Course Outline

Introduction to Generative AI for Government

  • Defining generative artificial intelligence (AI)
  • Overview of generative models, including Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs)
  • Applications and case studies for government

The Need for Synthetic Data in Government Operations

  • Limitations of real data in public sector applications
  • Privacy and security concerns for government agencies
  • Enhancing AI model robustness and reliability for government use

Generating Synthetic Data for Government Use

  • Techniques for synthetic data generation in the public sector
  • Ensuring data quality and diversity for government applications
  • Practical workshop: Creating your first synthetic dataset for government

Evaluating Synthetic Data for Government

  • Metrics for assessing the quality of synthetic data in government contexts
  • Comparing the performance of synthetic versus real data for government operations
  • Case study analysis for government applications

Ethical and Legal Aspects for Government Use

  • Navigating the ethical landscape in government AI initiatives
  • Legal frameworks and compliance for synthetic data use in government
  • Balancing innovation with responsibility in government operations

Advanced Topics in Data Synthesis for Government

  • Synthetic data for unsupervised learning in government applications
  • Cross-domain data synthesis for government use
  • Future trends in generative AI for government operations

Capstone Project for Government

  • Applying knowledge to real-world scenarios in the public sector
  • Developing a synthetic data strategy for government agencies
  • Assessment and feedback for government professionals

Summary and Next Steps for Government AI Initiatives

Requirements

  • An understanding of fundamental machine learning concepts for government applications.
  • Experience with Python programming in a governmental context.
  • Familiarity with data science workflows and methodologies for government use.

Audience

  • Data scientists working in the public sector.
  • AI practitioners supporting government initiatives.
 21 Hours

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