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 Duration 14 hours

Course Outline

Foundations of AI Programming

  • Defining AI programming: Key concepts and practical examples
  • AI applications in the public sector: Chatbots, summarizers, and intelligent search
  • Distinguishing AI models from traditional programming logic

Introductory Python for AI

  • Creating your initial Python scripts
  • Utilizing data structures and control logic
  • Essential libraries for AI programming: requests, pandas, and json

Leveraging AI APIs

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

Building Simple AI Tools

  • Developing a document summarizer
  • Prototyping a chatbot for citizen services
  • Automating the labeling of public datasets using AI

Evaluating Outputs and Limitations

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

Compliance, Ethics, and Responsible Development

  • Privacy and explainability standards in government contexts
  • Comparing open-source and proprietary models: advantages and disadvantages
  • A checklist for safe experimentation and scaling up

Summary and Next Steps

Requirements

  • Basic proficiency with spreadsheets or structured data.
  • Familiarity with public sector service delivery or analytical tasks.
  • No prior programming experience is necessary, as introductory Python will be covered.

Target Audience

  • Public servants and analysts exploring the integration of AI into daily operations.
  • Digital government professionals seeking hands-on experience with AI implementation.
  • Government teams focused on innovation, transformation, and research.

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