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Course Outline
Foundations of AI Programming
- Defining AI programming: Key concepts and illustrative examples
- Applications of AI in the public sector: chatbots, summarizers, and intelligent search
- Comparing AI models with traditional programming logic
Introductory Python for AI
- Developing your first Python scripts
- Navigating data structures and control logic
- 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
- Utilizing OpenAI, Cohere, or Hugging Face APIs
Developing Simple AI Tools
- Constructing a document summarizer
- Prototyping a chatbot for citizen services
- Automating the labelling of public datasets using AI
Assessing Outputs and Limitations
- Comprehending the probabilistic nature of AI behaviour
- Prompt engineering and monitoring output quality
- Red-teaming prototypes to identify bias and hallucinations
Compliance, Ethics, and Responsible Development
- Privacy and explainability mandates within government
- Open-source vs proprietary models: advantages and disadvantages
- Checklist for safe experimentation and scaling up
Conclusion and Future 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 concepts will be covered
Target Audience
- Public servants and analysts investigating the integration of AI in daily operations
- Digital government professionals seeking practical skills in AI implementation
- 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.
