Generative AI and Agentic AI Training Course
Generative AI and Agentic AI represent two distinct yet powerful paradigms that are propelling the next generation of automation and intelligent systems. While one focuses on creating new content, the other is dedicated to achieving goals through autonomous behavior.
This instructor-led live training, available both online and onsite, is designed for AI professionals and technical specialists at an intermediate level. It aims to equip them with the knowledge required to build, evaluate, and integrate generative and agentic AI solutions into practical applications.
Upon completing this training, participants will be able to:
- Grasp the architecture and capabilities of generative AI systems.
- Explore the emergence of autonomous AI agents and their ability to extend Large Language Models (LLMs).
- Apply prompt engineering and tool integrations for effective deployments.
- Evaluate different models, tools, and techniques to ensure responsible deployment.
Course Format
- Interactive lectures and group discussions.
- Practical application of generative and agentic AI tools in real-world scenarios.
- Guided exercises centered on content generation and autonomous workflows.
Customization Options
- To request a customized version of this course, please contact us to arrange it.
Course Outline
Introduction to Generative AI and Agentic AI
- Definitions: What is Generative AI? What is Agentic AI?
- Key differences and how they complement each other.
- Use cases and industry trends.
Generative AI Architecture and Tools
- Transformer models: GPT, LLaMA, Claude, and others.
- Fine-tuning versus in-context learning.
- Tools: ChatGPT, Hugging Face Transformers, Google AI Studio.
Prompt Engineering for Control and Structure
- Prompt patterns for writing, coding, summarization, and more.
- Few-shot, zero-shot, and chain-of-thought prompting techniques.
- Utilizing prompt libraries and testing tools.
Understanding Agentic AI
- Definition and evolution of agentic AI.
- Architectures: planning, memory, tools, and self-reflection.
- Popular frameworks: AutoGPT, BabyAGI, CrewAI, LangGraph.
Designing and Deploying Autonomous Agents
- Goal setting and task decomposition.
- Integrating tools and APIs (search, memory, code).
- Multi-agent coordination and human-in-the-loop supervision.
Use Cases and Implementation Scenarios
- Content generation versus task orchestration.
- Enterprise productivity, customer support, and data extraction.
- Responsible and secure implementation practices.
Summary and Next Steps
Requirements
- A foundational understanding of AI and machine learning concepts.
- Experience working with APIs or scripting languages such as Python.
- Familiarity with prompt engineering or the usage of Large Language Models.
Audience
- AI developers and engineers.
- Innovation and R&D teams.
- Technical product managers exploring agentic AI systems.
Custom Corporate Training
Training solutions designed exclusively for businesses.
- Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
- Flexible Schedule: Dates and times adapted to your team's agenda.
- Format: Online (live), In-company (at your offices), or Hybrid.
Price per private group, online live training, starting from 3200 € + VAT*
Contact us for an exact quote and to hear our latest promotions
(*The final price may vary depending on the technical specialization of the course, the level of customization, the method of delivery and the number of learners)
Need help picking the right course?
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