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⇱ Design, Compare and Analyze LLM Architectures | Coursera


Design, Compare and Analyze LLM Architectures

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Design, Compare and Analyze LLM Architectures

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Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

2 hours to complete
Flexible schedule
Learn at your own pace

Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

2 hours to complete
Flexible schedule
Learn at your own pace

What you'll learn

  • Design and justify LLM architectures by modeling system flows and analyzing self-hosting vs. managed API trade-offs.

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Recently updated!

February 2026

Assessments

3 assignmentsΒΉ

AI Graded see disclaimer
Taught in English

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This course is part of the Microservices Architecture for AI Systems Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
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There are 2 modules in this course

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.

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.

What's included

2 videos1 reading1 assignment

2 videosβ€’Total 17 minutes
  • The Cost of Ambiguityβ€’8 minutes
  • Building Sequence Diagrams Step-by-Stepβ€’9 minutes
1 readingβ€’Total 12 minutes
  • Synchronous vs. Asynchronous Architecturesβ€’12 minutes
1 assignmentβ€’Total 15 minutes
  • Hands-On Learning: Diagram an LLM-Powered Workflowβ€’15 minutes

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.

What's included

2 videos1 reading2 assignments

2 videosβ€’Total 21 minutes
  • The Build vs. Buy Dilemmaβ€’9 minutes
  • A Practical Guide to TCO Calculationβ€’12 minutes
1 readingβ€’Total 12 minutes
  • The Deployment Decision Matrixβ€’12 minutes
2 assignmentsβ€’Total 40 minutes
  • Project: Architectural Decision Record (ADR)β€’30 minutes
  • Hands-On Learning: Calculate the TCO for Your LLMβ€’10 minutes

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Frequently asked questions

In this course, analyzing LLM architectures means comparing how an LLM application handles requests, moves work through the system, and gets deployed. The emphasis is on making trade-offs visible so you can justify choices around system flow, cost, latency, and data privacy.

You would use it when a team needs to decide how an LLM feature should behave in practice and which deployment path fits the situation. It is especially useful when comparing synchronous versus asynchronous flows or weighing self-hosting against a managed API.

It fits after the feature idea is clear but before the final system is built and defended to stakeholders. In this course, the analysis helps teams map interactions, surface risks, and document why one architecture makes more sense than another.

Choosing a model in isolation focuses on the model itself, while architecture analysis looks at the full system around it. Here, that means comparing request flows, failure handling, deployment options, and business trade-offs rather than treating model selection as the whole decision.

A basic understanding of software systems and LLM-based applications is helpful for following the trade-offs in this course. What matters most is being able to reason about system behavior, compare options, and read simple technical diagrams.

The course uses sequence diagrams, a web-based diagramming tool such as diagrams.net, and a spreadsheet-style TCO calculator. The main methods are visual system modeling and structured comparison of cost, latency, and data privacy.

You practice drawing sequence diagrams for synchronous and asynchronous LLM flows, including timeouts, retries, and error paths, and comparing self-hosted and managed deployment options. You also work through cost modeling, evaluate latency and privacy trade-offs, and write short recommendations that defend an architectural choice.

Financial aid available,

ΒΉ Some assignments in this course are AI-graded. For these assignments, your data will be used in accordance with Coursera's Privacy Notice.