DEN200 Dental Chairside Assisting
College of Health Science Dental Assisting Department
Course Description: This course provides instruction in the principles of clinical chairside dental assisting; dental equipment use and maintenance; safety and instrument identification. Students will learn the many varied dental office designs. Students will also learn chairside operatory procedures, infection control practices, provider and ergonomic assistant positioning. Various dental hand pieces and their attachments, dental operative hand instruments and their tray set-ups are included. Anesthesia and pain control will be discussed. Chairside assisting procedures including dental amalgam and composite restorative materials are taught to a competent level. Additional chairside assisting functions include oral illumination, tissue retraction, evacuation, and dental dam, and the tofflemire matrix band. Advanced chairside functions include placing liners, bases, and varnishes for restorative procedures. Students will be able to pronounce, define, and spell key terms.
Credit Hours: 2.00
Corequisites: DEN200L
DEN100 Dental Anatomy
College of Health Science Dental Assisting Department
Course Description: This course will introduce the student to dental head and neck anatomy and physiology. The focus of this course will include dental terminology related to oral anatomy. Tooth morphology and overview of the dentition is taught at the in-depth level. Students will learn the human skull, including landmarks of the skull, face and oral cavity, bones of the head, and the temporomandibular joint. The musculature, nerves and vascular circulation of the head and neck will be studied. The students will study tooth embryology, histology, structure, components of the periodontium, and systems of tooth identification.
Credit Hours: 3.00
Prerequisites: None
Corequisites: None
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