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Course Outline
Fundamentals of AI Programming
- Defining AI programming: Key concepts and real-world examples
- AI applications in the public sector: Chatbots, summarization tools, and intelligent search
- Comparing AI models with traditional programming logic
Python Basics for AI Development
- Writing initial Python scripts
- Managing data structures and control flow
- Essential libraries for AI: requests, pandas, and json
Utilizing AI APIs
- Understanding APIs: Secure access to AI models
- Transmitting text and structured data to models
- Working with OpenAI, Cohere, or Hugging Face APIs
Developing Basic AI Applications
- Creating a document summarization tool
- Prototyping a citizen service chatbot
- Using AI for automatic labeling of public datasets
Assessing Output and Limitations
- Understanding the probabilistic nature of AI behavior
- Prompt engineering and managing output quality
- Testing prototypes for bias and hallucinations via red-teaming
Compliance, Ethics, and Responsible Development
- Privacy and explainability standards in government
- Open-source vs. proprietary models: Advantages and disadvantages
- A checklist for safe experimentation and scaling up
Wrap-up and Future Steps
Requirements
- Basic proficiency with spreadsheets or handling structured data
- Familiarity with public sector service delivery or analytical tasks
- No prior programming background needed (introductory Python will be provided)
Target Audience
- Public servants and analysts looking to integrate AI into their daily routines
- Digital government specialists aiming to gain hands-on experience 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.
