DP-3014: Implementing a Machine Learning solution with Azure Databricks

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DP-3014: Implementing a Machine Learning Solution with Azure Databricks is intended to give data professionals the know-how to use Azure Databricks to create and implement scalable machine learning solutions. This course guides you through the whole machine learning lifecycle, from data preparation and model training to deployment and monitoring, all in a collaborative, cloud-based setting, utilizing the capabilities of Apache Spark, MLflow, and Azure Machine Learning.

You will learn how to manage trials, operationalize ML models in production, and streamline data operations through practical laboratories and real-world scenarios. This course will help you become proficient in the tools and methods required to use Azure’s unified analytics ecosystem to produce significant AI solutions, regardless of your background as a data scientist, machine learning engineer, or data engineer.

What is the DP-3014 course about?

The practical course DP-3014: Implementing a Machine Learning Solution with Azure Databricks teaches data professionals how to use Azure Databricks to create, train, and implement machine learning models at scale.

Who should take this course?

This course is ideal for data scientists, machine learning engineers, data engineers, AI/ML developers, and technical architects who want to build, deploy, and manage scalable machine learning solutions using Azure Databricks and related Azure services.

Are there any prerequisites for this course?

Yes. Participants should have a basic understanding of machine learning concepts, familiarity with Python programming, experience with data analysis libraries (like pandas or NumPy), and foundational knowledge of Azure cloud services. Experience with Apache Spark is helpful but not mandatory.

What are the main learning outcomes of DP-3014?

By the end of the course, you will be able to:

Prepare and process data at scale with Apache Spark on Azure Databricks

Build, train, and evaluate machine learning models using Python and Spark MLlib

Track experiments using MLflow

Deploy and manage models with Azure Machine Learning

Do I need my own Azure subscription?

While not always mandatory, having an Azure subscription is helpful for hands-on labs. Many training providers offer temporary access to Azure environments or sandbox accounts during the course.

How is this course delivered?

The course typically includes a mix of instructor-led sessions, hands-on labs, and practical exercises to ensure applied learning.

Is this course aligned with any certification?

Yes, DP-3014 aligns with Microsoft’s role-based certification paths and helps prepare for certifications focused on Azure data and AI workloads.

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