Business Applications of AI 10156122

Explores the use of AI in modern business environments, focusing on practical applications such as predictive analytics, customer relationship management, and automation. Students will analyze real-world case studies, assess the benefits and challenges of integrating AI into business operations, and explore AI-powered business tools and platforms.

Clinical Supervision In Substance Abuse Counseling 47520410

The Clinical Supervision in Substance Abuse Counseling course is designed to fulfill the Wisconsin Department of Safety and Professional Services requirement of 30 hours of classroom training in clinical supervision. This course is designed for working professionals with the flexibility of online and self-paced. Each module includes a minimum of 6 hours of training in each of the following domains: Assessment or Evaluation, Counselor Development, Management or Administration, Professional Responsibility.

Crisis Intervention And Stress Management 10520143

Explores crisis intervention and stress management techniques used in professional settings. Learners examine developmental, situational, and traumatic crises, including those related to loss, victimization, substance use, veterans, and serious illness. Learners practice how to respond to crises in ways that support, empower, and advocate for individuals and communities while practicing cultural humility and being trauma sensitive. Emphasis is placed on ethical practice, safety, and the use of evidence-based strategies such as motivational interviewing and reflective practitioner methods to address stress, secondary trauma, and burnout.

Data Concepts 1 10156131

Data Concepts 2 10156132

Data Mining & Predicitve Analytics 2 10156111

Employs RapidMiner, R, and Orange software packages in order to explore text mining using classification algorithms. Uses k-nearest neighbor and decision trees to further explore classification on structured data. Lastly, learners evaluate time series data using forecasting algorithms. Learners demonstrate their findings via PowerPoint and short video presentations.

Data Mining & Predictive Analytics 1 10156109

Employs RapidMiner, R, and Orange software packages in order to facilitate exploration of clustering, association, and text mining algorithms. Learners import a variety of data and use the algorithms in the various software products to extract meaningful information. Learners demonstrate their findings via PowerPoint and short video presentations.

Data Mining & Predictive Analytics 3 10156115

Employs Python, Excel, R, and other GUI software to explore a variety of algorithms that fall under the umbrella of predictive analytics and data mining. Learners derive meaning from data using neural networks. Learners apply statistical models including linear and logistic regression. Lastly, learners evaluate data using Naïve Bayes and Bayesian Networks. Learners demonstrate their findings via PowerPoint and short video presentations.

Data Visualizations 1 10156113

Design charts, graphs, dashboards, and other visualizations with an understanding of color and chart type. Learners use the appropriate types of chart based on the data that is being presented and the audience that is viewing the presentation and also build charts for the purpose of exploratory data analysis.

Data Visualizations 2 10156117

Builds on Data Visualizations 1 and emphasizes choosing proper charts for quantitative and time-series analysis. Learners build effective dashboards and tell effective stories based on audience needs and analytical comfort. Learners contrast the ways in which data visualization can be used to tell truthful and untruthful stories.

Ethics and Implications of AI 10156123

Examines the ethical, legal, and societal implications of artificial intelligence (AI). Students will explore issues such as bias in algorithms, data privacy, and the broader impact of AI on employment and social structures and will utilize frameworks for ethical AI development and deployment, emphasizing responsible data-driven decision making.

Foundations of Data Engineering 10156124

Provides a comprehensive introduction to data engineering principles and foundational cloud computing for data. Students will learn to build and maintain scalable data pipelines, process and store large datasets, and implement cloud-based solutions for secure and efficient data management. With a focus on real-world applications, this course explores data ingestion, transformation, and storage strategies using AWS tools. By combining essential cloud computing skills with data engineering techniques, students will develop the expertise needed to support analytics, machine learning, and business intelligence workflows across diverse environments.

Introduction to AI 10156121

Introduces the fundamental concepts and history of artificial intelligence (AI), including machine learning, neural networks, large language models and natural language processing. Students will explore AI technologies, review their development over time, and study their impact on society. This foundation will provide students with the necessary framework to understand and work with AI in future courses and professional settings.

Introduction To Gerontology 10520150

Introduces the study of aging and how biological, psychological, and social changes affect people as they grow older. Learners explore factors that influence health, independence, and quality of life for older adults. The course also examines how society and culture shape attitudes toward aging. Learners use communication and interviewing skills to understand and support older adults in human services settings.

Introduction To Human Services 10520101

Explores the history, values, and philosophy of the helping professions and their connection to social welfare systems. Learners examine public and private programs, service delivery systems, and professional roles across agency settings. Learners are introduced to the ethical standards and codes of the National Association of Social Workers (NASW), the National Organization for Human Services (NOHS), and NAADAC, the Association for Addiction Professionals and the National Certification Commission for Addiction Professionals (NCC AP) Code of Ethics. Learners apply advocacy and reflective practice skills to support access to services and overall well-being in diverse communities.

Introduction to Python 10156102

Introduces computer programming and terminology in the Python programming language. Special attention is paid to concepts essential to writing basic computer programs. These concepts include: Data Types, Expressions, Loops, File Interaction, Collections, and Functions. Additionally, several tools required to develop Python applications will be explored. Throughout the course learners will develop increasingly complex applications as new topics are introduced.

Introduction to R 10156114

Introduce learners to the foundational concepts of data programming in the open-source language R. Learners explore ways to visualize data, examine data structures, and model the relationship between variables using commands in R. Learners incorporate problem-solving and critical thinking skills as they write commands to support their work with data analysis.

Issues In Child Maltreatment 10520141

Explores the complex social, environmental, and individual factors that influence the safety and well-being of children and families. Learners examine patterns of maltreatment, laws, and child welfare policies such as the Wisconsin Children’s Code, the Indian Child Welfare Act, and the Adoption and Safe Families Act. Learners build on prior knowledge of communication, documentation, and human development to apply evidence-based approaches such as motivational interviewing and trauma-informed care. Emphasis is placed on ethical practice, professional boundaries, and family-centered strategies that promote prevention, intervention, and well-being across diverse communities.

Professional Readiness 10520145

Applies professional knowledge and skills needed for success in the human services field. Learners analyze professionalism, legal and ethical standards, and characteristics of effective professional relationships. Emphasis is placed on culturally responsive practice, worker safety, self-care, and the value of active and engaged supervision. Learners explore community resources, best practices, and techniques that support ethical and effective service delivery. Note: Learners are encouraged to take this course at the end of the Human Services Assistant Technical Diploma or the semester before Field Experience 1.

Python for Data Analytics 10156103

Introduces topics and libraries related to data analytics in the Python programming language. Learners will explore reading, processing, and writing files in native Python. Then they will explore data analytics, processing and visualization using NumPy, Pandas, Matplotlib and Seaborn.

Registered Behavior Technician 47520428

The Registered Behavior Technician (RBT®) is a nationally recognized paraprofessional certification in behavior analysis. RBTs assist in areas such as delivering direct behavior-analytic services, aiding in implementing behavior plans which are developed by the BCBA or BCaBA, and collecting data. Completing this 40-hour course will provide students with the necessary training hours required for access to the RBT certification exam with the Behavior Analysis Certification Board (An exam separate from NTC).

Using AI & Technology in Supervision 47520446

Using AI & Technology in Supervision (Ethically) is an advanced continuing education course for Wisconsin DSPS-credentialed SUDC Clinical Supervisors addressing the ethical, legal, and professional implications of AI and digital tools in supervision. Grounded in the NAADAC Code of Ethics (2025) and the heightened confidentiality standards of 42 CFR Part 2, the course examines risks related to confidentiality, data security, bias, and organizational liability. Through applied case analysis and policy-focused activities, participants evaluate AI tools, vendor relationships, and impacts on supervisory judgment, equity, and counselor autonomy, while developing AI-inclusive supervision policies.