Building Agentic AI Systems for Tech Leaders

Übersicht

Gain the technical skills and strategies to successfully implement agentic AI systems across organizations while navigating challenges and identifying opportunities. With these courses, tech leaders will be able to understand, design, and implement agentic AI systems.

Balancing technical and leadership knowledge, tech leaders can drive innovation and prepare their teams with the advancements in agentic AI workflows and systems.Understand agentic AI architectures and frameworks.Create strategies for managing agentic AI implementation.Build and implement lightweight agentic AI solutions.Understand cloud computing for deploying and managing agents.

Lehrplan

• Introduction to Agentic AI Systems
Definition and characteristics of agentic AI
Overview of applications in various industries
Key benefits and challenges
• Understanding Agentic AI Architectures and Frameworks
Components of agentic AI systems
Common architectures: reactive, deliberative, hybrid
Comparison of popular frameworks
• Designing Agentic AI Systems
Principles of intelligent agent design
Techniques for knowledge representation and reasoning
Developing agent communication protocols
• Strategies for Managing Agentic AI Implementation
Project management for AI system deployment
Stakeholder engagement and communication
Mitigating risks and ethical considerations
• Building Lightweight Agentic AI Solutions
Tools and platforms for rapid development
Practical approaches to prototyping agentic AI
Integrating agents into existing infrastructure
• Cloud Computing for Deploying and Managing Agents
Overview of cloud platforms and services
Deployment strategies for scalability and reliability
Monitoring and maintaining agentic AI in the cloud
• Driving Innovation with Agentic AI
Fostering a culture of AI-driven innovation
Aligning AI solutions with business goals
Case studies of successful agentic AI implementations
• Preparing Teams for Advancements in Agentic AI
Training and upskilling team members
Building cross-functional AI teams
Continuous learning and adaptation strategies
• Course Wrap-Up and Capstone Project
Summary of key learnings
Capstone project: design and implement a prototype agentic AI system
Feedback and next steps for further learning and development

---

Unterrichtet von

Andreas Welsch, David Linthicum, Charlene Li, Sudha Jamthe and Kumaran Ponnambalam

---

Fachgebiete

Computer Science