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Course Outline

Fundamentals of AI Programming

  • Defining AI programming: core concepts and illustrative examples
  • AI applications in the public sector: chatbots, summarizers, and intelligent search
  • AI models compared to traditional programming logic

Python Basics for AI

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

Leveraging AI APIs

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

Developing Basic AI Tools

  • Constructing a document summarizer
  • Prototyping a chatbot for citizen services
  • Utilizing AI to automatically label public datasets

Assessing Outputs and Constraints

  • Comprehending probabilistic AI behavior
  • Prompt engineering and monitoring output quality
  • Red-teaming prototypes to identify bias and hallucinations

Compliance, Ethics, and Responsible Development

  • Privacy and explainability standards in the government sector
  • Open-source versus proprietary models: advantages and disadvantages
  • Checklists for secure experimentation and scaling

Wrap-Up and Future Steps

Requirements

  • Basic proficiency with spreadsheets or structured data
  • Familiarity with public sector service delivery or analytical tasks
  • No previous coding experience is necessary; introductory Python will be taught

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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