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Course Outline

Foundations of AI Programming

  • What is AI programming? Key concepts and examples.
  • Public sector applications of AI: chatbots, summarizers, intelligent search.
  • AI models versus traditional programming logic.

Introductory Python for AI

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

Using AI APIs

  • What is an API? Accessing AI models securely.
  • Sending text and structured data to models.
  • Working with OpenAI, Cohere, or Hugging Face APIs.

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 probabilistic AI behavior.
  • Prompt engineering and managing output quality.
  • Red-teaming your prototypes for bias and hallucinations.

Compliance, Ethics, and Responsible Development

  • Privacy and explainability requirements in government.
  • Open-source versus proprietary models: pros and cons.
  • Checklist for safe experimentation and scale-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 daily workflows.
  • Digital government professionals seeking hands-on skills in AI integration.
  • Innovation, transformation, and research teams within government.
 14 Hours

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