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Certification

Certification in Scaling Test-Time Compute for Smarter LLMs

Become certified in test-time compute scaling and prove you can make smaller LLMs beat frontier ones. You'll know when to scale sampling, build verifiers, and predict compute gains,then apply it to real inference pipelines.

Exam of 10 to 20 questionsCertificate for LinkedInIntermediate · Expert, technical
IT and developmentScience and research
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The exam

Take the certification exam

Multiple-choice questions about the course. Pass with 70% or more and your certificate is issued at once, with a public page and an "Add to LinkedIn" button.

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What the exam covers

2 questions from each of the 11 chapters of the course

20 multiple-choice questions, drawn fresh for every attempt. Pass with 70% or more.

  1. 01Inference scaling2:20
  2. 02Repeated sampling and coverage2:40
  3. 03A shift in compute allocation6:00
  4. 04Formal proofs and code9:00
  5. 05Knowledge graphs and efficiency7:38
  6. 06Parallel and sequential methods1:05
  7. 07Process reward models3:23
  8. 08Analysing test-time scaling7:54
  9. 09Pre-training versus test-time compute5:47
  10. 10Architecture search for inference4:13
  11. 11Inference techniques and optimization13:20
About the course

The Test-Time Compute Scaling: Smarter LLMs Without Retraining video course shows you how to get dramatically better answers from the models you already have, without touching a single weight. You'll gain a real competitive advantage, sharper judgment about where to invest compute, and skills that keep you adaptable as the field keeps evolving. If you've ever felt like your model knows more than it's telling you, this course is where you learn to draw it out.

This certification covers the following topics:

  • The Large Language Monkeys: Sampling Your Way to Smarter Answers
  • Inference Has Scaling Laws Too
  • The Long Tail of Hard Problems
  • The Verifier Problem: Generation Is Easy, Verification Is Hard
  • Reward Models: Teaching Machines to Judge
  • Sequential Revisions: The Other Dimension of Scaling
  • Test-Time Compute vs. Pre-Training: Where Should You Spend Your Tokens?
  • The Building Blocks: Seven Operations That Power Inference Architectures
  • Archon: Treating Inference as an Architecture Search Problem