“The Microsoft Fabric implementation program gave our data engineering team a structured path from legacy pipelines to a modern lakehouse architecture.”
Enterprise Program Brief
Databricks Generative AI & LLM Applications
This program focuses on enterprise GenAI solution design with Databricks. Participants implement RAG pipelines, optimize prompts and retrieval strategies, and build deployable LLM applications for business use cases like chat assistants, document intelligence, and workflow automation.
VNode ITeSAdvancedIn Demand
Download Program Brief (PDF)Program Snapshot
Engagement scoped to cohort
Duration3 Days
FormatVirtual / Onsite
LevelAdvanced
- MCT-led delivery
- Private cohort / virtual ILT
- Typical response: 1 business day
Scoping call typically scheduled within one business day
VNode ITeS delivers Databricks Generative AI & LLM Applications as an MCT-led VNode ITeS program for Data Scientists, ML Engineers, AI Engineers. Typical duration is 3 Days (Virtual / Onsite). Labs follow production-shaped scenarios rather than slide-only walkthroughs. Private cohorts can shift emphasis by role mix, workspace or repo constraints, and rollout timing.
Audience Profile
Built for these roles
Data Scientists, ML Engineers, AI Engineers
- Tailored Team Delivery
- Implementation-Focused
Overview
Executive overview
Build enterprise-grade GenAI applications in Databricks with LLM integration, RAG architectures, embeddings, vector search, and scalable deployment patterns.
Prerequisites
- Experience with Python and notebook-based ML workflows
- Familiarity with core machine learning and NLP concepts
- Basic understanding of API-based model integration
Program Outcomes
Capabilities your teams will gain
- Design and implement RAG-based LLM application architectures
- Apply prompt engineering and embedding strategies for higher response quality
- Build vector search-powered retrieval workflows in Databricks
- Deploy and optimize GenAI applications for enterprise reliability and scale
Enterprise Delivery
Private cohort delivery
VNode-designed, vendor-aligned instructor-led program. Scope role mix, delivery format, and rollout goals for your cohort.
Curriculum
Curriculum roadmap
- LLM foundations and enterprise GenAI patterns
- Prompt engineering and embedding strategies
- RAG architecture and vector search implementation
- LLM frameworks and deployment optimization
1Module 1
LLM Foundations and Enterprise GenAI
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Module 1
LLM Foundations and Enterprise GenAI
Understand LLM capabilities, enterprise GenAI use cases, and how the Databricks ecosystem supports scalable AI workloads.
- Understand LLM capabilities
- enterprise GenAI use cases
- and how the Databricks ecosystem supports scalable AI workloads
2Module 2
Prompt Engineering and Embeddings
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Module 2
Prompt Engineering and Embeddings
Apply prompt engineering techniques and generate text embeddings for retrieval, semantic search, and similarity-based task applications.
- Apply prompt engineering techniques
- generate text embeddings for retrieval
- semantic search
- and similarity-based task applications
3Module 3
RAG Architecture and Vector Search
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Module 3
RAG Architecture and Vector Search
Design and implement RAG pipelines with vector search-powered retrieval using Databricks tools for grounded enterprise AI applications.
- RAG architecture and vector search implementation
4Module 4
LLM Frameworks and Deployment
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Module 4
LLM Frameworks and Deployment
Build LLM applications with LangChain or equivalent orchestration frameworks and deploy with cost and performance optimization for production.
- Build LLM applications with LangChain or equivalent orchestration frameworks
- deploy with cost
- performance optimization for production
Delivery Models
Delivery models
Virtual ILTOnsiteHybridExecutive WorkshopBootcampWeekend
Engagement Fit
Engagement fit
- Implementation-focused labs
- Private cohort delivery
- Advanced practitioner depth
- Business outcome alignment
Enterprise Customization
Enterprise customization
Tailor this program to your organization's priorities: Prepares teams to design and deploy enterprise GenAI applications on Databricks using production-ready RAG, vector search, and LLM optimization patterns.
- Use-case focused labs (assistants, knowledge search, automation)
- Framework preference track (LangChain or equivalent orchestration stack)
- Performance and cost optimization module for enterprise rollout
Resources
Program resources
Yes. Most enterprise clients prefer private delivery scoped to role mix, timezone, and rollout timeline. We align lab environments and scenarios to your tenant context where applicable.
Enterprise Proof
Trusted delivery outcomes
“We needed a partner who understood both the technical depth of Azure OpenAI and the governance requirements of an enterprise.”
Delivery Capability
Enterprise-grade instruction
MCT-led delivery
Programs led by Microsoft Certified Trainer practitioners
Enterprise program oversight
Founder-led specialist delivery with structured rollout planning
Global delivery
APAC · EMEA · Americas · Virtual & Onsite
Implementation-focused
Hands-on labs aligned to production scenarios
