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Duration 14 hours (2 days)
Course Outline
AI Programming Fundamentals
- Defining AI programming: Core concepts and real-world examples
- Distinguishing between AI models and traditional programming logic
Python Essentials for AI
- Creating your initial Python scripts
- Managing data structures and control flow
- Key libraries for AI development: requests, pandas, and json
Integrating AI APIs
- Understanding APIs and securely accessing AI models
- Transmitting text and structured data to AI models
- Utilizing APIs from OpenAI, Cohere, or Hugging Face
Developing Basic AI Tools
- Constructing a document summarization tool
Assessing Output and Limitations
- Understanding the probabilistic nature of AI behavior
- Applying prompt engineering techniques to manage output quality
- Conducting red-teaming exercises to identify bias and hallucinations in prototypes
Compliance, Ethics, and Responsible Development
- Comparing open-source versus proprietary models: advantages and disadvantages
- Establishing a checklist for safe experimentation and scalable deployment
Conclusion and Future Directions
Requirements
- Foundational experience in managing spreadsheets or structured data
- Basic familiarity 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 investigating AI integration in daily operations
- Digital government professionals looking to acquire hands-on skills in AI implementation
- Government teams focused on innovation, transformation, and research
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.
