Get in Touch

Course Outline

Introduction to Generative AI and Agentic AI

  • Defining Generative AI and Agentic AI
  • Key differences and synergies between the two
  • Industry use cases and emerging trends

Generative AI Architecture and Tools

  • Transformer models: GPT, LLaMA, Claude, and others
  • Fine-tuning versus in-context learning
  • Key tools: ChatGPT, Hugging Face Transformers, Google AI Studio

Prompt Engineering for Control and Structure

  • Prompt patterns for writing, coding, summarization, and more
  • Techniques: Few-shot, zero-shot, and chain-of-thought prompting
  • Utilizing prompt libraries and testing utilities

Understanding Agentic AI

  • Definition and evolution of agentic AI
  • Core architectures: planning, memory, tools, and self-reflection
  • Leading frameworks: AutoGPT, BabyAGI, CrewAI, LangGraph

Designing and Deploying Autonomous Agents

  • Defining goals and decomposing tasks
  • Integrating tools and APIs (search, memory, code execution)
  • Multi-agent coordination and human-in-the-loop oversight

Use Cases and Implementation Scenarios

  • Content generation compared to task orchestration
  • Applications in enterprise productivity, customer support, and data extraction
  • Ensuring responsible and secure implementation

Summary and Next Steps

Requirements

  • Foundational knowledge of AI and machine learning concepts
  • Hands-on experience with APIs or scripting languages like Python
  • Familiarity with prompt engineering or the use of large language models

Target Audience

  • AI developers and engineers
  • Innovation and Research & Development (R&D) teams
  • Technical product managers interested in exploring agentic AI systems
 14 Hours

Number of participants


Price per participant

Upcoming Courses

Related Categories