Learners explore the full life cycle of designing, building, and deploying no-code generative Al agents. Designed for absolute beginners, this course introduces the foundations of agentic Al, including how agents plan, act, and contribute to everyday workflows. Learners map simple workflows by defining inputs, reasoning loops, memory needs, and outputs, while using prompt-based strategies to guide tone, accuracy, and reliability. Through guided minitasks and reflection, students practice building agents using free or freemium tools, evaluating platforms, configuring settings, and deploying agents without programming knowledge. They develop skills in testing and refining agent behavior, identifying bias, and implementing safeguards to support ethical and privacy-aware use. From embedding agents into chats, documents, and web interfaces to improving their performance through iteration, learners gain practical experience with Al-supported productivity, communication, and decision-making. Throughout the course, students build a multi-agent portfolio that includes annotated prompts, workflow diagrams, and improvement notes, demonstrating their transferable skills across digital environments.
This is one of two foundational courses in the occupation-specific Artificial Intelligence (AI) series of courses. It is strongly recommended that students have a mastery of competencies usually obtained by completing AI Prompt Engineering (ONT AI1), followed by Agentic AI (ONT AI2), before proceeding with other occupation-specific courses in the series: AI for Entrepreneurs, AI for Marketing, AI for Human Resources, AI for Business Analysis.