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.
Learning objectives
- Master the 2026 LLM-as-judge protocols to precisely evaluate AI model performance in business settings
- Develop professional skills in designing certified automated benchmarks for AI training
- Design scalable evaluation pipelines integrating LLM-as-judge in real projects
- Optimize judge prompts to reduce biases and boost AI verdict reliability
- Implement advanced human-LLM correlation metrics in professional contexts
- Deploy 2026 LLM-as-judge solutions tailored to companies' certification 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.
Program
Module 1LLM-as-judge 2026 Foundations: Protocols and Benchmarks (Hugging Face, OpenAI Tools)
Discover the 2026 evolutions of LLM-as-judge through concrete automated evaluation cases, explore basic protocols with exercises on standard datasets like MT-Bench, configure your first judge prompts using Hugging Face and OpenAI API, analyze human-LLM correlations on text generation tasks, produce an initial benchmark report validated in group to anchor practical skills from the first day.
Module 2LLM-as-judge 2026 Implementation: Pipelines and Advanced Prompts (LangChain, Custom Datasets)
Dive into building robust pipelines with LangChain and LLMs like GPT-4o or Llama 3, adapt multi-agent prompts to judge complex responses, test on customized datasets from real companies, optimize scalability via batch processing and cloud GPU, evaluate biases with tools like EleutherAI, generate deliverables including a functional pipeline ready for production deployment.
Module 3LLM-as-judge 2026 Optimization: Bias Reduction and Metrics (Fine-tuning, A/B Testing)
Master fine-tuning of LLM judges on specific data via LoRA and PEFT, implement A/B tests to validate robustness, analyze advanced metrics like G-Eval and pairwise comparison, reduce judge hallucinations with chain-of-thought prompting, apply to 2026 use cases like multimodal evaluation, produce an interactive dashboard with Streamlit to visualize performance and export actionable insights.
Module 4Deployment and Real Cases LLM-as-judge 2026: Enterprise Scalability (Kubernetes, MLOps)
Deploy your LLM-as-judge solutions in production with Kubernetes and MLOps tools like MLflow, integrate into CI/CD workflows for continuous evaluation, explore 2026 case studies from leading AI companies, simulate high-load scenarios with 10k+ evaluations, measure ROI via customized KPIs, finalize with a capstone project delivering certification, including source code, report, and maintenance plan for immediate enterprise adoption.
Evaluation method
- Practical projects evaluated by experts (70% of final grade)
- Advanced quizzes and peer-review on LLM-as-judge benchmarks
- Real case study with certifying oral presentation
Learning method
- 80% hands-on approach on real business cases
- Hands-on exercises with open-source LLMs and paid APIs
- Continuous feedback in small groups (max 10 participants)
- Post-training resources: code, datasets, alumni community
Methods, materials and delivery
The Training LLM-as-judge 2026 - 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 2026 - 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 2026 - 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
★★★★★
« cool, j'ai appris des trucs »
★★★★★
« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »
★★★★★
« la formation dev etait intense mais grave bien. merci Anthony Khelil »
★★★★★
« 😊👍 »
★★★★★
« bien 👍 »
★★★★★
« Allan Busi t'es au top, continue comme ça. formation géniale »
★★★★★
« cool, j'ai appris des trucs »
★★★★★
« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »
★★★★★
« la formation dev etait intense mais grave bien. merci Anthony Khelil »
★★★★★
« 😊👍 »
★★★★★
« bien 👍 »
★★★★★
« Allan Busi t'es au top, continue comme ça. formation géniale »
★★★★★
« cool, j'ai appris des trucs »
★★★★★
« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »
★★★★★
« la formation dev etait intense mais grave bien. merci Anthony Khelil »
★★★★★
« 😊👍 »
★★★★★
« bien 👍 »
★★★★★
« Allan Busi t'es au top, continue comme ça. formation géniale »
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.
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.
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.
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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