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Course Outline
Basics of AI Programming
- Defining AI programming: Key concepts and real-world examples
- AI use cases in the public sector: chatbots, summarizers, and intelligent search
- Comparing AI models with traditional programming logic
Python Basics for AI Applications
- Writing your initial Python scripts
- Utilizing data structures and control flow logic
- Essential libraries for AI programming: requests, pandas, json
Leveraging AI APIs
- Understanding APIs: Securely accessing AI models
- Transmitting text and structured data to models
- Working with APIs from OpenAI, Cohere, or Hugging Face
Building Basic AI Tools
- Constructing a document summarizer
- Prototyping a chatbot for citizen services
- Automating the labeling of public datasets using AI
Assessing Output Quality and Limitations
- Understanding the probabilistic nature of AI behavior
- Prompt engineering techniques and managing output quality
- Red-teaming prototypes to identify bias and hallucinations
Compliance, Ethics, and Responsible Development
- Privacy and explainability requirements in the government context
- Open-source versus proprietary models: Advantages and disadvantages
- Checklist for safe experimentation and scaling up
Recap and Future Steps
Requirements
- Basic familiarity with spreadsheets or working with structured data.
- Experience with public sector service delivery or analytical tasks.
- No prior programming background is necessary, as introductory Python concepts will be covered.
Target Audience
- Public servants and analysts looking to integrate AI into their daily routines.
- Digital government specialists seeking practical 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.