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.
Duration 14 hours
Course Outline
Introduction to Generative and Agentic AI
- Defining Generative AI and Agentic AI
- Distinctions and synergies between the two paradigms
- Cross-industry applications and emerging trends
Generative AI Architecture and Tooling
- Transformer architectures: GPT, LLaMA, Claude, and others
- Fine-tuning versus in-context learning approaches
- Key tools: ChatGPT, Hugging Face Transformers, and Google AI Studio
Prompt Engineering for Precision and Structure
- Patterns for writing, coding, and summarization tasks
- Few-shot, zero-shot, and chain-of-th prompting techniques
- Leveraging prompt libraries and testing utilities
Concepts in Agentic AI
- Origins and evolution of agentic AI
- Core architectures: planning, memory, tools, and self-reflection
- Leading frameworks: AutoGPT, BabyAGI, CrewAI, and LangGraph
Building and Deploying Autonomous Agents
- Goal definition and task decomposition strategies
- Tool and API integration (search, memory, code execution)
- Multi-agent coordination and human-in-the-loop oversight
Practical Use Cases and Scenarios
- Content generation versus task orchestration
- Enterprise productivity, customer support, and data extraction
- Principles of responsible and secure implementation
Recap and Future Directions
Requirements
- Foundational knowledge of AI and machine learning principles
- Practical experience with APIs or scripting languages like Python
- Familiarity with prompt engineering or the utilization of Large Language Models
Target Audience
- AI developers and engineers
- Innovation and R&D teams
- Technical product managers exploring agentic AI ecosystems
Testimonials (1)
the tips and recommended prompts that we can take away from this training
