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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, understanding pricing models 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 vs. concise prompting and few-shot techniques
- Testing prompts and defining clear acceptance criteria
APIs, SDKs, and Local Dev Workflow
- Integrating GPT-5 APIs, utilizing SDKs, and managing authentication and secrets
- Local development practices, mocking responses, and sandboxing environments
- Version control, request/response schemas, and robust error handling
Building Agents and Tool Integrations
- Designing secure agent architectures and tool interfaces
- Routing logic, orchestration, and fallback strategies
- Managing rate limits, concurrency control, and transactional integrity
Testing, Evaluation and Validation
- Creating automated test suites for prompts and behavioral outcomes
- Red-teaming, fuzz testing, and analyzing adversarial examples
- Tracking metrics for accuracy, hallucination rates, and user satisfaction
Deployment, Monitoring and Observability
- CI/CD patterns for model-enabled features and canary release strategies
- Implementing logging, tracing, and telemetry for prompt-level observability
- Setting up alerting systems, SLA considerations, and incident response protocols
Security, Privacy and Cost Optimization
- Data handling, PI/PHI compliance considerations, and context sanitization
- Implementing access control, auditing trails, and compliance checkpoints
- Optimizing token usage through batching and caching strategies
Summary and Next Steps
Requirements
- Proficiency in at least one programming language, such as Python or JavaScript.
- Hands-on experience with calling REST APIs or utilizing SDKs.
- Familiarity with basic 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.
