Generative and Agentic AI

Übersicht

Explore cutting-edge generative AI and autonomous agents, mastering LLMs, prompt engineering, RAG, and responsible deployment strategies for business transformation.

Lehrplan

• Introduction to Generative AI and Autonomous Agents
Overview of generative AI technologies
Introduction to autonomous agents and their applications
• Large Language Models (LLMs)
Understanding LLM architectures (e.g., GPT, BERT)
Use cases and applications of LLMs in business
• Prompt Engineering
Principles of effective prompt design
Techniques for optimizing prompt outcomes
Practical exercises in prompt crafting
• Retrieval-Augmented Generation (RAG)
RAG architectures and workflows
Integrating external knowledge sources
Implementing RAG in real-world applications
• Autonomous Agents
Designing and building intelligent agents
Agent communication protocols and frameworks
Case studies of autonomous agent deployment
• Responsible AI Deployment Strategies
Ethical considerations in AI applications
Mitigating biases and ensuring fairness
Compliance with legal and regulatory standards
• Business Transformation through Generative AI and Autonomous Agents
Identifying impactful AI transformation opportunities
Strategies for implementing AI in various business sectors
Measuring and evaluating AI-driven transformation outcomes
• Course Conclusion and Future Trends
Overview of emerging trends in generative AI and agents
Future challenges and opportunities in AI advancements
• Final Project or Assessment
Develop a generative AI or autonomous agent solution for a real-world business challenge
Present and discuss implementation strategies and potential impacts

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Fachgebiete

Computer Science