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Course Outline

Basics of AI Programming

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

Python Basics for AI Applications

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

Leveraging AI APIs

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

Building Basic AI Tools

  • Constructing a document summarizer
  • Prototyping a chatbot for citizen services
  • Automating the labeling of public datasets using AI

Assessing Output Quality and Limitations

  • Understanding the probabilistic nature of AI behavior
  • Prompt engineering techniques and managing output quality
  • Red-teaming prototypes to identify bias and hallucinations

Compliance, Ethics, and Responsible Development

  • Privacy and explainability requirements in the government context
  • Open-source versus proprietary models: Advantages and disadvantages
  • Checklist for safe experimentation and scaling up

Recap and Future Steps

Requirements

  • Basic familiarity with spreadsheets or working with structured data.
  • Experience with public sector service delivery or analytical tasks.
  • No prior programming background is necessary, as introductory Python concepts will be covered.

Target Audience

  • Public servants and analysts looking to integrate AI into their daily routines.
  • Digital government specialists seeking practical skills in AI integration.
  • Government teams focused on innovation, transformation, and research.
 14 Hours

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