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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 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 with concise prompting and few-shot techniques
- Testing prompts and defining acceptance criteria
APIs, SDKs, and Local Development Workflow
- Interacting with GPT-5 APIs, using SDKs, and managing authentication and secrets
- Local development setup, mocking responses, and sandboxing
- Versioning, request/response schemas, and error handling strategies
Building Agents and Tool Integrations
- Designing secure agent architectures and tool interfaces
- Implementing routing, orchestration, and fallback mechanisms
- Managing rate limits, concurrency, and transactional integrity
Testing, Evaluation, and Validation
- Creating automated test suites for prompts and model behaviors
- Conducting red-teaming, fuzz testing, and analyzing adversarial examples
- Defining metrics for accuracy, hallucination rates, and user satisfaction
Deployment, Monitoring, and Observability
- Applying CI/CD patterns for model-enabled features and canary releases
- Implementing logging, tracing, and telemetry for prompt-level observability
- Configuring alerting, SLA management, and incident response protocols
Security, Privacy, and Cost Optimization
- Managing data handling, PII/PHI considerations, and context sanitization
- Enforcing access control, auditing, and compliance checkpoints
- Optimizing token usage, batching, and caching strategies
Summary and Next Steps
Requirements
- Proficiency in at least one programming language, such as Python or JavaScript.
- Practical experience in calling REST APIs or using SDKs.
- Familiarity with fundamental ML/AI concepts and JSON data structures.
Target Audience
- Software engineers
- Machine Learning engineers
- DevOps and 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.
