Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Course Outline
Introduction to Generative AI and Agentic AI
- Defining Generative AI and Agentic AI
- Analyzing the differences and synergies between the two
- Key use cases and emerging industry trends
Generative AI Architecture and Tools
- Exploration of Transformer models: GPT, LLaMA, Claude, and others
- Distinguishing between fine-tuning and in-context learning
- Overview of key tools: ChatGPT, Hugging Face Transformers, and Google AI Studio
Prompt Engineering for Control and Structure
- Developing prompt patterns for writing, coding, summarization, and more
- Techniques including few-shot, zero-shot, and chain-of-thought prompting
- Leveraging prompt libraries and testing utilities
Understanding Agentic AI
- Tracing the definition and evolution of agentic AI
- Examining core architectures: planning, memory, tools, and self-reflection
- Review of popular frameworks: AutoGPT, BabyAGI, CrewAI, and LangGraph
Designing and Deploying Autonomous Agents
- Strategies for goal setting and task decomposition
- Integrating external tools and APIs (search, memory, code execution)
- Managing multi-agent coordination and human-in-the-loop supervision
Use Cases and Implementation Scenarios
- Differentiating content generation from task orchestration
- Applications in enterprise productivity, customer support, and data extraction
- Best practices for responsible and secure implementation
Summary and Next Steps
Requirements
- A foundational understanding of AI and machine learning principles
- Practical experience with APIs or scripting languages, such as Python
- Working knowledge of prompt engineering or the usage of large language models
Target Audience
- AI developers and engineers
- Innovation and R&D teams
- Technical product managers seeking to explore agentic AI systems
14 Hours
Testimonials (1)
the tips and recommended prompts that we can take away from this training
