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Training LLM-as-judge - Automating Precise AI Evaluation

Ref: IXQ339
10 people max.
4400€ 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
4 journées
distanciel

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Learning objectives

  • Master LLM-as-judge architectures for automated evaluations in certified professional training
  • Develop expert prompts optimizing AI judge precision in enterprise contexts
  • Implement scalable LLM-as-judge pipelines with advanced deep learning skills
  • Analyze and correct biases in professional AI evaluations
  • Optimize LLM-as-judge performance for production deployments
  • Design customized benchmarks enhancing artificial intelligence skills
  • Deploy certified LLM-as-judge solutions tailored to business needs

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.

Fouzi Benzidane
Fouzi Benzidane

Learni Trainer · Expert

73%productivity gap
×3cost of inaction

Program

Module 1LLM-as-judge Fundamentals: Advanced Principles and Benchmarks (Hugging Face, EleutherAI, MT-Bench)

Dive into expert theories of LLM-as-judge, explore standard benchmarks like MT-Bench and Arena, analyze correlations with humans via concrete case studies, set up your first environments with Hugging Face Transformers, perform practical exercises on real datasets, produce initial evaluation reports, while integrating tools like LangChain for quick and efficient enterprise setups.

Module 2Advanced LLM-as-judge Prompting: Expert Techniques and Chain-of-Thought (CoT, Tree-of-Thoughts)

Master expert prompt engineering for LLM-as-judge, implement reasoning chains CoT and ToT on GPT-4 and Llama, test variants with few-shot learning on complex evaluation tasks, optimize consistency via structured rubrics, apply to real cases like RLHF alignment, generate reusable prompt deliverables, integrate metrics like G-Eval for real-time validation during intensive practical sessions.

Module 3Implementing LLM-as-judge Pipelines: Tools and Frameworks (LangChain, LlamaIndex, Scaling)

Build end-to-end LLM-as-judge pipelines with LangChain and LlamaIndex, integrate APIs like OpenAI and vLLM for fast inference, deploy on AWS or GCP cloud with Docker, test scalability on 10k samples, analyze real costs and latencies, conduct collaborative remote exercises, produce a functional enterprise-deployable prototype, covering error handling and advanced monitoring.

Module 4Optimization and Real-World LLM-as-judge Cases: Biases, Fine-Tuning, Production (RAG, Agents)

Optimize LLM-as-judge against biases via LoRA fine-tuning on custom datasets, integrate RAG for expert contextualization, simulate production scenarios with multi-judge agents, evaluate robustness on adversarial benchmarks, analyze industrial case studies like those at Anthropic, deploy Streamlit dashboards for reporting, finalize a certifiable capstone project ready for AI business workflow integration.

Evaluation method

  • Daily technical quizzes on LLM-as-judge and benchmarks
  • Real-world case studies with personalized expert feedback
  • Final project: complete pipeline evaluated live, scored on precision and scalability

Learning method

  • Hands-on practical projects with real code and exclusive datasets
  • Live interactive remote sessions, max 10 participants
  • Replay videos and advanced resources post-training
  • Individual mentoring by Qualiopi-certified experts

Methods, materials and delivery

The Training LLM-as-judge - Automating Precise AI Evaluation 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 - Automating Precise AI Evaluation 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 - Automating Precise AI Evaluation 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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