Can the program be customized?

Yes. Fundamentals of Accelerated Data Science supports customization around lab depth, demo context, certification focus, and team-specific scenarios.

Yes. This program includes instructor-led labs and practical exercises aligned to real implementation patterns.

How does this align with official certification or curriculum?

This program is aligned to the official Official Source curriculum and learning path referenced for this track.

How are prerequisites assessed?

We review prerequisite readiness during scoping and can recommend preparatory modules or a skills checkpoint before cohort start.

What happens after the program?

Private cohorts receive a handover summary, recommended next learning paths, and optional follow-on advisory for rollout or certification readiness.

Enterprise Program Brief

Fundamentals of Accelerated Data Science

This NVIDIA DLI program teaches teams how to perform multiple analysis tasks on large datasets using RAPIDS, NVIDIA’s collection of accelerated data science libraries. It provides a strong delivery foundation for modern GPU-accelerated data preparation, analysis, and machine learning workflows.

Track: NVIDIA DLI Certificate of CompetencyNVIDIABeginnerIn Demand

Plan Private Delivery Consult a Solutions Architect

Download Program Brief (PDF)

Program Snapshot

Engagement scoped to cohort

Duration8 hours

FormatVirtual, On-site, or Hybrid

LevelBeginner

Certification TrackNVIDIA DLI Certificate of Competency

SubjectData Science

MCT-led delivery
Private cohort / virtual ILT
Typical response: 1 business day

Scoping call typically scheduled within one business day

VNode ITeS delivers Fundamentals of Accelerated Data Science as an MCT-led NVIDIA program for Data Scientist. Typical duration is 8 hours (Virtual, On-site, or Hybrid). 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

Built for data scientists who already work with Python-based analytics and want to apply GPU acceleration to real data preparation, analysis, and machine learning workflows.

Data Scientist
Data Science
Tailored Team Delivery
Implementation-Focused

Overview

Executive overview

Official NVIDIA DLI program focused on end-to-end GPU acceleration for enterprise data science workflows using RAPIDS libraries.

Prerequisites

Relevant foundational experience in the target technology area.
Comfort with hands-on labs in a cloud or GPU-accelerated environment.

Program Outcomes

Capabilities your teams will gain

Strengthen capability in data science scenarios
Strengthen capability in nvidia rapids scenarios

Enterprise Delivery

Official learning & delivery options

Review the vendor learning resource, then book a consultation or request a private cohort for your team.

View Official Learning Book a Consultation Request Private Cohort Open in learning platform Program brief (PDF)

Curriculum

Curriculum roadmap

Data Science
NVIDIA RAPIDS

Module 1

Data Science

Cover data science skills and implementation practices aligned to Fundamentals of Accelerated Data Science.

Cover data science skills
implementation practices aligned to Fundamentals of Accelerated Data Science

Module 2

NVIDIA RAPIDS

Cover nvidia rapids skills and implementation practices aligned to Fundamentals of Accelerated Data Science.

Cover nvidia rapids skills
implementation practices aligned to Fundamentals of Accelerated Data Science

Delivery Models

Delivery models

Virtual ILTOnsiteHybridExecutive WorkshopBootcampWeekend

Engagement Fit

Engagement fit

Implementation-focused labs
Private cohort delivery
Beginner practitioner depth
Business outcome alignment

Enterprise Customization

Enterprise customization

Tailor this program to your organization's priorities: Helps data teams speed up analytics and machine learning workflows on large datasets by adopting GPU-accelerated data science foundations with RAPIDS.

Use your tabular analytics scenario and representative datasets
Add Spark or deployment-focused follow-on modules
Extend into enterprise adoption planning for accelerated data science

Credentials

Certification & official source

•NVIDIA DLI Certificate of Competency

Aligned to the official source referenced for this program.

View Official Source

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.

Program brief (PDF)View Official Source

Enterprise Proof

Trusted delivery outcomes

“The Microsoft Fabric implementation program gave our data engineering team a structured path from legacy pipelines to a modern lakehouse architecture.”

“We needed a partner who understood both the technical depth of Azure OpenAI and the governance requirements of an enterprise.”

Banking & Finance

Representative Enterprise Banking Team

The focus was not just on tooling knowledge, but on helping teams work from a shared operating model as they adopted a more modern data platform.

Clearer platform operating model across teams
Improved confidence in modern data stack adoption

Read engagement

Delivery Capability

Enterprise-grade instruction

View delivery capability profile

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

Plan delivery