Artificial Intelligence (AI)

Formerly COSA 55. This course introduces students to foundational Artificial Intelligence (AI) and Machine Learning (ML) principles, preparing them for workplace applications in business, marketing, education, and healthcare. Topics include AI history, types of AI, machine learning basics, real-world applications, and ethical considerations. Students will analyze AI-powered tools and develop skills in evaluating AI technologies for responsible and effective use in professional environments.

Formerly COSA 60. This course provides students with theoretical knowledge and practical artificial intelligence (AI) skills tailored to meet industry demands. The curriculum encompasses a broad spectrum of AI, from foundational concepts to practical applications, including advanced prompt engineering techniques. It addresses ethical considerations and the broader societal impacts of AI. The pedagogical approach integrates weekly lectures with hands-on activities and projects, fostering an interactive learning environment emphasizing real-world applicability.

This course introduces students to the design and application of conversational and agentic AI systems. Students learn how modern AI models enable natural language interactions, multi-turn dialogues, and autonomous task completion. Using no-code and low-code platforms, learners will design, test, and deploy conversational assistants, workflow agents, and domain-specific AI applications. Emphasis is placed on human-centered design, ethics, and responsible deployment across industries such as business, education, customer service, and healthcare. Students produce a portfolio project showcasing a functional AI agent or assistant.

This course introduces students to multi-modal artificial intelligence (AI), focusing on applied systems that integrate text, images, audio, and video for real-world tasks. Using no-code and low-code tools, students will design, test, and deploy multi-modal prototypes such as image captioning tools, cross-modal search, and voice-enabled assistants. Emphasis is placed on workforce applications, ethical design, and human-centered innovation. Designed for learners pursuing stackable AI certificates or foundational skills for careers in digital transformation, this course culminates in a portfolio-ready applied project.

This course introduces students to the design and implementation of human–AI collaborative workflows and automation systems. Using no-code and low-code platforms, students will integrate large language models, multi-modal tools, and productivity applications to streamline real-world processes. Topics include task design, agent orchestration, retrieval-augmented generation (RAG), and human-in-the-loop evaluation. Emphasis is placed on ethical, reliable, and equitable automation for business, education, and community applications.

This advanced, project-based capstone course allows students to design, develop, and present an integrated AI solution that demonstrates comprehensive mastery of generative, conversational, and multi-modal AI systems. Students work in teams or individually to analyze a real-world problem, develop an applied AI workflow, and deploy a functional prototype using no-code and low-code tools. Emphasis is placed on ethical design, human–AI collaboration, system integration, and the presentation of professional documentation and analytics. The course culminates in a final portfolio and presentation showcasing a working AI solution for workforce or community impact.

Formerly COSA 655. This course introduces students to foundational Artificial Intelligence (AI) and Machine Learning (ML) principles, preparing them for workplace applications in business, marketing, education, and healthcare. Topics include AI history, types of AI, machine learning basics, real-world applications, and ethical considerations. Students will analyze AI-powered tools and develop skills in evaluating AI technologies for responsible and effective use in professional environments.

Formerly COSA 660. This course provides students with theoretical knowledge and practical artificial intelligence (AI) skills tailored to meet industry demands. The curriculum encompasses a broad spectrum of AI, from foundational concepts to practical applications, including advanced prompt engineering techniques. It addresses ethical considerations and the broader societal impacts of AI. The pedagogical approach integrates weekly lectures with hands-on activities and projects, fostering an interactive learning environment emphasizing real-world applicability.

This course introduces students to the design and application of conversational and agentic artificial intelligence systems. Students learn how modern AI models enable natural language interactions, multi-turn dialogues, and autonomous task completion. Using no-code and low-code platforms, learners design, test, and deploy conversational assistants, workflow agents, and domain-specific AI applications. Emphasis is placed on human-centered design, ethics, and responsible deployment across industries such as business, education, customer service, and healthcare. Students complete a portfolio project showcasing a functional AI agent or assistant.

This course introduces students to applied multi-modal artificial intelligence (AI) systems that integrate text, images, audio, and video for real-world applications. Students learn how multi-modal AI models interpret and generate information across various formats, enabling the creation of innovative digital tools and experiences. Using no-code and low-code platforms, learners design, test, and deploy prototypes such as image captioning systems, video summarizers, and voice-enabled agents. Emphasis is placed on practical workforce applications, responsible and ethical design, and human-centered innovation. The course culminates in a portfolio-ready project that demonstrates foundational proficiency in multi-modal AI integration and applied problem-solving.

This course explores human–AI collaboration and workflow automation in professional, educational, and creative contexts. Students learn to integrate generative and multimodal AI tools with automation platforms to streamline real-world processes. Using no-code and low-code tools, learners will design intelligent workflows that combine data retrieval, natural language processing, and AI-powered task execution. Emphasis is placed on responsible automation, human oversight, and the creation of inclusive, ethical, and efficient human–AI systems. The course culminates in a capstone project demonstrating an applied automation prototype ready for workplace adaptation.

This advanced capstone course guides learners through the design, development, and presentation of a fully integrated applied AI solution that demonstrates mastery of generative, conversational, and multi-modal AI systems. Participants identify a real-world or workforce-based problem, plan and build an AI-enabled workflow, and deploy a functional prototype using no-code or low-code tools. Emphasis is placed on ethical AI design, human–AI collaboration, automation, and professional presentation. The course culminates in a final project portfolio showcasing applied AI integration skills for workforce or community impact.