Generative and Agentic AI

Module 1: Foundations of Generative and Agentic AI

• ⁠Evaluate the strategic value of AI functionalities such as chatbots, reasoning, and multimedia

• Construct an evaluation of the cost of an AI system

• ⁠Distinguish between major AI model types and terminology

Module 2: The Rise of Agentic AI and Emerging AI Platforms

• Explain the most relevant AI platform or approach for a specific sector and its application to agentic AI use cases

• Evaluate the key factors influencing the selection of open-source versus proprietary AI platforms within a specific organizational context

• Develop a landing page using AI

• Prompt AI to create a visual mock-up and functional HTML code

• Activate the code by saving and reuploading

• Explain a new AI workflow in an organization

Module 3: Connecting Agents to Digital Ecosystems

• Construct a use case demonstrating agent-based interaction across integrated tools

• Write a structured email-style proposal that outlines a specific use case for an AI agent within an organizational context

• Analyze a business workflow to determine how an AI agent could improve efficiency, reduce costs, or enhance user experience

• Design an integration approach that specifies how the proposed agent would connect with existing systems, platforms, or application programming interfaces (APIs)

• Evaluate the potential risks, ethical considerations, and success metrics associated with deploying the proposed AI agent

Module 4: Cybersecurity: Classic Scenarios, Agent Risks, Disinformation, and Systemic Impact

• Analyze organizational AI systems and workflows to identify potential cybersecurity risks using the National Institute of Standards and Technology (NIST) Cybersecurity Framework categories

• Evaluate current security practices to identify gaps in access control, monitoring, response, and recovery capabilities

• Develop a structured AI risk and security plan, including stakeholders, training, and incident response procedures

• Recommend actions to improve organizational readiness across identify, protect, detect, respond, and recover domains

• Analyze organizational AI systems and workflows to identify potential cybersecurity risks

• Evaluate how accountability is defined and enforced alongside security practices and governance in AI systems

Module 5: AI Agents by Business Function

• Describe the organizational context, including industry, organization type, and department, relevant to a proposed AI-driven product design initiative

• Summarize the current product design workflow within an organization to establish a baseline for improvement

• Select an appropriate AI technology for integration into a product design process based on its capabilities and relevance

• Develop a structured plan outlining how AI can be integrated into a product design workflow to improve efficiency, effectiveness, or quality

• Identify an appropriate AI agent architecture for a given organizational context and explain key trade-offs

• Identify opportunities for AI-enabled BPO and describe their potential organizational impact

Module 6: The Last Mile- From Pilot to Practice

• Propose measurable key performance indicators (KPIs) that evaluate the effectiveness of an AI system in relation to business outcomes.

• Describe the organizational context including sector, organization type, and department relevant to an AI implementation

• Summarize the purpose and functionality of a proposed AI system within a business workflow

• Write three to five key performance indicators (KPIs) that measure the effectiveness of an AI implementation

• Evaluate how the selected KPIs align with business goals, and indicate whether the AI system is achieving its intended outcomes

Module 7: Governance, Compliance, and Agent Testing

• Identify applicable regulatory frameworks (e.g., GDPR, CCPA, HIPAA) relevant to a specific AI use case

• Analyze the risks associated with deploying AI systems, including both compliance and operational risks

• Apply appropriate testing strategies (e.g., sandboxing, A/B testing, safety checks) to evaluate AI system behavior

• Develop a comprehensive AI governance plan that integrates regulations, testing, risk mitigation, and documentation practices

• Create guiding questions that identify key regulatory and implementation considerations in real-world AI healthcare scenarios

• Classify AI use cases using the risk–speed quadrant framework

Module 8: Ethics and Capstone

• Explain how AI can be strategically integrated into organizational functions to create business value

• Evaluate the suitability of AI technologies for specific organizational use cases

• Analyze the cost, security, and operational implications of AI adoption

• Assess the human and organizational factors that influence successful AI implementation

• Synthesize course concepts into a structured approach for organizational AI adoption

• Evaluate ethical risks in a proposed AI system by identifying a potential issue, assessing its business impact, and recommending an appropriate mitigation strategy

Capstone Project The course culminates in a capstone project where participants apply course concepts to evaluate an organizational AI opportunity. They will assess the suitability of AI technologies for a specific use case, analyze the associated business, operational, security, and ethical considerations, and develop a structured approach for responsible AI adoption. The final deliverable includes recommendations for implementation, risk mitigation, and value creation within an organizational context.

You will gain the ability to understand, apply, and scale AI across your organization. This includes evaluating AI opportunities, designing AI-integrated strategies, and developing an executive-ready AI adoption roadmap or presentation supported by real-world use cases and hands-on learning.

This bundle provides a comprehensive learning journey across both generative and agentic AI. While one course focuses on understanding AI capabilities and business applications, the other focuses on deploying AI systems, integrating them into workflows, and driving real organizational impact.

Yes. This bundle includes hands-on projects and real-world applications. You will apply your learning through exercises and capstone projects where you build an AI strategy, adoption roadmap, or executive presentation tailored to your organization.

Applicable taxes will be calculated and added at checkout in accordance with country/state regulations.

This bundle equips you to translate AI from concept to execution. You will learn how to assess business value, integrate AI into existing systems, manage risks and governance, and communicate AI strategies effectively to stakeholders across your organization.