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Course Outline

Foundations of AI Programming

  • Defining AI programming: Key concepts and illustrative examples
  • Public sector AI applications: chatbots, summarizers, and intelligent search
  • Comparison of AI models and traditional programming logic

Introductory Python for AI

  • Writing initial Python scripts
  • Managing data structures and control logic
  • Essential libraries for AI programming: requests, pandas, json

Utilizing AI APIs

  • Understanding APIs: Secure access to AI models
  • Transmitting text and structured data to models
  • Working with APIs from OpenAI, Cohere, or Hugging Face

Developing Simple AI Tools

  • Constructing a document summarizer
  • Prototyping a chatbot for citizen services
  • Employing AI to automatically label public datasets

Evaluating Outputs and Limitations

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

Compliance, Ethics, and Responsible Development

  • Privacy and explainability requirements in government settings
  • Open-source versus proprietary models: advantages and disadvantages
  • Checklist for safe experimentation and scaling up

Summary and Next Steps

Requirements

  • Fundamental experience working with spreadsheets or structured data
  • Familiarity with public sector service delivery or analytical tasks
  • No prior programming experience is necessary (introductory Python will be included)

Target Audience

  • Public servants and analysts exploring AI integration in daily workflows
  • Digital government professionals seeking practical skills in AI implementation
  • Innovation, transformation, and research teams within the government
 14 Hours

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