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Course Outline
Fundamentals of AI Programming
- Defining AI programming: core concepts and illustrative examples
- AI applications in the public sector: chatbots, summarizers, and intelligent search
- AI models compared to traditional programming logic
Python Basics for AI
- Creating your initial Python scripts
- Managing data structures and control flow
- 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
- Interacting 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
Assessing Outputs and Constraints
- Comprehending probabilistic AI behavior
- Prompt engineering and monitoring output quality
- Red-teaming prototypes to identify bias and hallucinations
Compliance, Ethics, and Responsible Development
- Privacy and explainability standards in the government sector
- Open-source versus proprietary models: advantages and disadvantages
- Checklists for secure experimentation and scaling
Wrap-Up and Future Steps
Requirements
- Basic proficiency with spreadsheets or structured data
- Familiarity with public sector service delivery or analytical tasks
- No previous coding experience is necessary; introductory Python will be taught
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.