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Course Outline
Introduction to GPT-5 and Developer Capabilities for Government
- Overview of GPT-5’s key capabilities, including multi-modality and agent features
- Guidance on selecting appropriate models, understanding pricing structures, and navigating usage limits
- Discussion of ethical considerations and best practices for enterprise governance in the public sector
Prompting and System Design for Reliable Outputs for Government
- Strategies for effective prompt patterns, system messages, and context engineering to ensure consistent and accurate responses
- Comparison of chain-of-thought prompting versus concise prompts, and the application of few-shot techniques
- Methods for testing prompts and establishing clear acceptance criteria to meet government standards
APIs, SDKs, and Local Development Workflow for Government
- Procedures for calling GPT-5 APIs, using software development kits (SDKs), managing authentication, and handling secrets securely
- Best practices for local development, including mocking responses and sandboxing environments to facilitate testing
- Guidelines for versioning, defining request/response schemas, and implementing robust error handling mechanisms
Building Agents and Tool Integrations for Government
- Design principles for creating safe agent architectures and tool interfaces that comply with government regulations
- Strategies for routing, orchestration, and fallback to ensure reliable service delivery
- Considerations for rate limits, concurrency control, and transactional integrity in government applications
Testing, Evaluation, and Validation for Government
- Development of automated test suites to validate prompts and agent behaviors against government requirements
- Techniques for red-teaming, fuzz testing, and generating adversarial examples to identify potential vulnerabilities
- Metrics for assessing accuracy, hallucination rates, and user satisfaction in government contexts
Deployment, Monitoring, and Observability for Government
- Continuous integration/continuous deployment (CI/CD) patterns for deploying model-enabled features with canary releases to minimize disruption
- Practices for logging, tracing, and telemetry to achieve prompt-level observability in government systems
- Protocols for alerting, service level agreement (SLA) considerations, and incident response to ensure high availability and reliability
Security, Privacy, and Cost Optimization for Government
- Data handling practices, including considerations for personally identifiable information (PII) and protected health information (PHI), and methods for context sanitization
- Access control measures, auditing processes, and compliance checkpoints to meet government security standards
- Strategies for optimizing token usage, implementing batching, and leveraging caching techniques to reduce costs and improve performance
Summary and Next Steps for Government
Requirements
- An understanding of at least one programming language, such as Python or JavaScript
- Experience with calling REST APIs or SDKs
- Basic familiarity with machine learning/artificial intelligence concepts and JSON data structures
Audience for Government
- Software engineers
- Machine learning engineers
- DevOps/SRE engineers
14 Hours
Testimonials (1)
The trainer provided clear explanations, and the topic is highly relevant
