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Course Outline

Foundations of AI Programming

  • Defining AI programming: Key concepts and 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.
  • 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 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 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 contexts.
  • Open-source versus proprietary models: Pros and cons.
  • Checklist for safe experimentation and scaling up.

Summary and Next Steps

Requirements

  • Basic experience with spreadsheets or structured data.
  • Familiarity with public sector service delivery or analytical tasks.
  • No prior programming experience 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 agencies.
 14 Hours

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