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Course Outline

Fundamentals of AI Programming

  • Defining AI programming: core concepts and real-world examples.
  • Applications in the public sector: chatbots, summarizers, and intelligent search.
  • Comparing AI models with traditional programming logic.

Introductory Python for AI

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

Interacting with AI APIs

  • Understanding APIs: secure access to AI models.
  • Inputting text and structured data into models.
  • Utilizing APIs from OpenAI, Cohere, or Hugging Face.

Developing Basic AI Tools

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

Assessing Outputs and Limitations

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

Compliance, Ethics, and Responsible Development

  • Privacy and explainability mandates in government.
  • Open-source vs proprietary models: advantages and disadvantages.
  • A checklist for safe experimentation and scaling.

Wrap-up and Future Directions

Requirements

  • Foundational experience with spreadsheets or structured data.
  • Knowledge of public sector service delivery or analytical tasks.
  • No prior programming background is necessary; introductory Python will be provided.

Target Audience

  • Public servants and analysts looking to apply AI in their daily routines.
  • Digital government professionals aiming to acquire hands-on AI integration skills.
  • Government teams focused on innovation, transformation, and research.
 14 Hours

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