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Course Outline
Foundations of AI Programming
- Defining AI programming: key concepts and real-world examples.
- Applications in the public sector: chatbots, summarizers, and intelligent search.
- Comparing AI models with traditional programming logic.
Introductory Python for AI
- Creating your first Python scripts.
- Managing data structures and control logic.
- Essential libraries for AI programming: requests, pandas, json.
Utilizing AI APIs
- Understanding APIs: securely accessing AI models.
- Transmitting text and structured data to models.
- Interacting with OpenAI, Cohere, or Hugging Face APIs.
Building Simple AI Tools
- Developing a document summarizer.
- Prototyping a chatbot for citizen services.
- Applying AI to automatically label public datasets.
Assessing Outputs and Limitations
- Comprehending probabilistic AI behavior.
- Prompt engineering and maintaining output quality.
- Red-teaming prototypes to identify bias and hallucinations.
Compliance, Ethics, and Responsible Development
- Privacy and explainability standards in government.
- Open-source vs proprietary models: advantages and drawbacks.
- Guidelines for safe experimentation and scaling.
Conclusion and Next Steps
Requirements
- Basic experience handling spreadsheets or structured data.
- Familiarity with public sector service delivery or analytical tasks.
- No prior programming background is necessary; introductory Python will be taught.
Target Audience
- Public servants and analysts exploring AI integration in daily workflows.
- Digital government professionals seeking practical AI integration skills.
- 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.