Illustrate fundamental concepts of artificial intelligence (AI), including how AI models are trained to learn from data, and the capabilities and limitations of AI tools.
Identify AI applications across industries and their integration into workflows for content creation, problem-solving, and process automation.
Analyze opportunities for leveraging generative AI to enhance productivity, evaluate workflows for optimization, and justify process improvements.
Apply structured prompting techniques using established frameworks to compose prompts that yield relevant, high-quality outputs.
Analyze the privacy, security, and ethical implications of AI implementation, including data handling practices and impacts on organizational and societal levels.
Audit AI-generated outputs for bias, hallucinations, and security vulnerabilities, applying critical human oversight to ensure data integrity, reliability, and accountability.
Develop a continuous learning strategy to evaluate emerging AI tools and assess their suitability for specific workplace applications.
Deploy generative AI on a real task, measuring outcomes, and reporting results against defined metrics.
Artificial intelligence is rapidly reshaping how organizations create content, solve problems, and automate routine work. This course offers a practical, strategic introduction to AI, grounding students in core fundamentals while building the hands-on skills needed to apply generative AI effectively in professional settings. Learners examine real-world use cases across industries, assess where AI can improve workflows, and practice prompt engineering using structured frameworks to produce reliable, high-quality, contextually appropriate outputs. Students will also gain hands-on experience using Google’s Gemini and build readiness for the Google AI Essentials credential. A central emphasis is on Responsible AI and the critical role of human oversight. Students also develop the strategic capability to identify and prioritize AI opportunities, optimize processes, and communicate governance considerations. The course culminates in a project where students deploy a generative AI tool on an authentic task, define success metrics, measure outcomes, and present results and risk controls to stakeholders.