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Training LLM-as-judge 2026 - Automatically Evaluate AI Outputs

Ref: JET835
10 people max.
4375€ HT / per person
−15% from 2 people−30% from 3 people−50% from 5 people
Pay in 3 installments · +$170/day onsite · +$500 with certification exam
5 journées
distanciel

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Learning objectives

  • Master the fundamental principles of LLM-as-judge for professional evaluations
  • Develop effective prompts tailored to evaluating AI outputs in a business setting
  • Implement automated evaluation pipelines using certifying LLMs
  • Design custom metrics to assess the quality of generative responses
  • Optimize LLM-as-judge workflows for scalable and reliable projects
  • Deploy LLM-as-judge solutions integrated with production data skills

The Learni story

Founded by passionate learning and innovation experts, Learni's mission is to make professional training accessible to everyone, anywhere in the world. Our team operates in major hubs — London, New York, Boston — and internationally, to support talents and organizations in upskilling.

Don't let this gap widen

Why this program matters

  • Without this upskilling, your team accumulates a technological gap that translates directly into productivity loss.

  • Organizations that don't train their talents on key topics see their competitiveness drop.

  • Every quarter without training is a gap widening with competitors who invest.

  • The cost of inaction quickly exceeds that of well-targeted training.

Allan Busi
Allan Busi

Learni Trainer · Expert

73%productivity gap
×3cost of inaction

Program

Module 1LLM-as-judge Fundamentals: Principles and Setup (OpenAI API, HuggingFace, Evaluation Datasets)

Immersive introduction to the key concepts of LLM-as-judge, quick setup of the development environment with OpenAI GPT-4o and HuggingFace models, creation of your first evaluation prompt on public datasets like MT-Bench, practical exercises to judge simple textual responses, comparative analysis with human judgments, production of an initial basic metrics report to validate your skills from day one.

Module 2LLM-as-judge Prompt Engineering: Crafting Expert Prompts (Chain-of-Thought, Few-Shot, Role-Playing)

Deep dive into prompt engineering dedicated to LLM-as-judge, experimentation with chain-of-thought and few-shot techniques on real business cases, creation of role-playing prompts to simulate human experts, iterative testing on varied AI outputs using tools like LangChain, measurement of improvements in coherence and relevance scores, development of a reusable prompt template to accelerate future team evaluations.

Module 3LLM-as-judge Metrics and Evaluation: Defining Custom Scores (BLEU, ROUGE, Semantic Coherence)

In-depth exploration of standard and advanced metrics for LLM-as-judge, implementation of BLEU, ROUGE, and semantic evaluations with embeddings via Sentence Transformers, exercises on real datasets like AlpacaEval, calibration of judgment thresholds to minimize biases, creation of an interactive dashboard with Streamlit to visualize results, tangible gains in evaluation precision for professional AI projects.

Module 4Advanced LLM-as-judge Pipelines: Automation and Scaling (Docker, Batch Processing, API Integration)

Building complete LLM-as-judge pipelines in Docker containers for enterprise scalability, implementation of batch processing for thousands of outputs using Ray or Dask, seamless integration with existing APIs such as those for your fine-tuned models, simulations of high loads with R&D use cases, optimization of inference costs on cloud providers, delivery of a deployable prototype ready for production.

Module 5LLM-as-judge 2026 Deployment and Optimization: Best Practices and Real Cases (Fine-Tuning, Monitoring)

Preparation for production deployment with lightweight fine-tuning of LLM judges on your internal data, integration of monitoring with Weights & Biases to track drifts, analysis of real cases from leading companies in 2026, resolution of challenges like hallucinations and biases, final exercises on a personalized red thread project, delivery of a complete kit with source code and optimization guide for immediate team adoption.

Evaluation method

  • Quiz to validate learning outcomes at the end of the training
  • Continuous assessment through practical exercises on pipelines
  • Defense of the LLM-as-judge red thread project in front of the trainer

Learning method

  • Courses led by an expert trainer in applied AI
  • Practical exercises on real 2026 business cases
  • Progressive red thread project throughout the training
  • Complete course materials provided to each participant

Methods, materials and delivery

The Training LLM-as-judge 2026 - Automatically Evaluate AI Outputs program is delivered onsite or remote (blended-learning, e-learning, virtual classroom, remote presence). At Learni, an industry-certified training organization, every program is built to maximize skills acquisition regardless of the chosen format.

The trainer alternates between demonstrative, interrogative and active methods (through hands-on labs and/or scenarios). This pedagogical approach guarantees concrete learning that's immediately applicable at work.

Equipment required

For the smooth delivery of the Training LLM-as-judge 2026 - Automatically Evaluate AI Outputs program, the following equipment is required:

  • Mac or PC computers, high-speed fiber internet, whiteboard or flipchart, projector or interactive touch screen (for remote sessions)
  • Training environments installed on workstations or accessible online
  • Course materials, hands-on exercises and complementary resources
  • Post-training access to materials and educational resources

For intra-company training on a site outside Learni, the client commits to providing all required teaching materials (computers, internet, etc.) for the smooth delivery of the program in line with the prerequisites in the communicated program.

* contact us for remote delivery feasibility** ratio varies depending on the program

Skills assessment methods

Assessment of skills acquired during the Training LLM-as-judge 2026 - Automatically Evaluate AI Outputs program is performed through:

  • During training: case studies, hands-on labs and professional scenarios
  • End of training: self-assessment questionnaire and skills evaluation by the trainer
  • After training: completion certificate detailing acquired skills

Program accessibility

Learni is committed to making its programs accessible. All our programs are accessible to people with disabilities. Our teams are available to adapt the pedagogical methods to your specific needs. Please contact us for any adjustment request.

Enrollment terms and lead times

Learni programs are available inter-company and intra-company, onsite or remote. Enrollments are possible up to 48 business hours before the program starts. Our programs are eligible for corporate funding paths. Contact us to discuss your training project and funding options.

Verified reviews

What our learners

4.9 · +100 verified reviews
★★★★★

« cool, j'ai appris des trucs »

TomFormation AWS — Cloud Practitioner
★★★★★

« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »

Eva CarpentierFormation LLM en Entreprise — Claude, ChatGPT, Mistral
★★★★★

« la formation dev etait intense mais grave bien. merci Anthony Khelil »

NolanDWWM - Développeur Web et Web Mobile
★★★★★

« 😊👍 »

AmbreDWWM - Développement Web & Mobile React
★★★★★

« bien 👍 »

Léo BlanchardFormation AWS — DevOps Engineer Professional
★★★★★

« Allan Busi t'es au top, continue comme ça. formation géniale »

MargotFormation Claude & ChatGPT — Comparatif et Cas d'Usage
★★★★★

« cool, j'ai appris des trucs »

TomFormation AWS — Cloud Practitioner
★★★★★

« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »

Eva CarpentierFormation LLM en Entreprise — Claude, ChatGPT, Mistral
★★★★★

« la formation dev etait intense mais grave bien. merci Anthony Khelil »

NolanDWWM - Développeur Web et Web Mobile
★★★★★

« 😊👍 »

AmbreDWWM - Développement Web & Mobile React
★★★★★

« bien 👍 »

Léo BlanchardFormation AWS — DevOps Engineer Professional
★★★★★

« Allan Busi t'es au top, continue comme ça. formation géniale »

MargotFormation Claude & ChatGPT — Comparatif et Cas d'Usage
★★★★★

« cool, j'ai appris des trucs »

TomFormation AWS — Cloud Practitioner
★★★★★

« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »

Eva CarpentierFormation LLM en Entreprise — Claude, ChatGPT, Mistral
★★★★★

« la formation dev etait intense mais grave bien. merci Anthony Khelil »

NolanDWWM - Développeur Web et Web Mobile
★★★★★

« 😊👍 »

AmbreDWWM - Développement Web & Mobile React
★★★★★

« bien 👍 »

Léo BlanchardFormation AWS — DevOps Engineer Professional
★★★★★

« Allan Busi t'es au top, continue comme ça. formation géniale »

MargotFormation Claude & ChatGPT — Comparatif et Cas d'Usage
Read all reviews
Our method

Training quality, guaranteed at every step

Before, during, after: we frame the brief, introduce the trainer, tailor the content and measure impact. You stay in control from kickoff to wrap-up.

Step 1

Rigorous trainer selection

Each trainer is validated on three criteria: hands-on field expertise, proven pedagogy and alignment with your industry.

  • Triple validation: technical, pedagogical, sectoral.
  • Minimum rating 4.8/5 over the last 12 sessions.
Step 2

You meet the trainer beforehand

30-minute video call between you and the selected trainer to validate the fit, adjust content and clear any final doubts.

  • Live briefing on goals and team context.
  • Veto right — we swap the trainer for free if needed.
Step 3

Content tailored to your context

No recycled slides. The syllabus is reworked from your real cases: tools, constraints, vocabulary, ongoing projects.

  • Hands-on cases drawn from your stack and projects.
  • Program co-written then validated by your team.
Step 4

Continuous quality follow-up

Live evaluations, 30/90/180-day check-ins and a consolidation plan. If the impact misses the mark, we rework it.

  • NPS, knowledge quizzes and skills self-assessment.
  • Satisfaction guarantee: fully satisfied or free rework.

A simple promise: you don't pay to discover the trainer on day one. Everything is validated upfront, by you.

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