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Training RAG on AWS - Optimizing Vector Databases

Course created on November 1, 2026Updated on November 7, 2026

Specialist course · Minimum level required

$7,875

5 days
Remote
10 people max.

Request a quote See the program

Ref: KBX487

10 people max.

$7,875

In-company rate: from $14,175 for the whole teamExpertise rate: $1,575 per day, reflecting the difficulty levelAWS, Azure or OVH infrastructure: from $158 / day extra

On-site and certification exam on quote

5 days

Remote

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.

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41,258 programs · 25 countries

Every program built with a dedicated engineer

Companies: Aptar, ArcelorMittal, Equans, EDF, Ubisoft, Microsoft and Atos.

RAG on AWS training objectives

Master building a RAG pipeline on AWS for enterprise documents with the right vector store selection.
Tune chunking and enrichment of extracts to measure their direct impact on response quality.
Implement reranking and verifiable source citations to ensure traceability.
Evaluate response quality using a reference question set under real-world conditions.
Configure access rights management so each user retrieves only authorized documents.
Optimize cost per prediction and latency in production on AWS workloads.

Program

RAG on AWS curriculum: 5 modules over 5 days

Module 1 : RAG Architecture and AWS Knowledge Bases (Bedrock, OpenSearch)

Analysis of retrieval flows on enterprise documents, vector store selection, and index setup. Hands-on labs with participant data to identify real latency and cost challenges. Review of integration patterns with Lambda and API Gateway.

Module 2 : Chunking and Enrichment of Extracts (LangChain, Bedrock)

Experimentation with chunking strategies and semantic enrichment, measuring impact on response relevance. Iterative exercises on real datasets, parameter tuning, and results comparison with simple metrics. Deliverables: documented preprocessing pipeline.

Module 3 : Reranking and Verifiable Citations (LangChain, OpenSearch)

Implementation of reranking and integration of traceable citations in generated responses. Use cases on internal data to validate consistency and reliability. Analysis of common errors and adjustments to reduce hallucinations.

Module 4 : Quality Evaluation and Reference Question Set (Bedrock, CloudWatch)

Building a reference question set and measuring production performance. Model comparison by real cost and latency rather than offline scores. Group labs to refine prompts and retrieval thresholds.

Module 5 : Security, Access Rights, and Deployment (IAM, Bedrock)

Strict implementation of retrieval-level access rights to respect user permissions. Deployment of a secure autonomous agent and integration tests. Final review of best practices and cost optimization in AWS environments.

How RAG on AWS skills are assessed

Daily quizzes on key concepts
Ongoing evaluated capstone project
Final assessment with trainer feedback

How the RAG on AWS course is taught

Hands-on labs using participants' real data
Concrete business case studies
Model comparisons under production conditions
Group debugging sessions

RAG on AWS training: access and practical arrangements

The Training RAG on AWS - Optimizing Vector Databases 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 on AWS - Optimizing Vector Databases 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 on AWS - Optimizing Vector Databases 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.

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.

Our method

How Learni guarantees the quality of your RAG on AWS training

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.

A child walking to school with a backpack

Our social commitment

A school kit donated to a child for every training booked

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

Enroll and offer a kit

FAQ

RAG on AWS: frequently asked questions

Which tools are used in RAG on AWS training?+

Hands-on work runs on bedrock, openSearch, langChain, cloudWatch and IAM. Those tools come from the RAG on AWS program itself, delivered remotely over 5 days, so participants practise on the stack they will use at work.

What can participants do after RAG on AWS training?+

They can master building a RAG pipeline on AWS for enterprise documents with the right vector store selection, tune chunking and enrichment of extracts to measure their direct impact on response quality and implement reranking and verifiable source citations to ensure traceability. Those are the stated objectives of the RAG on AWS program at Advanced level, checked by the end-of-session assessment.

What does the RAG on AWS program cover, day by day?+

Day 1: RAG Architecture and AWS Knowledge Bases (Bedrock, OpenSearch). Day 2: Chunking and Enrichment of Extracts (LangChain, Bedrock). Day 3: Reranking and Verifiable Citations (LangChain, OpenSearch). Day 4: Quality Evaluation and Reference Question Set (Bedrock, CloudWatch). Day 5: Security, Access Rights, and Deployment (IAM, Bedrock). The RAG on AWS program runs over 5 days, delivered remotely.

How is RAG on AWS training assessed?+

Assessment relies on daily quizzes on key concepts, ongoing evaluated capstone project and final assessment with trainer feedback. Learni issues a completion certificate together with the individual assessment report at the end of the RAG on AWS program, which an L&D team can file as evidence.

How much does RAG on AWS training cost per participant?+

RAG on AWS training costs $7,875 per participant. For an in-company team, the flat rate starts at $14,175 for the whole group, up to 8 people. AWS, Azure or OVH infrastructure is extra, from $158 per day. The detailed quote, sent within one business day, adjusts the amount to the format and how far the syllabus is tailored to your team.

How long does RAG on AWS training take?+

5 days, available live online (US time zones) or on-site at your offices. Half-day tracks spread over several weeks are possible so the team stays operational.

Who pays for RAG on AWS training?+

Most US teams pay directly through their company L&D or training budget. Learni invoices in US dollars and accepts bank transfer (ACH/wire) or card, with volume pricing for teams. A purchase order is welcome.

What do participants need to know before RAG on AWS training?+

Confirmed experience in Python, LLM usage, and AWS services (Bedrock, Lambda, S3). Solid knowledge of vectorization and REST APIs.

Is a certificate issued after RAG on AWS training?+

Yes. A Learni completion certificate is issued, along with the individual evaluation report. Learni is a certified training provider and prepares for third-party certifications, but does not award them itself.

Does Learni provide the equipment for RAG on AWS training?+

No. A computer and a stable internet connection are required for each participant. Learni provides the learning platform, the trainer and all course materials.

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