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Duration 14 hours
Course Outline
Introduction to GPT-5 and Developer Capabilities
- Key GPT-5 capabilities, multi-modality, and agent features.
- Selecting models, and understanding pricing and usage limits.
- Ethical considerations and enterprise governance frameworks.
Prompting and System Design for Reliable Outputs
- Prompt patterns, system messages, and context engineering.
- Comparing chain-of-thought versus concise prompting, including few-shot techniques.
- Testing prompts and defining acceptance criteria.
APIs, SDKs, and Local Development Workflow
- Interacting with GPT-5 APIs, SDK usage, authentication, and secrets management.
- Local development setups, mocking responses, and sandboxing.
- Version control, 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, and transactional requirements.
Testing, Evaluation, and Validation
- Developing 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
- Implementing CI/CD patterns for model-enabled features and canary releases.
- Utilizing logging, tracing, and telemetry for prompt-level observability.
- Setting up alerting, SLA considerations, and incident response protocols.
Security, Privacy, and Cost Optimization
- Managing data handling, PI/PHI considerations, and context sanitization.
- Implementing access control, auditing, and compliance checkpoints.
- Optimizing token usage, batching, and employing caching strategies.
Summary and Next Steps
Requirements
- Proficiency in at least one programming language, such as Python or JavaScript.
- Experience with calling REST APIs or utilizing SDKs.
- Fundamental knowledge of ML/AI concepts and JSON data structures.
Audience
- Software engineers.
- Machine learning 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.
