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 Duration 14 hours

Course Outline

Introduction to Generative Artificial Intelligence and Agentic Systems

  • Definitions of Generative AI and Agentic AI.
  • Distinctions and synergistic capabilities between the two modalities.
  • Applications and emerging trends across public and private sectors.

Generative AI Architectural Frameworks and Toolsets

  • Transformer-based models, including GPT, LLaMA, and Claude.
  • Methodologies: Fine-tuning versus in-context learning.
  • Key platforms: ChatGPT, Hugging Face Transformers, and Google AI Studio.

Prompt Engineering for Governance and Structural Control

  • Prompting strategies for composition, code generation, and summarization.
  • Techniques: Few-shot, zero-shot, and chain-of-thought approaches.
  • Leveraging prompt libraries and evaluation testing instruments.

Conceptual Foundations of Agentic AI

  • Definition and evolutionary trajectory of agentic systems.
  • Core architectures: Planning mechanisms, memory retention, tool utilization, and self-reflective loops.
  • Leading frameworks: AutoGPT, BabyAGI, CrewAI, and LangGraph.

Design and Deployment of Autonomous Agents

  • Objective formulation and task decomposition strategies.
  • Integration of external tools and APIs for search, memory, and code execution.
  • Coordination among multiple agents and human-in-the-loop oversight mechanisms.

Operational Use Cases and Implementation Scenarios

  • Differentiating content generation from complex task orchestration.
  • Applications in enterprise productivity, customer service, and data extraction.
  • Ensuring responsible, secure, and compliant implementation for government operations.

Summary and Forward-Looking Recommendations

Requirements

  • A foundational understanding of artificial intelligence and machine learning principles.
  • Practical experience with API interactions or scripting languages, such as Python.
  • Working knowledge of prompt engineering or the utilization of large language models.

Target Audience

  • AI developers and systems engineers.
  • Innovation and Research and Development (R&D) personnel.
  • Technical product managers evaluating agentic AI systems for government applications.

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