EET113 DC and AC Circuits
College of Technology Engineering Technology Department
Course Description: This course provides an introduction to AC and DC circuits through simple series and series-parallel circuits used to illustrate applications of Ohm’s Law and Kirchhoff’s Laws. Students will learn about power in DC resistive circuits and sine waves, complex numbers, and phasors applications in the analysis of AC circuits.
Credit Hours: 3.00
Prerequisites: MTH200
Corequisites: None
BAN327 Data Visualization and BI Tools with Applied AI
College of Business and Criminal Justice Business Department
Course Description: This course builds practical skill with business analytics tools and introduces responsible AI assistance. Students design surveys, manage datasets, and build visualizations and dashboards for decision support. Topics include BI concepts, data collection methods, data quality and governance, visualization best practices, and action-plan development. Students also learn when and how to use AI assistants to draft survey items, document methods, suggest formulas or DAX, explain charts, and generate first-pass narratives. Emphasis is on verification, reproducible workflows, and human-in-the-loop review.
Credit Hours: 3.00
Prerequisites: BAN325
Corequisites: None
BAN485 Data Mining II: R, Python, and Applied AI
College of Business and Criminal Justice Business Department
Course Description: This course extends data mining with hands-on work in R and Python and selective use of AI. Students prepare and visualize data, build and compare models, and communicate results for business decisions. Topics include linear and nonlinear regression, logistic regression, association-rule mining (market basket analysis), and k-means clustering. Projects include analyzing social-media and survey datasets with Python and AI to extract signals, generate first-pass summaries, and validate findings. Emphasis is on feature engineering, evaluation and validation, interpretability, and clear recommendations.
Credit Hours: 3.00
Prerequisites: BAN385
Corequisites: None
BAN317 Data Analytics, Machine Learning, and Business Forecasting
College of Business and Criminal Justice Business Department
Course Description: This course introduces practical approaches to business forecasting and decision support using artificial intelligence and modern data tools. Students will work in cloud-based environments to analyze data using guided tools that support SQL-style operations and Python workflows. Key activities include structuring multi-tab datasets, creating KPI dashboards for cost, risk, and performance, and applying AI-assisted predictive models to inform business decisions. Learners will calculate and interpret forecasting and error metrics to evaluate scenarios and validate spreadsheet-based analyses. Emphasis is placed on using enhanced analytics platforms to run and interpret models, compare outcomes, and generate clear, stakeholder-ready reports. Throughout the course, students will practice responsible AI use by ensuring transparency, traceability, and reliability in their data-driven recommendations.
Credit Hours: 3.00
Prerequisites: BUS121
Corequisites: None
CIS376 Data Analytics Tools
College of Technology Cybersecurity Department
Course Description: This course will provide students with the advanced concepts and practical applications of database technologies and visualization tools for data analytics. Through a project-based approach, students will learn to use SQL (focusing on Oracle), MongoDB, PowerBI, Excel, Tableau, and cloud computing platforms. Students will also explore the integration of machine learning and AI in business analytics using Python and R.
Credit Hours: 3.00
Corequisites: None
CIS469L Data Analytics Methods and Modeling LAB
College of Technology Cybersecurity Department
Course Description: This course will provide students with application oriented experiences in data analytics methods and modelling. Student will learn skills required to use data analytics methods and modelling tools in a data oriented solution.
Credit Hours: 1.00
Prerequisites: CIS376
Corequisites: CIS469
CIS469 Data Analytics Methods and Modeling
College of Technology Cybersecurity Department
Course Description: This course will provide students with an application of data analytics methods, modelling, and visualization tools and techniques. Students will learn about different tools, methods, and approaches to the depiction of data.
Credit Hours: 3.00
Prerequisites: CIS376
Corequisites: CIS469L
MSCS501 Cybersecurity with AI Synopsis
College of Technology Cybersecurity Department
Course Description: This course provides a comprehensive exploration of cybersecurity strategy in the era of artificial intelligence (AI). Students will examine how AI enhances threat intelligence, risk evaluation, and organizational defense through advanced analytical frameworks. Guided by NIST standards, students will apply critical thinking to assess adversarial tactics, interpret complex security data, and explore adaptive strategies that strengthen organizational resilience. Throughout the course, students will also collaborate with AI assistants to support analysis, decision-making, and strategy development in real-world cybersecurity contexts.
Credit Hours: 3.00
Prerequisites: None
Corequisites: None
MSCS645 Cybersecurity Strategies (Prevention and Protection)
College of Technology Cybersecurity Department
Course Description: This course will provide students with advanced knowledge of how to navigate this new world of security by developing effective information security strategies, including mission, awareness, education, culture, task, technology, and people. Students will apply different components, starting from policy, legal, and compliance aspects of governance, audit management, and business continuity planning.
Credit Hours: 3.00
Prerequisites: MSCS501
Corequisites: None
MSCS643 Cybersecurity Governance and Compliance using AI Gap Detection
College of Technology Cybersecurity Department
Course Description: This course explores how artificial intelligence (AI) can support compliance and governance in cybersecurity by identifying and analyzing detection gaps. Students will use AI tools, such as ChatGPT, to investigate security gaps, translate findings into everyday language, and map them to key regulatory requirements. The course emphasizes U.S. utility sector compliance, focusing on standards like NIST 800-53 and GLBA 501. Through labs and case studies, students will learn to identify detection gaps, connect them to specific regulatory obligations, interpret control IDs and clauses, and explore best practices for governance, compliance, and operational improvement in federally regulated industries. By the end of the course, students will be able to apply AI-assisted analysis to strengthen compliance strategies and improve cybersecurity governance practices.
Credit Hours: 3.00
Prerequisites: MSCS501
Corequisites: None