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Coursera

Design, Compare and Analyze LLM Architectures

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Overview

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Selecting the appropriate architecture for a large language model (LLM) application is a critical decision for any technical team, influencing costs, performance, and security. The course "Design, Compare and Analyze LLM Architectures" is tailored for engineers, architects, and technical leads involved in these pivotal "build vs. buy" assessments. It offers a structured approach to designing and justifying system architectures. Learners will learn to enhance their visual communication skills by creating sequence diagrams that illustrate the trade-offs between synchronous and asynchronous processing flows. The course also emphasizes strategic analysis of deployment options, comparing self-hosting an open-source model with utilizing a managed API. Key skills developed include calculating Total Cost of Ownership (TCO), evaluating latency, and understanding data privacy implications, enabling participants to make informed, business-focused recommendations. By the end of this course, you will be able to confidently design, defend, and document your architectural choices to any stakeholder.

Syllabus

  • System Architecture Diagramming
    • This module introduces the critical role of visual modeling in system design. You will discover why sequence diagrams are essential for comparing synchronous and asynchronous architectures. You will also learn the fundamental components of these diagrams. You will finally practice creating your own diagram to clarify complex LLM application flows and prevent the kinds of costly misunderstandings that plague projects without clear visual documentation.
  • Deployment Strategy Analysis
    • This module tackles the crucial "build vs. buy" decision that every technical leader faces. You will delve into the complex trade-offs between self-hosting an open-source LLM and using a managed API. The focus is on conducting a rigorous, business-aware analysis that balances Total Cost of Ownership (TCO), performance benchmarks, and critical data privacy considerations.

Taught by

LearningMate

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