C4DT Course for Decision-Makers: Agentic AI Unveiled: Myth, Reality, and Trust
Introduction
Agentic AI—capable of autonomously handling tasks, coordinating
workflows, and interacting with people and systems—continues to
transform how organizations operate.
Unlock the potential of agentic AI with our course, “Agentic AI Unveiled: Myth, Reality, and Trust.” Designed specifically for decision makers, this 2.75-hour program provides a clear and comprehensive overview of AI agents, their functionalities, and their impact. You’ll gain insights into the operational challenges, ethical considerations, and security issues surrounding AI agents, all explained in an accessible and engaging manner. This course empowers you to make informed decisions about AI technologies, ensuring you understand the key concepts without needing a technical background.
Who should attend?
- Professionals seeking a straightforward overview of Agentic AI
- Managers guiding AI projects and transformations
Course curriculum
- Demo: Observe a live demonstration showcasing key components
and functionalities of Agentic AI - Agentic AI landscape: Understand Agentic AI and recognize their
opportunities and limitations - Technical and operational considerations: Articulate issues related to
integration, data management and scalability - Legal compliance: Review relevant legal frameworks and regulations
concerning AI - Security: Explore cybersecurity issues specifically related to AI
- Ethics: Address ethical aspects that are vital to building trust and
ensuring societal acceptance
Syllabus
| Topic | Description | Key words | Time [min] |
| Demo | Discover the AI agent components and functioning via a demo | LLM, roles, tools, guardrails, multi agent architecture (sequentially, hierarchically, asynchronously), memory | 30 |
| Intro | Understand AI agents, and recognize their opportunities and limitations | Tasks, processes, workflow, agentic collaboration, architecture, tools, multi model, use cases | 30 |
| Technical and operational challenges | Articulate issues related to integration, data management and scalability | Robust structure, legacy infrastructures, integration issues, complexity, outdated software and APIs, data formats, data management, ontology-based communication, data scarcity, data quality, overfitting, underfitting, performance, critical applications, scalability, maintenance, cost management | 30 |
| Ethical and social challenges | Address Ethical challenges that are vital to building trust and ensuring societal acceptance | Trust, societal acceptance, transparency, explainability, interpretable models, accountability, strategic reasoning, attention mechanisms, bias, fairness, biased datasets, societal inequities, fairness audits, training processes, civil liberties, ethical frameworks, governance standards, decision-making processes, human-AI collaboration, human-in-the-loop systems, workforce transition | 45 |
| Security challenges | Explore cyber security issues specifically related to AI | security vulnerabilities, adversarial attacks, model poisoning, inference attacks critical applications, mitigation strategies | 30 |
| Total [hour] | 2.75 |
For more information: contact Alexandre Fawal