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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.
- Selecting models and understanding pricing structures and limits.
- Ethical considerations and enterprise governance.
Prompting and System Design for Reliable Outputs
- Effective prompt patterns, system messages, and context engineering.
- Comparing chain-of-thought with concise prompting and few-shot techniques.
- Testing prompts and defining clear acceptance criteria.
APIs, SDKs, and Local Dev Workflow
- Invoking GPT-5 APIs, using SDKs, and managing authentication and secrets.
- Local development workflows, including mocking responses and sandboxing.
- Versioning, request/response schemas, and error handling.
Building Agents and Tool Integrations
- Designing secure agent architectures and tool interfaces.
- Implementing routing, orchestration, and fallback strategies.
- Managing rate limits, concurrency control, and transactional considerations.
Testing, Evaluation and Validation
- Creating automated test suites for prompts and behavioral outputs.
- Conducting red-teaming, fuzz testing, and analyzing adversarial examples.
- Tracking metrics for accuracy, hallucination rates, and user satisfaction.
Deployment, Monitoring and Observability
- Applying CI/CD patterns for model-enabled features and managing canary releases.
- Implementing logging, tracing, and telemetry for prompt-level observability.
- Configuring alerting, SLA considerations, and incident response protocols.
Security, Privacy and Cost Optimization
- Managing data handling, PI/PHI considerations, and context sanitization.
- Enforcing access control, auditing, and compliance checkpoints.
- Optimizing token usage through batching and caching strategies.
Summary and Next Steps
Requirements
- Familiarity with at least one programming language, such as Python or JavaScript.
- Experience with calling REST APIs or utilizing SDKs.
- Basic knowledge of ML/AI concepts and JSON data structures.
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.
