Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Course Outline
LLM Application Architecture and Design
- Common OpenAI application patterns for assistants, copilots, and workflow automation.
- Choosing the right architecture for business requirements, reliability, and user experience.
- Moving from prototype code to maintainable application design.
Prompting, Context, and Structured Outputs
- Structuring system, user, and developer instructions for predictable behavior.
- Designing prompts for consistency, task control, and clearer responses.
- Using structured outputs to support downstream application logic.
- Managing context windows, conversation state, and response quality.
Tool Use and Workflow Orchestration
- Using function calling and tool-enabled workflows with external services.
- Validating inputs and outputs, handling errors, and applying fallback behavior.
- Designing multi-step flows for practical business tasks.
Retrieval and Knowledge Grounding
- Identifying when retrieval-augmented generation is appropriate.
- Preparing documents and chunking content for useful retrieval.
- Retrieving relevant context and grounding responses in trusted sources.
Evaluation, Guardrails, and Operational Readiness
- Defining quality criteria and testing workflows against expected outcomes.
- Reducing hallucinations and handling unsafe, irrelevant, or ambiguous requests.
- Monitoring usage, latency, token consumption, and cost.
- Preparing applications for deployment, support, and iterative improvement.
Hands-On Implementation Workshop
- Building a small end-to-end OpenAI application that combines prompting, structured output, tool use, and retrieval.
- Reviewing design decisions, common issues, and practical next steps for production use.
Requirements
- Familiarity with large language model concepts and API-based application development.
- Experience working with REST APIs, JSON, and prompt-driven application workflows.
- Intermediate programming skills in Python, JavaScript, or a similar language.
Audience
- Software developers building LLM-powered applications.
- AI engineers and technical leads designing OpenAI-based solutions.
- Product teams and solution architects responsible for production AI features.
7 Hours
