“We needed a partner who understood both the technical depth of Azure OpenAI and the governance requirements of an enterprise.”
Microsoft Official Curriculum
Role-Based Certification PrepTrack: DP-3014Official Source: Microsoft Learn
MicrosoftIntermediate
Build machine learning solutions using Azure Databricks
Azure Databricks is a fully managed, cloud-based data analytics platform, which empowers developers to accelerate AI and innovation by simplifying the process of building enterprise-grade data applications. Built as a joint effort by Microsoft and the team that started Apache Spark, Azure Databricks provides data science, engineering, and analytical teams with a single platform for big data processing and machine learning. In this course, you’ll learn how to use Azure Databricks to train and deploy machine learning models.
Duration
1 day
Level
Intermediate
Format
Virtual, On-site, or Hybrid
Language
English
Executive brief for stakeholdersDownload Program Brief (PDF)
Microsoft
DataIT
Build machine learning solutions using Azure Databricks
Azure
Data
On this page
Ideal for
AI EngineerDataCertification ReadinessTailored Team Delivery
Audience Profile
Built for these roles
This course is designed for aspiring data scientists and AI engineers who need to train and manage machine learning models by using Azure Databricks.
Overview
Executive overview
Official Microsoft Learn-aligned instructor-led program for Build machine learning solutions using Azure Databricks.
Readiness
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 scenarios
Strengthen capability in azure scenarios
Strengthen capability in role-based scenarios
Curriculum
Curriculum roadmap
1
Data
2
Azure
3
Role-Based
1Module 1
Build machine learning solutions using Azure Databricks
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Module 1
Build machine learning solutions using Azure Databricks
Azure Databricks is a cloud-scale platform for data analytics and machine learning. Data scientists and machine learning engineers can use Azure Databricks to implement machine learning solutions at scale. (DP-3014)
- Explore Azure Databricks
- Use Apache Spark in Azure Databricks
- Train a machine learning model in Azure Databricks
- Use MLflow in Azure Databricks
- Tune hyperparameters in Azure Databricks
- Use AutoML in Azure Databricks
- Train deep learning models in Azure Databricks
- Manage machine learning in production with Azure Databricks
Delivery Models
Delivery models
Virtual ILTOnsiteHybridExecutive WorkshopBootcampWeekend
Engagement Fit
Engagement fit
Certification readinessImplementation-focused labsPrivate cohort deliveryIntermediate practitioner depth
Enterprise Customization
Enterprise customization
Tailor this program to your organization's priorities: Builds current Microsoft credential readiness for Build machine learning solutions using Azure Databricks using the official Microsoft Learn outline.
- •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
- •DP-3014
Aligned to the official Microsoft Learn course and learning path for this program.
View Official Microsoft Learn PageResources
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
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
Healthcare
Representative Healthcare Product Team
The engagement helped product and engineering stakeholders move from interest in AI to clearer implementation choices, security expectations, and prototyping discipline.
- Stronger alignment between product and engineering teams
- Improved clarity on prototype-to-production requirements
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