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Course Outline

AI Programming Foundations

  • 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

Introduction to Python for AI

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

Utilizing AI APIs

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

Building Simple AI Tools

  • Creating 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 and managing output quality
  • Testing prototypes for bias and hallucinations

Compliance, Ethics, and Responsible Development

  • Privacy and transparency requirements in government contexts
  • Open-source versus proprietary models: advantages and disadvantages
  • Checklist for safe experimentation and scaling up

Summary and Next Steps

Requirements

  • Basic experience using spreadsheets or working with structured data
  • Familiarity with public sector service delivery or analytical tasks
  • No prior programming experience is necessary (introductory Python will be taught)

Target Audience

  • Public servants and analysts exploring the use of AI in their daily work
  • Digital government professionals looking to gain hands-on AI integration skills
  • Government innovation, transformation, and research teams
 14 Hours

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