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Duration 14 hours
Course Outline
Introduction to GPT-5 and Developer Capabilities
- Key features of GPT-5, including multi-modality and agent capabilities
- Model selection, pricing structures, and usage limits
- Ethical considerations and enterprise governance frameworks
Prompting and System Design for Reliable Outputs
- Prompt patterns, system messages, and context engineering techniques
- Comparing chain-of-thought with concise prompting and few-shot methods
- Prompt testing and defining acceptance criteria
APIs, SDKs, and Local Development Workflows
- Interacting with GPT-5 APIs, utilizing SDKs, and managing authentication and secrets
- Local development practices, response mocking, and sandboxing
- Version control, request/response schemas, and error handling strategies
Building Agents and Tool Integrations
- Designing secure agent architectures and tool interfaces
- Routing, orchestration, and fallback mechanisms
- Managing rate limits, concurrency, and transactional integrity
Testing, Evaluation, and Validation
- Automated testing suites for prompts and system behaviors
- Red-teaming, fuzz testing, and handling adversarial inputs
- Defining metrics for accuracy, hallucination rates, and user satisfaction
Deployment, Monitoring, and Observability
- CI/CD patterns for model-driven features and canary deployment strategies
- Implementing logging, tracing, and telemetry for prompt-level visibility
- Setting up alerting, SLA management, and incident response protocols
Security, Privacy, and Cost Optimization
- Data handling practices, PI/PHI considerations, and context sanitization
- Access control, audit trails, and compliance checkpoints
- Optimizing token usage, implementing batching, and caching strategies
Summary and Next Steps
Requirements
- Proficiency in at least one programming language, such as Python or JavaScript
- Experience with consuming REST APIs or utilizing SDKs
- Fundamental understanding of ML/AI concepts and JSON data structures
Target Audience
- Software Engineers
- ML Engineers
- DevOps / SRE Engineers
Testimonials (2)
correct way of prompting and including guardrails in instructions.
YEO SHI MIN - ST Engineering Aerospace Ltd
Course - ChatGPT and Microsoft 365 Copilot for Advanced Productivity
Able to pivot upon audience suggestions - ie able to create a real AI agent scenario on the spot.
