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Duration 14 hours
Course Outline
Foundations of AI Programming
- 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 initial Python scripts
- Working with data structures and control logic
- Essential libraries for AI programming: requests, pandas, and json
Utilizing AI APIs
- Understanding APIs: Securely accessing AI models
- Transmitting text and structured data to models
- Interfacing with OpenAI, Cohere, or Hugging Face APIs
Developing Basic AI Tools
- Constructing a document summarizer
- Prototyping a chatbot for citizen services
- Employing AI to automatically label public datasets
Assessing Outputs and Limitations
- Understanding the probabilistic nature of AI behavior
- Prompt engineering and controlling output quality
- Red-teaming prototypes to identify bias and hallucinations
Compliance, Ethics, and Responsible Development
- Privacy and explainability standards in government contexts
- Open-source versus proprietary models: Advantages and drawbacks
- Checklist for safe experimentation and scaling
Summary and Next Steps
Requirements
- Basic proficiency in working with spreadsheets or structured data
- Familiarity with public sector service delivery or analytical tasks
- No prior programming experience is required, as introductory Python will be covered
Target 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
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.