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Course Outline

Foundations of AI Programming

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

Introductory Python for AI

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

Using AI APIs

  • Understanding APIs and securely accessing AI models.
  • Sending text and structured data to AI models.
  • Working with APIs from OpenAI, Cohere, or Hugging Face.

Creating Simple AI Tools

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

Evaluating Outputs and Limitations

  • Understanding the probabilistic nature of AI behavior.
  • Prompt engineering techniques and managing output quality.
  • Testing prototypes for bias and hallucinations.

Compliance, Ethics, and Responsible Development

  • Privacy and explainability requirements in government contexts.
  • Open-source vs. proprietary models: Advantages and disadvantages.
  • Checklist for safe experimentation and scaling up AI projects.

Summary and Next Steps

Requirements

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

Audience

  • Public servants and analysts looking to explore AI integration into their daily workflows.
  • Digital government professionals seeking practical skills in AI implementation.
  • Innovation, transformation, and research teams within government agencies.
 14 Hours

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