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.
Students who wish to apply to Brescia University’s MS in Information Systems program should submit the following:
- A FREE online application.
- Official transcript showing an earned bachelor’s degree from a college or university accredited by a recognized regional accrediting association.
- 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)
- 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.
MIS 510: 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.
MIS 520: 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.
MIS 530: Database Management Systems
Covers the design, implementation, and management of relational databases. Topics include data modeling, normalization, SQL, and the use of DBMS software to manage and query large-scale data.
MIS 540: Software Engineering
Examines software development life cycles, agile methodologies, and software quality assurance. Students gain hands-on experience in designing, testing, and maintaining software systems.
MIS 550: Network and Cloud Computing
Explores network architectures, protocols, and cloud service models. Students learn to design, implement, and manage networked and cloud-based information systems, with a focus on security and scalability.
MIS 560: Information Systems Ethics and Governance
Addresses ethical, legal, and societal issues in IS, including privacy, intellectual property, and regulatory compliance. Emphasizes frameworks for responsible decision-making and IS governance.
MIS 590: Capstone Project in Information Systems
Students undertake a comprehensive project synthesizing knowledge and skills gained throughout the program. Includes problem identification, research, systems design, solution implementation, and presentation.
MIS 610: Information Security Management
Explores principles and practices of managing information security, including risk analysis, policy development, and implementation of security frameworks in organizational settings.
MIS 620: Network Security
Covers secure network design and implementation. Topics include encryption, authentication, firewalls, intrusion detection systems, and defense-in-depth strategies.
MIS 630: Cybersecurity Risk and Compliance
Introduces risk management frameworks, regulatory requirements (e.g., GDPR, HIPAA), and the development of compliance strategies within cybersecurity programs.
MIS 640: Data Analytics and Visualization
Covers statistical analysis, data wrangling, and visualization using modern analytics tools. Students develop models and dashboards to inform business and technical decisions.
MIS 650: Big Data Technologies
Focuses on technologies for storing, processing, and analyzing large-scale datasets, including Hadoop, Spark, and NoSQL databases.
MIS 660: Machine Learning for Data Analytics
Introduces supervised and unsupervised learning, classification, clustering, and regression models. Students implement models using Python and industry-standard libraries.
MIS 670: Introduction to Artificial Intelligence
Explores foundational AI techniques including search algorithms, logic, planning, and knowledge representation. Students gain exposure to modern AI applications across industries.
MIS 680: Machine Learning
Covers principles and applications of machine learning including supervised, unsupervised, and reinforcement learning. Emphasis on implementation and evaluation in applied settings.
MIS 690: Deep Learning and Neural Networks
Examines deep learning architectures such as CNNs, RNNs, and GANs. Students implement models in frameworks like TensorFlow and PyTorch to solve complex AI challenges.