Course Outline

Introduction

Overview of Artificial Intelligence (AI)

  • Machine learning systems for government

Exploring Applications for AI in the Public Sector

  • AI applications in corporate contexts and their relevance for government operations

Learning About the Technology of AI

  • Concepts such as underfitting, overfitting, classification, and regularization for government use cases
  • Multi-layer perceptrons (MLP) and deep learning techniques for government applications
  • Convolutional and recurrent neural networks for enhancing public sector operations

Assessing Strategic Approaches for Government AI Implementation

  • Commissioning or procurement decisions: build versus buy considerations for government
  • AI maturity models tailored for government organizations

Working With Data in Your Government Organization

  • Evaluating data readiness for AI projects in the public sector
  • Utilizing word embeddings to enhance data analysis for government
  • Training with artificial data to improve AI models for government use

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 for government applications
  • Project management considerations, including lifecycle, timescales, and methodologies for government 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 on government AI initiatives
  • Analyzing feedback results to inform continuous improvement in government AI programs

Summary and Next Steps for Government AI Initiatives

Requirements

  • No prerequisites required

Audience

  • Business leaders for government
  • Project managers
 14 Hours

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