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Course Outline

Foundations of AI Programming

  • What is AI programming? Key concepts and real-world examples
  • Public sector applications of AI: chatbots, summarizers, and intelligent search
  • Differences between AI models and traditional programming logic

Introductory Python for AI

  • Writing your first Python scripts
  • Working with data structures and control logic
  • Essential libraries for AI programming: requests, pandas, json

Using AI APIs

  • Understanding APIs and securely accessing AI models
  • Sending text and structured data to AI models
  • Working with APIs from OpenAI, Cohere, or Hugging Face

Creating Simple AI Tools

  • Building a document summarizer
  • Prototyping a chatbot for citizen services
  • Using AI to auto-label public datasets

Evaluating Outputs and Limitations

  • Understanding the probabilistic nature of AI behavior
  • Prompt engineering and managing output quality
  • Red-teaming your prototypes to identify bias and hallucinations

Compliance, Ethics, and Responsible Development

  • Privacy and explainability requirements in government contexts
  • Open-source vs proprietary models: pros and cons
  • Checklist for safe experimentation and scaling up

Summary and Next Steps

Requirements

  • Basic experience working with spreadsheets or structured data
  • Familiarity with public sector service delivery or analysis tasks
  • No prior programming experience is required (introductory Python will be covered)

Audience

  • Public servants and analysts exploring the use of AI in their daily workflows
  • Digital government professionals seeking hands-on skills in AI integration
  • Innovation, transformation, and research teams within government organizations
 14 Hours

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