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Course Outline
Foundations of AI Programming
- What is AI programming? Key concepts and examples
- Public sector applications of AI: chatbots, summarizers, intelligent search
- AI models vs traditional programming logic
Introductory Python for AI
- Writing your first Python scripts
- Working with data structures and control logic
- Libraries for AI programming: requests, pandas, json
Using AI APIs
- What is an API? Accessing AI models securely
- Sending text and structured data to models
- Working with OpenAI, Cohere, or Hugging Face APIs
Creating Simple AI Tools
- Building a document summarizer
- Prototyping a chatbot for citizen services
- Using AI to auto-label public datasets
Evaluating Outputs and Limitations
- Understanding probabilistic AI behavior
- Prompt engineering and managing output quality
- Red-teaming your prototypes for bias and hallucinations
Compliance, Ethics, and Responsible Development
- Privacy and explainability requirements in government
- Open-source vs proprietary models: pros and cons
- Checklist for safe experimentation and scale-up
Summary and Next Steps
Requirements
- Basic experience working with spreadsheets or structured data
- Familiarity with public sector service delivery or analysis tasks
- No prior programming experience required (introductory Python will be covered)
Audience
- Public servants and analysts exploring AI use in daily workflows
- Digital government professionals seeking hands-on skills in AI integration
- Innovation, transformation, and research teams in government
14 Hours
