Technologies / Artificial Intelligence

Operational Deployment of Large Language Models with Vector Search

Advanced workshop on building stable question-answering systems based on corporate data using vector search (RAG) and large language models. The program covers the full cycle from document chunking through vector indexes to security guardrails and quality monitoring. The methodology combines theory with practical building of a RAG system prototype ready for production deployment. The workshop focuses on achieving enterprise-grade reliability and security of AI solutions.

Required Participant Preparation

Solid experience in Python programming and machine learning fundamentals. Knowledge of API architectures and distributed systems in production environment. Experience working with large datasets and databases. Basic knowledge of NLP concepts and neural networks, transformer familiarity preferred.

Benefits

To deploy stable AI systems based on corporate data with quality and security guarantees
The training will make organizational knowledge accessible through intelligent question-answering interfaces available 24/7
The workshop will increase knowledge worker productivity through fast access to corporate information
Participants will ensure compliance and data security through built-in control mechanisms
Knowledge about optimizing AI systems operational costs through effective resource management
The training will enable systematic monitoring and improvement of answer quality through automatic evaluation systems
The workshop will help build scalable architecture enabling system expansion to new business areas without performance loss

Who is this training for?

Machine Learning and AI Engineers

AI/ML Solution Architects

Data Scientists and ML Engineers

Python Developers with AI experience

DevOps Engineers deploying AI systems

Product Managers of AI products

CTOs and technical leaders

Training program

Pipeline components: chunking, embedding, vector search, generation
Comparing vector databases and indexing strategies
Hybrid search: keyword + semantic
Enterprise-scale architecture and high availability

Chunking strategies for different document types
Preprocessing and normalizing corporate data
Knowledge versioning and incremental updates
Metadata and tagging for better search precision

Quality assessment: faithfulness, answer relevancy, context precision
Guardrails: PII detection, inappropriate content, hallucinations
A/B testing for question-answering systems
Model drift monitoring and quality degradation

Practical RAG prototype building with code
Deployment patterns and load balancing for AI systems
Cost and latency optimization in production
Incident response and AI systems troubleshooting

Delivery Methods

Online

Convenience of participating from anywhere
Interactive live sessions with trainer
Materials available for 30 days
No travel costs

On-site

Direct contact with trainer and group
Intensive hands-on workshops
Networking with other participants
Full focus on learning

Training Topics

Frequently asked questions

Who is the Operational Deployment of Large Language Models with Vector Search training for?

This training is designed for professionals looking to develop skills in operational deployment of large language models with vector search. Required level: intermediate.

How long is the Operational Deployment of Large Language Models with Vector Search training?

The training lasts 3. Available in online or on-site format.

Will I receive a certificate?

Yes — every participant receives a completion certificate confirming acquired competencies. EITT holds ISO 9001 accreditation.

Can this training be conducted for a closed group?

Yes — we offer dedicated closed trainings for companies. We customize the program to your team's needs. Contact us for an individual quote.