Master of Science in Information Systems*

*Pending Southern Association of Colleges and Schools Commission on Colleges (SACSCOC) and Council on Postsecondary Education (CPE) approval.

Brescia University’s Master of Science in Information Systems online degree is structured to accommodate the needs of working professionals and those seeking a high-quality, engaging learning experience in a flexible format. The core curriculum consists of six foundational courses that cover key concepts and principles in information systems. Students can further specialize in one of three concentrations: Information Security, Data Analytics, or Artificial Intelligence, each consisting of three additional courses tailored to develop in-depth expertise in the chosen area.

 

Throughout the program, students will gain practical, hands-on experience in designing, implementing, and evaluating information systems solutions that address the diverse needs of organizations across various industries. The program emphasizes critical thinking, problem-solving, and communication skills, empowering students to effectively analyze and address complex information systems challenges.

The MSIS online degree culminates in a capstone project that provides students with the opportunity to synthesize and apply the knowledge and skills gained throughout the program to solve a real-world problem. This project serves as a comprehensive assessment of students’ mastery of the program’s learning outcomes and prepares them for success in their chosen career paths.

Graduates of the MSIS online degree at Brescia University will be well-equipped to excel in a variety of roles in the information systems field, including systems analyst, software engineer, database administrator, network architect, cybersecurity analyst, data analyst, and artificial intelligence specialist. The program’s strong emphasis on ethics and governance ensures that graduates are prepared to navigate the complex professional challenges of the information systems industry with responsibility and integrity.

For additional information, please call 270-686-4353 or email [email protected].

Back to TopAdmissions Process

Students who wish to apply to Brescia University’s MS in Information Systems program should submit the following:

  1. A FREE online application. 
  2. Official transcript showing an earned bachelor’s degree from a college or university accredited by a recognized regional accrediting association.
  3. Undergraduate GPA of 2.5.
    • Upon written request, applicants with a marginally lower GPA may be considered if they address remediation of the reason(s) for the low GPA and their ability to manage successfully the demands of a rigorous graduate program. To demonstrate their academic readiness, students may choose to submit any or all of the following examples:
      • Successful completion of graduate coursework
      • Strong GRE scores
      • Strong writing skills
      • Strong work history in the field (multiple years, with references)
  1. Students for whom English is a second language must meet the minimum acceptable score for the Test of English as a Foreign Language (TOEFL)
    • 550 on the paper-based TOEFL, or
    • 79 on the iBT TOEFL

The MS in Information Systems Program does not grant academic credit for life experience or previous work experience in lieu of academic courses.  Note: The Program reserves the right to require an interview of any applicant.

Graduation Requirements

  • Complete all coursework with a GPA of 3.0.
  • Complete 30 credit hours of academic work.
  • Apply for candidacy after completing a minimum of fifteen credit hours and before completing twenty-one credit hours.
  • Students complete all requirements within five years.

Back to TopCourses

IS 501: Foundations of Information Systems

This course introduces the fundamental concepts and principles of information systems, including hardware, software, data, and their interrelationships. Students will explore the role of information systems in organizations and society, as well as the challenges and opportunities presented by emerging technologies.

IS 502: Systems Analysis and Design

This course provides an in-depth study of the processes and techniques used in the analysis, design, and development of information systems. Students will learn to apply various methodologies and tools to effectively gather user requirements, model system components, and create system specifications.

IS 503: Database Management Systems

This course covers the design, implementation, and management of database systems, focusing on relational databases. Students will learn data modeling techniques, normalization, SQL, and the use of database management systems to create, maintain, and query databases.

IS 504: Software Engineering

This course examines the principles and practices of software engineering, including the software development lifecycle, agile methodologies, and software quality assurance. Students will gain hands-on experience in designing, implementing, testing, and maintaining software applications.

IS 505: Network and Cloud Computing

This course explores the concepts and technologies related to computer networks and cloud computing, including network architectures, protocols, security, and cloud service models. Students will learn how to design, implement, and manage networked and cloud-based information systems.

IS 506: Information Systems Ethics and Governance

This course addresses the ethical, legal, and social issues related to information systems, including privacy, security, intellectual property, and digital divide. Students will learn the principles of information systems governance and develop strategies for managing risks and ensuring compliance with relevant regulations.

IS 520: Capstone Project in Information Systems

In this course, students will undertake a comprehensive project that synthesizes and applies the knowledge and skills gained throughout the program. Students will identify a real-world problem, conduct research, develop a solution, and present their findings to faculty and peers.

IS 601: Information Security Management

This course explores the principles and practices of information security management, including risk assessment, policy development, and security controls. Students will learn to develop and implement effective information security strategies to protect organizational assets and ensure compliance with relevant standards and regulations.

IS 602: Network Security

This course focuses on the design, implementation, and management of secure computer networks. Students will learn the principles of network security, including encryption, authentication, intrusion detection, and firewalls, and gain hands-on experience in securing networked systems.

IS 603: Cybersecurity Risk and Compliance

This course covers the key concepts and practices related to cybersecurity risk management and compliance. Students will learn to assess and manage risks, develop cybersecurity policies, and ensure compliance with relevant laws, regulations, and industry standards.

IS 604: Data Analytics and Visualization

This course introduces students to the techniques, tools, and methodologies used in data analytics and visualization. Students will learn to analyze large datasets, develop predictive models, and create effective visualizations to communicate data insights to diverse audiences.

IS 605: Big Data Technologies

This course explores the technologies and architectures used to store, process, and analyze large-scale and complex datasets. Students will learn about big data.

IS 606: Machine Learning for Data Analytics

This course provides an in-depth study of machine learning techniques and their applications in data analytics. Students will learn to implement, train, and evaluate machine learning models using popular libraries and tools, and apply these techniques to make predictions and inform decision-making processes.

IS 701: Introduction to Artificial Intelligence

This course introduces the fundamental concepts and techniques of artificial intelligence, including knowledge representation, search algorithms, logic, and planning. Students will explore various AI applications and gain hands-on experience in designing and implementing AI solutions.

IS 702: Machine Learning

This course covers the principles and techniques of machine learning, including supervised, unsupervised, and reinforcement learning. Students will learn to design, implement, and evaluate machine learning models for various applications, such as natural language processing, computer vision, and robotics.

IS 703: Deep Learning and Neural Networks

This course provides an in-depth study of deep learning and neural networks, focusing on convolutional neural networks, recurrent neural networks, and generative adversarial networks. Students will learn to implement and train these models using popular deep learning libraries and apply them to solve complex problems in AI.