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Duration 14 hours
Course Outline
Introduction to GPT-5 and Developer Capabilities
- Key capabilities of GPT-5, including multi-modality and agent features
- Selecting models, understanding 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
- Comparing chain-of-thought versus 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 practices, mocking responses, and sandboxing
- Versioning, request/response schemas, and robust 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 concerns
Testing, Evaluation and Validation
- Creating automated test suites for prompts and system behaviors
- Conducting red-teaming, fuzz testing, and analyzing adversarial examples
- Evaluating metrics for accuracy, hallucination rates, and user satisfaction
Deployment, Monitoring and Observability
- CI/CD patterns for model-enabled features and canary releases
- Implementing logging, tracing, and telemetry for prompt-level observability
- Setting up alerting, defining SLA considerations, and incident response plans
Security, Privacy and Cost Optimization
- Data handling, managing PI/PHI considerations, and context sanitization
- Access control, auditing procedures, 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.
- Experience with calling REST APIs or utilizing SDKs.
- Fundamental knowledge 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.
