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Course Outline
Basics of AI Programming
- Defining AI programming: core concepts and examples
- AI applications in the public sector: chatbots, summarizers, and intelligent search
- AI models compared to traditional programming logic
Introductory Python for AI
- Creating your first Python scripts
- Utilizing data structures and control logic
- Essential libraries for AI coding: requests, pandas, json
Utilizing AI APIs
- Understanding APIs: Securely accessing AI models
- Sending text and structured data to models
- Interfacing with OpenAI, Cohere, or Hugging Face APIs
Developing Simple AI Tools
- Constructing a document summarizer
- Prototyping a chatbot for citizen services
- Applying AI to automatically label public datasets
Assessing Outputs and Limitations
- Understanding probabilistic AI behavior
- Prompt engineering and managing output quality
- Red-teaming prototypes to identify bias and hallucinations
Compliance, Ethics, and Responsible Development
- Privacy and explainability standards in government
- Open-source versus proprietary models: advantages and disadvantages
- A checklist for safe experimentation and scaling up
Recap and Future Directions
Requirements
- Basic proficiency in working with spreadsheets or structured data
- Knowledge of public sector service delivery or analytical tasks
- No prior coding experience is necessary (introductory Python concepts will be taught)
Target Audience
- Public servants and analysts interested in incorporating AI into their daily tasks
- Digital government professionals looking to acquire hands-on 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.
