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 Duration 14 hours

Course Outline

AI Programming Fundamentals

  • Defining AI programming: core concepts and illustrative examples
  • Public sector AI applications: chatbots, content summarizers, and intelligent search engines
  • Contrasting AI models with traditional programming logic

Introductory Python for AI Applications

  • Composing initial Python scripts
  • Managing data structures and control flow logic
  • Exploring key libraries for AI programming: requests, pandas, and json

Integrating AI APIs

  • Understanding APIs and securely accessing AI models
  • Transmitting text and structured data to AI models
  • Utilizing APIs from OpenAI, Cohere, or Hugging Face

Developing Basic AI Tools

  • Constructing a document summarization tool
  • Designing a chatbot prototype for citizen services
  • Applying AI to automatically label public datasets

Assessing Output Quality and Limitations

  • Comprehending the probabilistic nature of AI behavior
  • Mastering prompt engineering to manage output quality
  • Conducting red-teaming exercises to identify bias and hallucinations in prototypes

Compliance, Ethics, and Responsible Development

  • Meeting privacy and explainability requirements within government frameworks
  • Comparing open-source and proprietary models: advantages and disadvantages
  • Establishing a checklist for safe experimentation and scalable deployment

Recap and Future Steps

Requirements

  • Foundational experience working with spreadsheets or structured data
  • Basic familiarity with public sector service delivery or analytical tasks
  • No prior programming background is necessary, as introductory Python concepts will be taught

Target Audience

  • Public servants and analysts investigating AI integration into daily operations
  • Digital government professionals looking to acquire hands-on AI integration skills
  • Government teams focused on innovation, transformation, and research

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