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Course Outline
AI Programming Essentials
- Defining AI programming: core principles and real-world examples.
- AI in the public sector: applications like chatbots, summarizers, and intelligent search.
- Comparing AI models with traditional programming logic.
Python Basics for AI
- Creating your first Python scripts.
- Managing data structures and control flow.
- Key libraries for AI development: requests, pandas, and json.
Leveraging AI APIs
- Understanding APIs and accessing AI models securely.
- Inputting text and structured data into models.
- Working with APIs from OpenAI, Cohere, or Hugging Face.
Developing Basic AI Tools
- Constructing a document summarizer.
- Creating a chatbot prototype for citizen-facing services.
- Applying AI to automatically label public datasets.
Assessing Outputs and Limitations
- Understanding the probabilistic nature of AI behavior.
- Prompt engineering techniques to manage output quality.
- Conducting red-teaming exercises to identify bias and hallucinations in prototypes.
Compliance, Ethics, and Responsible Development
- Meeting privacy and explainability standards within government.
- Comparing open-source and proprietary models: advantages and drawbacks.
- Establishing a checklist for safe experimentation and scaling up.
Key Takeaways and Future Actions
Requirements
- Basic proficiency with spreadsheets or managing structured data.
- Familiarity with public sector service delivery or analytical tasks.
- No previous coding background is necessary, as foundational Python concepts will be introduced.
Who Should Attend
- Government officers and analysts looking to incorporate AI into their daily routines.
- Digital government specialists aiming for 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.
