Quick skill test · 20 questions · 20 minutes · Free

LLM Evaluation and Benchmarking Certification

Tests how to evaluate large language models — choosing benchmarks, building task-specific evals, human and LLM-as-judge grading, contamination, statistical significance and safety evals. Pass to earn LLM Evaluation and Benchmarking SOA-LLME.

What is the LLM Evaluation and Benchmarking Certification?

The LLM Evaluation and Benchmarking Certification is a free 20-minute skill test from Science of Apps. It tests how to evaluate large language models — choosing benchmarks, building task-specific evals, human and LLM-as-judge grading, contamination, statistical significance and safety evals. Score 70% or more on its 20 questions to earn a verifiable LLM Evaluation and Benchmarking certificate (SOA-LLME). Every question is based on published standards and research — including HELM: Holistic Evaluation of Language Models (Stanford CRFM), Define success criteria and build evaluations (Anthropic), Evals guide (OpenAI) — and each answer is explained with its source.

Built for your job title

ML engineer, AI researcher, AI engineer, Data scientist and AI product manager — and anyone who wants quick, verifiable proof of LLM Evaluation and Benchmarking skills for a CV or LinkedIn.

  • ML engineer
  • AI researcher
  • AI engineer
  • Data scientist
  • AI product manager

Land the job, not just the certificate

Career guide · 8 min read

LLM evaluation skills employers want in 2027: benchmarks vs task evals, rubrics, human and model graders, contamination, significance and safety

LLM evaluation skills employers want in 2027: task evals vs benchmarks, rubrics, LLM-as-judge, contamination, significance, safety and eval infrastructure.

Read the hiring playbook →

What the test covers

Four skill areas with 5 questions each, drawn from a bank of 10 per area, so a retake brings questions you haven't seen.

  1. 01

    Designing evals

    25%
    • Benchmarks vs task evals
    • Metrics and rubrics
    • Human and model graders
  2. 02

    Interpreting results

    25%
    • Contamination and validity
    • Variance and significance
    • Safety and robustness
  3. 03

    Evaluation infrastructure

    25%
    • Eval harnesses
    • Datasets and versioning
    • CI integration
  4. 04

    Human evaluation and product metrics

    25%
    • Human preference studies
    • Online A/B tests
    • User feedback signals

Based on published standards

The questions are original scenarios, and each one names the public standard, official guide or research it draws on — shown under the question while you answer, and linked in your review. These are the sources behind this test:

Try a sample question

Which is the best evidence a model fits your support use case?

  1. A demo video
  2. Model size
  3. High scores on an eval set built from your real support tickets
  4. The vendor's leaderboard rank
Show the answer

C. High scores on an eval set built from your real support tickets — Your own representative data is the best predictor. The real test has 20 questions like this.

How the test works

  1. 20 minutes, 20 questions

    One question per screen, with a progress bar and a countdown. Your progress is saved on this device if you need to pause.

  2. Graded on our server

    Answers reach the page only after you submit, so the certificate can only be earned by passing.

  3. Every answer explained

    Pass or not, you see every question with the right answer, why, and the source behind it. Pass mark 70%, distinction 90%.

  4. Your certificate

    Founder-signed, with a QR code and credential ID. Download PDF or PNG, add to LinkedIn, and it's emailed to you.

What you earn

A Science of Apps certificate for AI & Generative AI: ivory paper with a gold medal
LinkedIn-ready certificate

Pass, then add it to LinkedIn in one click

No typing. The Add to LinkedIn button opens your profile’s Licenses & certifications form already filled in: the certificate name, Science of Apps as the issuer, the issue date, your credential ID and a link recruiters can use to verify it.

  1. 1Take the 20-minute test
  2. 2Score 70% or more
  3. 3Click Add to LinkedIn
Free · no sign-up · also emailed to you as a PDF
How it shows on your LinkedIn profile

See every AI & GenAI certification and test →

Frequently asked questions

What is the LLM Evaluation and Benchmarking Certification?

The LLM Evaluation and Benchmarking Certification is a free 20-minute skill test from Science of Apps. It tests how to evaluate large language models — choosing benchmarks, building task-specific evals, human and LLM-as-judge grading, contamination, statistical significance and safety evals. Score 70% or more on its 20 questions to earn a verifiable LLM Evaluation and Benchmarking certificate (SOA-LLME). Every question is based on published standards and research — including HELM: Holistic Evaluation of Language Models (Stanford CRFM), Define success criteria and build evaluations (Anthropic), Evals guide (OpenAI) — and each answer is explained with its source.

How do I take the LLM Evaluation and Benchmarking Certification for free?

Read the four skill areas on this page, then take the 20-minute test online — no fee, course or sign-up. You see every answer explained when you finish. Score 70% or more and you get a LLM Evaluation and Benchmarking certificate straight away, on screen, as a PDF and by email, with a credential ID anyone can verify.

Are the LLM Evaluation and Benchmarking Certification questions based on real standards?

Yes. The questions are original scenarios written by Science of Apps, and each one is based on a public source you can read: HELM: Holistic Evaluation of Language Models (Stanford CRFM); Define success criteria and build evaluations (Anthropic); Evals guide (OpenAI); e-Handbook of Statistical Methods (NIST); Trustworthy Online Controlled Experiments (Kohavi, Tang & Xu); Machine Learning Crash Course (Google for Developers). The source is shown under each question and linked in the answer review. Science of Apps doesn't copy questions from other tests.

What does the LLM Evaluation and Benchmarking Certification cover?

Four skill areas with five questions each, drawn from a bank of 10 per area so a retake brings new questions: Designing evals (Benchmarks vs task evals, Metrics and rubrics and Human and model graders); Interpreting results (Contamination and validity, Variance and significance and Safety and robustness); Evaluation infrastructure (Eval harnesses, Datasets and versioning and CI integration); Human evaluation and product metrics (Human preference studies, Online A/B tests and User feedback signals). Every question is an original scenario based on a published standard, official documentation or research, named under the question.

Who should take the LLM Evaluation and Benchmarking Certification?

ML engineer, AI researcher, AI engineer, Data scientist and AI product manager. It suits anyone who wants a quick, verifiable way to show LLM Evaluation and Benchmarking skills, from students and career switchers to experienced professionals.

Can I take the LLM Evaluation and Benchmarking Certification from any country?

Yes. The test is online, in English and free everywhere — people take it from India, the US, the UK, Europe, Africa, Latin America and Asia-Pacific. Your certificate is dated with your own local date and can be verified from anywhere at scienceofapps.com/certification/verify/.

How long is the LLM Evaluation and Benchmarking Certification?

20 questions — 5 from each of 4 skill areas — with a 20-minute limit. You need 70% (14 of 20) to pass and 90% for distinction.

How hard is the LLM Evaluation and Benchmarking Certification?

We rate it Advanced: assumes years in the role or deep specialist knowledge. It has 20 scenario questions — 5 from each of 4 skill areas — and a 20-minute limit. You need 70% (14 of 20) to pass and 90% for distinction.

How do I prepare for a ML engineer job?

Employers in 2027 want ML engineers, AI engineers and data scientists who can evaluate language models properly: knowing when public benchmarks mislead, building task-specific evals with clear rubrics, using human and calibrated model graders, checking contamination, reporting variance and significance, running safety evals, and wiring evals into CI and A/B tests. Benchmarks saturate fast, so custom evaluation is the durable skill. Build an eval harness and verify your knowledge with a free test. Our full career guide covers the hiring process, interview loop, pay and a prep plan: scienceofapps.com/blog/llm-evaluation-and-benchmarking-career-guide/

How much do Science of Apps certifications cost?

Nothing. There is no fee to take a test, to receive the certificate, to have it emailed or to verify it, and no sign-up.

How are the tests graded?

On our server, not in your browser. The answers never reach the page until you submit, so a certificate can only be earned by passing. Each certificate gets a unique credential ID stored by Science of Apps.

What happens if I don't pass?

You see your score for each area and every question with the correct answer and why, with the published source behind it. You can retake after 30 minutes, and the retake draws questions you haven't seen yet.

Do the certificates expire?

No. Every certificate is dated, so it always shows when you passed. Retake a test any time for a newer date or a higher score.

Can I add the certificate to LinkedIn?

Yes. After you pass, Add to LinkedIn opens the Licenses & certifications form with the certificate name, Science of Apps as the issuer, the issue date, your credential ID and the verification link filled in. You can also download it as a PDF or PNG, and it's emailed to you as a PDF.

How can an employer verify my certificate?

Every certificate has a credential ID and a QR code. Scanning it, or entering the ID at scienceofapps.com/certification/verify/, shows the holder's name, the certification, the score and the issue date from our records.

Are these accredited qualifications?

No. They are Science of Apps' own assessments of applied skill. They aren't issued by a university or standards body, and they work best alongside a portfolio that shows the skills in real work.

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