also offer courses in accelerated 8-week terms in order to reduce your time to completion. These are just a few of the reasons why we are proud to be the best, fastest, and most affordable option locally in the Kansas City, Milwaukee, and Phoenix areas, as well as serving students nationally through our online degrees.