Master of Science in Artificial Intelligence

The Master of Science in Computer Science at Concordia University Wisconsin prepares graduate students to advance their expertise in computing through rigorous study of algorithms, systems design, and emerging technologies while integrating ethical reflection and professional responsibility. The program combines core technical mastery with opportunities for specialization in areas such as software engineering, cybersecurity, and data science, and culminates in applied capstone experiences that emphasize real-world problem solving. Graduates emerge with deep technical competency, strategic thinking, and leadership skills that empower them to innovate responsibly in industry, research, and service, grounded in the university’s commitment to purposeful Christian-informed engagement.

By fulfilling all of the course requirements for the Master of Science in Artificial Intelligence, students be will able to:

  1. Evaluate and implement AI systems with ethical and legal integrity, addressing bias, fairness, transparency, privacy, accountability, and issues related to economic access and potential harm. Articulate a vocational understanding of artifical intellgence as a means of serving others, guided by a Christian worldview that informs responsible innovation, professional humility, and care for the common good.
  2. Conduct data aquisition, including collecting, cleaning, storing, and analyzing data from multiple sources using APIs, databases, and machine learning algorithms to solve real-world problems. Design and integrate domain-specific AI agents, enabling secure and flexible task execution with real-time knowledge integration.
  3. Apply foundational AI theory and mathematics, including neural networks, probabilistic models, evolutionary computation, language theory, and search algorithms. Evaluate and implement AI systems with ethical and legal integrity, addressing bias, fairness, transparency, privacy, accountability, and issues related to economic access and potential harm.
  4. Develop AI systems and intelligent agents using supervised, unsupervised, and reinforcement learning. Engineer effective prompts to guide large language models (LLMs) for better alignment, formatting, and adaptability in practical applications.
  5. Communicate AI concepts, results, and ethical considerations effectively to both technical and non-technical audiences with clarity and responsibility. Define and evaluate Artificial Intelligence, distinguishing between semantic, historical, and popular definitions.
  6. Utilize LLMs in industrial settings through APIs, embeddings, and structured deployment in embedded systems and enterprise environments. Assess the performance and limitations of AI models using appropriate evaluation metrics, and iteratively refine models based on diagnostic results.

Curriculum

CSC 5010AI Ethics and Vocation3
CSC 5015Applied Artificial Intelligence3
CSC 6210Applied Restful APIs and Integrations3
CSC 6270Applied Research Practicum3
CSC 5025Cybersecurity3
CSC 6220Language Theory3
CSC 6230Industrial AI Application and Practice3
CSC 6240Data Acquisition and Management3
CSC 6250Neural Networks and Deep Learning3
CSC 6260Natural Language Processing3
Total Hours30

Plan

Plan of Study Grid
Semester 1Hours
CSC 5010 AI Ethics and Vocation 3
CSC 5015 Applied Artificial Intelligence 3
 Hours6
Semester 2
CSC 6210 Applied Restful APIs and Integrations 3
CSC 5025 Cybersecurity 3
 Hours6
Semester 3
CSC 6220 Language Theory 3
CSC 6230 Industrial AI Application and Practice 3
 Hours6
Semester 4
CSC 6240 Data Acquisition and Management 3
CSC 6250 Neural Networks and Deep Learning 3
 Hours6
Semester 5
CSC 6260 Natural Language Processing 3
CSC 6270 Applied Research Practicum 3
 Hours6
 Total Hours30

Course options and schedule are subject to change.