This course is an introduction to the core concepts, terminology, and capabilities of modern artificial intelligence. Learners will explore foundational topics such as machine learning, natural language processing, computer vision, responsible AI principles, and the use of cloud-based AI services. Gain practical experience through a combination of lectures, demonstrations, and hands-on labs aligned with current AI technologies. This course emphasizes understanding how AI systems work, when to apply them, and how to evaluation their effectiveness. Students will use guided labs in live environments.
Outcomes
- Define and explain foundational AI terminology, including machine learning, deep learning, classification, regression, clustering, and supervised vs. unsupervised learning
- Analyze key machine learning processes, including data preparation, model training, evaluation, and deployment
- Create, refine, and evaluate effective prompts to interact with AI systems, using clear instructions and context while critically assessing outputs for accuracy, bias, and ethical use in real-world scenarios
- Identify AI agents are, describe how they operate in real-world applications, and use basic AI tools to interact with and evaluate simple AI agents in ethical and responsible ways
- Apply foundational AI and machine learning concepts within IT contexts by interpreting model outputs, evaluating basic performance metrics, identifying sources, and explaining operational impacts
Distribution
Professional Education
Campus
Central
Area of Study
Career Education