The Course on Generative AI Agents It is your gateway to a world of ever-growing innovation. Today, generative artificial intelligence agents are revolutionising sectors such as data analysis and process automation. With demand for skilled workers on the rise, acquiring skills in this field puts you at the cutting edge of technology. This online course offers you a comprehensive understanding of the large-scale language models and their application in conversational agents, as well as the design and development of generative agents for digital environments. You will also explore the ethics and safety, issues that are crucial to the responsible use of AI.
Cross-cutting
AI Academy
40 hours
Generative AI Agents
AI Academy
40 hours
Introduction
Objectives
- Understand the key concepts of generative AI agents. - Identify the differences between generative models and intelligent agents. - Analyse current use cases and future trends in generative AI. - Evaluate large-scale language models and their practical application. - Design effective prompts for generative agents. - Integrate AI agents into various digital environments. - Examine the ethical and social risks of autonomous agents.
Table of Contents
TEACHING UNIT 1. INTRODUCTION TO GENERATIVE AI AGENTS
Concept and definition of generative AI agents
Historical development: from expert systems to autonomous agents
Differences between generative models and intelligent agents
Key components of an AI agent
Current use cases and future trends
TEACHING UNIT 2. FUNDAMENTALS OF GENERATIVE AI
Large-scale language models (LLMs)
Generative models: text, image, audio and multimodality
Model training, fine-tuning and alignment
Prompting and control of generation
Technical limitations and inherent risks
TEACHING UNIT 3. ARCHITECTURE OF AI AGENTS
The internal structure of an agent (perception, reasoning and action)
Short- and long-term memory in agents
Planning and decision-making
Tools and the use of external APIs
Orchestration of workflows and execution cycles
TEACHING UNIT 4. DESIGN AND DEVELOPMENT OF GENERATIVE AGENTS
Definition of the agent’s objectives and roles
Design of prompts and instruction systems
Integration of agents with digital environments
State and Persistence Management
Testing, validation and iterative improvement
TEACHING UNIT 5. AUTONOMOUS AGENTS AND MULTI-AGENT SYSTEMS
The concept of autonomy in AI agents
Multi-agent systems and cooperation
Communication between agents
Conflict resolution and coordination
Examples of multi-agent frameworks and platforms
TEACHING UNIT 6. PRACTICAL APPLICATIONS OF GENERATIVE AI AGENTS
Conversational agents and virtual assistants
Process automation agents
Creative professionals (content, design, programming)
Tools for data analysis and decision-making
Case studies in various sectors
TEACHING UNIT 7. ETHICS, SECURITY AND GOVERNANCE OF AI AGENTS
Ethical and social risks associated with autonomous agents
Cognitive biases, hallucinations and behaviour control
Privacy and data protection
Safety, alignment and human supervision
Regulatory frameworks and best practice
TEACHING UNIT 8. THE FUTURE OF GENERATIVE AI AGENTS
Generalist agents vs. specialist agents
Integration with robotics and physical environments
Impact on work and education
Current research and emerging trends
Long-term technological and social challenges
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