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 Duration 14 hours

Course Outline

Foundations of AI Programming

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

Introductory Python for AI

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

Working with AI APIs

  • Understanding APIs: Securely accessing AI models.
  • Transmitting text and structured data to models.
  • Interacting with OpenAI, Cohere, or Hugging Face APIs.

Creating Simple AI Tools

  • Developing a document summarizer.
  • Prototyping a chatbot for citizen services.
  • Applying AI to auto-label public datasets.

Evaluating Outputs and Limitations

  • Understanding probabilistic 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 vs. proprietary models: Advantages and disadvantages.
  • Checklists 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 analysis tasks.
  • No prior programming experience is necessary (introductory Python concepts will be taught).

Target Audience

  • Public servants and analysts looking to integrate AI into daily workflows.
  • Digital government professionals seeking hands-on skills in AI integration.
  • Innovation, transformation, and research teams within the government.

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