Intelligent Applications Fundamentals Training Course

Introduction to Artificial Intelligence for Government

• History of AI for government applications
• Definitions and terminology relevant to public sector use
• Comparing AI capabilities with human intelligence in governmental contexts
• Future trends and potential impacts on public sector operations

Machine Learning Basics for Government

• Types of machine learning: supervised, unsupervised, and reinforcement learning for government use cases
• Key ML algorithms applicable to public sector challenges
• ML workflow from data collection to model evaluation in governmental settings

Data Management for Government

• Data collection techniques suitable for public sector operations
• Data cleaning and preprocessing methods for government datasets
• Data analysis and visualization tools for enhancing transparency and accountability

AI in Practice for Government

• Case studies of AI applications in federal, state, and local governments
• Industry-specific AI solutions tailored for public sector needs
• AI integration into consumer products with implications for government services

Ethical Considerations for Government

• AI and job displacement within the public sector workforce
• Bias and fairness in AI systems used by government agencies
• Privacy and security issues related to government data management
• Future of AI ethics in public sector governance

Lab Project for Government

• Python programming assignments focused on governmental datasets
• Data analysis projects using real-world government data
• Development of a simple ML model to address public sector challenges

Summary and Next Steps for Government