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Duration 14 hours (2 days)
Course Outline
AI Programming Fundamentals
- Defining AI programming: core concepts and real-world examples.
- Applications of AI in the public sector, including chatbots, summarizers, and intelligent search.
- Distinguishing AI models from traditional programming logic.
Introductory Python for AI Applications
- Writing initial Python scripts.
- Managing data structures and control logic.
- Key libraries for AI programming: requests, pandas, json.
Integrating AI APIs
- Understanding APIs and secure access to AI models.
- Transmitting text and structured data to models.
- Working with OpenAI, Cohere, or Hugging Face APIs.
Developing Basic AI Tools
- Constructing a document summarizer.
- Prototyping a chatbot for citizen services.
- Utilizing AI to automatically label public datasets.
Evaluating Outputs and Limitations
- Comprehending probabilistic AI behavior.
- Prompt engineering and maintaining output quality.
- Conducting red-teaming tests on prototypes to identify bias and hallucinations.
Compliance, Ethics, and Responsible Development
- Addressing privacy and explainability requirements in government.
- Comparing open-source and proprietary models: advantages and disadvantages.
- Checklists for safe experimentation and scaling.
Recap and Future Steps
Requirements
- Foundational experience with spreadsheets or structured data handling.
- Familiarity with public sector service delivery or analytical tasks.
- No prior programming background is needed, as introductory Python concepts will be taught.
Target Audience
- Public servants and analysts aiming to integrate AI into their daily operations.
- Digital government professionals looking to acquire hands-on AI integration skills.
- 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.
