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Duration 14 hours
Course Outline
Foundations of AI Programming
- Defining AI programming: Key concepts and practical examples
- AI applications in the public sector: Chatbots, summarizers, and intelligent search
- Distinguishing AI models from traditional programming logic
Introductory Python for AI
- Creating your initial Python scripts
- Utilizing data structures and control logic
- Essential libraries for AI programming: requests, pandas, and json
Leveraging AI APIs
- Understanding APIs: Secure access to AI models
- Transmitting text and structured data to models
- Integrating with OpenAI, Cohere, or Hugging Face APIs
Building Simple AI Tools
- Developing a document summarizer
- Prototyping a chatbot for citizen services
- Automating the labeling of public datasets using AI
Evaluating Outputs and Limitations
- Understanding the probabilistic nature of AI behavior
- Prompt engineering and optimizing output quality
- Red-teaming prototypes to identify bias and hallucinations
Compliance, Ethics, and Responsible Development
- Privacy and explainability standards in government contexts
- Comparing open-source and proprietary models: advantages and disadvantages
- A checklist for safe experimentation and scaling up
Summary and Next Steps
Requirements
- Basic proficiency 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.
Target Audience
- Public servants and analysts exploring the integration of AI into daily operations.
- Digital government professionals seeking hands-on experience with AI implementation.
- 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.