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Course Outline

Basics of AI Coding

  • Definition of AI coding: main ideas and real-world examples
  • AI uses in the public sector: chatbots, summarizing tools, smart search
  • AI models compared to standard coding logic

Beginner Python for AI

  • Creating your first Python scripts
  • Handling data structures and logic controls
  • Useful AI coding libraries: requests, pandas, json

Working with AI APIs

  • Understanding APIs: accessing AI models safely
  • Passing text and structured data to models
  • Using OpenAI, Cohere, or Hugging Face APIs

Building Simple AI Tools

  • Developing a document summarizer
  • Creating a chatbot prototype for citizen services
  • Using AI to automatically tag public datasets

Assessing Results and Limits

  • Grasping the unpredictable nature of AI
  • Prompt engineering and controlling output quality
  • Testing prototypes for bias and hallucinations

Compliance, Ethics, and Safe Development

  • Privacy and transparency needs in government
  • Open-source vs. proprietary models: advantages and disadvantages
  • Checklist for safe testing and expansion

Recap and Future Steps

Requirements

  • Basic knowledge of using spreadsheets or handling structured data
  • Some familiarity with public sector service delivery or analytical tasks
  • No previous coding experience is needed (beginner Python will be taught)

Intended Participants

  • Public sector employees and analysts looking to use AI in their everyday work
  • Digital government specialists aiming to gain practical AI integration skills
  • Government teams focused on innovation, transformation, and research
 14 Hours

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