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Course Outline
Foundations of AI Programming
- Defining AI programming: key concepts and real-world examples
- AI applications in the public sector, including chatbots, summarizers, and intelligent search
- Distinguishing AI models from traditional programming logic
Introductory Python for AI
- Writing your first Python scripts
- Managing data structures and control logic
- Essential libraries for AI programming: requests, pandas, and json
Using AI APIs
- Understanding APIs and accessing AI models securely
- Transmitting 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
- Leveraging AI to automatically label public datasets
Evaluating Outputs and Limitations
- Understanding the probabilistic nature of AI behaviour
- Prompt engineering techniques for managing output quality
- Red-teaming prototypes to identify bias and hallucinations
Compliance, Ethics, and Responsible Development
- Privacy and explainability requirements within government
- Comparing open-source and proprietary models: advantages and disadvantages
- A checklist for safe experimentation and scaling
Summary and Next Steps
Requirements
- Basic experience working with spreadsheets or structured data
- Familiarity with public sector service delivery or analytical tasks
- No prior programming experience is necessary, as introductory Python will be covered
Audience
- Public servants and analysts looking to integrate AI into their daily workflows
- Digital government professionals seeking practical skills in AI integration
- Government teams focused on innovation, transformation, and research
14 Hours
Testimonials (1)
I got to learn more about Microsoft Copilot, something that I thought was the same as chatGPT but I got to discover more exciting options that I will forever use to make my life easy.
