Can the program be customized?

Yes. Machine Learning Engineer 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 Databricks 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

Machine Learning Engineer

Get started with Machine Learning Data Preparation with Machine Learning Machine Learning Model Development Machine Learning Model Deployment Machine Learning Operations

Role-Based Certification PrepTrack: Databricks Academy learning planOfficial Source: DatabricksDatabricksIntermediate

Plan Private Delivery Consult a Solutions Architect

Download Program Brief (PDF)

Program Snapshot

Engagement scoped to cohort

Duration1 to 2 days

FormatVirtual, On-site, or Hybrid

LevelIntermediate

Certification TrackDatabricks Academy learning plan

SubjectMachine Learning

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

Scoping call typically scheduled within one business day

VNode ITeS delivers Machine Learning Engineer as an MCT-led Databricks program for ML / AI Engineer. Typical duration is 1 to 2 days (Virtual, On-site, or Hybrid). Labs follow production-shaped scenarios rather than slide-only walkthroughs. Certification prep maps to the official exam outline without turning the week into a dump of Learn modules. Private cohorts can shift emphasis by role mix, workspace or repo constraints, and rollout timing.

Audience Profile

Built for these roles

Built for ML / AI Engineer learners adopting Machine Learning Engineer.

ML / AI Engineer
Machine Learning
Certification Readiness
Tailored Team Delivery

Overview

Executive overview

Databricks Academy-aligned program for Machine Learning Engineer.

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 machine learning scenarios
Strengthen capability in databricks data intelligence platform 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

Machine Learning
Databricks Data Intelligence Platform

Module 1

Machine Learning

Cover machine learning skills and implementation practices aligned to Machine Learning Engineer.

Cover machine learning skills
implementation practices aligned to Machine Learning Engineer

Module 2

Databricks Data Intelligence Platform

Cover databricks data intelligence platform skills and implementation practices aligned to Machine Learning Engineer.

Cover databricks data intelligence platform skills
implementation practices aligned to Machine Learning Engineer

Delivery Models

Delivery models

Virtual ILTOnsiteHybridExecutive WorkshopBootcampWeekend

Engagement Fit

Engagement fit

Certification readiness
Implementation-focused labs
Private cohort delivery
Intermediate practitioner depth

Enterprise Customization

Enterprise customization

Tailor this program to your organization's priorities: Develops Databricks lakehouse delivery capability for machine learning teams through official Academy-aligned training.

Align labs to your production environment and platform priorities
Add readiness reviews and instructor-led practice sessions
Extend into project-specific architecture or delivery coaching

Credentials

Certification & official source

•Databricks Academy learning plan

Aligned to the official Databricks training catalog and certification guidance for this program.

View Databricks Training 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 Databricks Training 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