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Course Outline

Introduction

Overview of Artificial Intelligence (AI)

  • Machine learning systems for government

Exploring Applications for AI in Government

  • AI in the corporate context and its relevance for government operations

Learning About the Technology of AI for Government

  • Concepts of underfitting, overfitting, classification, and regularization
  • Multi-layer perception (MLP) and deep learning techniques for government applications
  • Convolutional and recurrent neural networks in governmental contexts

Assessing Strategic Approaches for Government AI Projects

  • Commissioning or procurement decisions (build versus buy) for government initiatives
  • AI maturity models tailored for government organizations

Working With Data in Your Government Organization

  • Evaluating data readiness for AI projects in government
  • Utilizing word embeddings in governmental datasets
  • Training with artificial data for government applications

Assessing AI Project Selection for Government

  • Key criteria for selecting AI projects in the public sector

Managing an AI Project for Government

  • Differentiating between machine learning and deep learning approaches in government contexts
  • Project management methodologies, lifecycle stages, and timescales for government AI projects
  • Operations, maintenance, and risk management strategies for government AI initiatives

Gathering Feedback on Government AI Projects

  • Implementing feedback methods such as surveys and interviews for government AI projects
  • Identifying key stakeholders who will provide feedback in the public sector
  • Analyzing feedback results to inform continuous improvement in government AI initiatives

Summary and Next Steps for Government AI Initiatives

Requirements

  • No prerequisites required

Audience

  • Business leaders for government and private sectors
  • Project managers for government and private sectors
 14 Hours

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