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.
1 seat held for the next session
30:00Held for another
Request a call back and an advisor reaches you within 24 business hours, Monday to Saturday.
Trusted by — schools, companies and industrial groups
Every program built with a dedicated engineer
Learning objectives
- Master advanced RAG architectures in a professional context
- Deploy Qdrant for high-performance semantic search in enterprise environments
- Integrate TensorFlow and PyTorch into certifying MLOps pipelines
- Optimize production skills for generative AI systems
- Design scalable RAG solutions tailored to business needs
- Evaluate and secure data flows for professional training
Our social commitment
A school kit donated to a child for every training
To fight inequalities in access to education, Learni donates a complete school kit to a child in need for every training booked. You build your skills, a child heads back to school.
- Backpack, notebooks and essential supplies
- Distributed through our partner charities
- Included, at no extra cost to you
The Learni story
Founded by engineers and learning experts, Learni's mission is to make high-impact tech training accessible to teams everywhere. We work remotely with organizations across the US and Canada, in your time zone, to help teams upskill fast.
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 1Theme: Advanced RAG Architecture with Qdrant (design, indexing, benchmarks)
Participants explore the foundations of RAG systems by combining vector retrieval and generation. They deploy Qdrant, configure optimized collections, and complete practical exercises on business corpora. Real-world business cases help measure gains in precision and latency while integrating MLOps practices.
Module 2Theme: Integrating TensorFlow and PyTorch into RAG Pipelines (models, embeddings, fine-tuning)
This day covers the integration of TensorFlow and PyTorch for generating high-performance embeddings. Learners build complete pipelines, test different models, and optimize data flows. GPU-based practical exercises and deliverables include a RAG prototype connected to Qdrant.
Module 3Theme: MLOps Applied to Qdrant and RAG (orchestration, monitoring, CI/CD)
Focus on MLOps best practices for industrializing RAG systems. Participants set up deployment pipelines, metric monitoring, and Qdrant index update strategies. Real enterprise use cases enable delivery of a functional CI/CD pipeline.
Module 4Theme: RAG Optimization and Scalability with Qdrant (filtering, hybrid search, latency)
Learners optimize RAG system performance by configuring advanced filtering and hybrid search in Qdrant. Practical work on large volumes, response time analysis, and configuration adjustments. Deliverables include a performance report and an optimized system.
Module 5Theme: Final RAG & Qdrant Project (design, deployment, presentation)
Day dedicated to completing a full project integrating all acquired skills. Participants design, deploy, and evaluate a production RAG solution using Qdrant, TensorFlow, and PyTorch. Presentation of deliverables to the group and issuance of professional training certificates.
Evaluation method
- Final practical project assessed
- Knowledge validation quiz
- Oral defense of the business case
Learning method
- Practical exercises on GPU
- Real-world business cases
- Deployment of functional prototypes
- Personalized expert feedback
Methods, materials and delivery
The Training RAG & Qdrant - Optimizing Generative AI Systems program is delivered onsite or remote (blended-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 RAG & Qdrant - Optimizing Generative AI Systems 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 RAG & Qdrant - Optimizing Generative AI Systems 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
Registration is possible up to 48 business hours before the start of training. All our programs are built for corporate L&D budgets and delivered onsite or remotely.
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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FAQ
Frequently asked questions
How much does the Training RAG & Qdrant - Optimizing Generative AI Systems training cost?+
The individual price is $5,775 (USD). The team / on-site group package is shown on the course page. A detailed quote is sent within one business day.
How long is the Training RAG & Qdrant - Optimizing Generative AI Systems training?+
The training lasts 5 journées, available live online (US time zones) or on-site at your offices.
How is this training paid for?+
Most US teams pay directly through their company (L&D or training budget). We invoice in US dollars and accept bank transfer (ACH/wire) or card, with volume pricing for teams. A purchase order is welcome.
Are there any prerequisites?+
Proficiency in Python, experience with LLMs, and solid foundations in vector databases.
Is a certificate delivered at the end?+
Yes. A Learni completion certificate is issued, along with the individual evaluation report.
Does Learni provide the equipment?+
No. A computer and stable internet connection are required for the participant. Learni provides the educational platform, the trainer and all course materials.
On-site & remote
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