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Course Outline
Foundations of AI Programming
- Defining AI programming: Key concepts and real-world examples.
- Public sector applications of AI, including chatbots, summarizers, and intelligent search.
- Distinguishing AI models from traditional programming logic.
Introductory Python for AI
- Creating your initial Python scripts.
- Managing data structures and control logic.
- Essential libraries for AI programming: requests, pandas, and json.
Utilizing AI APIs
- Understanding APIs and securely accessing AI models.
- Transmitting text and structured data to models.
- Working with APIs from providers such as OpenAI, Cohere, or Hugging Face.
Developing Simple AI Tools
- Constructing a document summarizer.
- Prototyping a chatbot for citizen services.
- Automating the labeling of public datasets using AI.
Assessing Outputs and Limitations
- Grasping 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 mandates in government.
- Open-source versus proprietary models: advantages and disadvantages.
- A checklist for safe experimentation and scaling up.
Summary and Next Steps
Requirements
- Basic proficiency in handling spreadsheets or structured data.
- Familiarity with public sector service delivery or analytical tasks.
- No prior programming background is required, as introductory Python will be taught.
Target Audience
- Public servants and analysts looking to integrate AI into their daily routines.
- Digital government professionals seeking hands-on capabilities 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.
