DP-090T00: Implementing a Machine Learning Solution with Microsoft Azure Databricks Course Overview

DP-090T00: Implementing a Machine Learning Solution with Microsoft Azure Databricks Course Overview

The DP-090T00: Implementing a Machine Learning Solution with Microsoft Azure Databricks course is designed to teach learners how to leverage Azure Databricks for big data analytics and integrate it with Azure Machine Learning to build, train, and deploy machine learning models. Throughout the course, participants gain hands-on experience in working with data, training models, managing experiments, and using MLflow and Azure Machine Learning for experiment tracking and model deployment.

By the end of this Azure Databricks training, students will be adept at using the platform for machine learning tasks, making them well-prepared for the Azure Databricks certification. The course is beneficial for data scientists, data engineers, and anyone interested in machine learning with a focus on practical application in the Azure ecosystem. Each module is structured with lessons that build upon one another, ensuring a comprehensive understanding of the subject matter.

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1. DP-100T01: Designing and Implementing a Data Science Solution on Azure "DP-090T00: Implementing a Machine Learning Solution with Microsoft Azure Databricks" and "DP-100T01: Designing and Implementing a Data Science Solution on Azure" are both focused on teaching the skills needed to implement data-driven solutions in Azure Read More

Course Prerequisites

To ensure that students can successfully undertake the DP-090T00: Implementing a Machine Learning Solution with Microsoft Azure Databricks course, the following minimum prerequisites are recommended:


  • Basic understanding of data science and machine learning concepts.
  • Familiarity with Python programming language, as it is commonly used in data science and machine learning tasks within Azure Databricks.
  • Knowledge of fundamental data processing and data analysis tasks.
  • Experience working with data in various formats (e.g., CSV, JSON) and using data processing libraries such as Pandas.
  • An introductory level of knowledge about big data and the use of distributed computing systems is helpful but not mandatory.
  • Some exposure to Azure services, specifically Azure Databricks, Azure Machine Learning, or similar cloud-based data processing and machine learning platforms.
  • Willingness to learn and experiment with new tools and techniques in a hands-on lab environment.

Please note that while having a strong background in these areas will be beneficial, the course is designed to guide learners through the necessary concepts and practices related to implementing machine learning solutions on Azure Databricks. Therefore, a keen interest in the subject matter and a willingness to engage with the course materials will also go a long way in ensuring a successful learning experience.


Target Audience for DP-090T00: Implementing a Machine Learning Solution with Microsoft Azure Databricks

The course DP-090T00 focuses on implementing ML solutions with Azure Databricks, ideal for IT professionals interested in data science and Azure technologies.


Target audience for the DP-090T00 course includes:


  • Data Scientists
  • Data Engineers
  • Machine Learning Engineers
  • AI Developers
  • IT Professionals with a focus on data analytics
  • Cloud Solutions Architects
  • DevOps Engineers focusing on machine learning workflows
  • Technical Team Leads managing data science projects
  • Software Developers looking to integrate machine learning into applications
  • Business Intelligence Professionals seeking to leverage Azure for advanced analytics


Learning Objectives - What you will Learn in this DP-090T00: Implementing a Machine Learning Solution with Microsoft Azure Databricks?

Introduction to Course Learning Outcomes

The DP-090T00 course equips learners with skills to implement machine learning solutions using Azure Databricks, track experiments, manage models, and integrate with Azure Machine Learning for advanced analytics.

Learning Objectives and Outcomes

  • Understand the fundamentals of Azure Databricks and its role in big data processing and machine learning.
  • Learn to ingest and manipulate data effectively within Azure Databricks environments.
  • Prepare and preprocess data for use in machine learning models.
  • Gain proficiency in training machine learning models using Azure Databricks.
  • Master the use of MLflow for experiment tracking and management within Azure Databricks.
  • Acquire skills to manage and version machine learning models effectively.
  • Learn to track machine learning experiments using Azure Machine Learning.
  • Develop expertise in deploying machine learning models into production within Azure Databricks and Azure Machine Learning.
  • Understand how to utilize Azure Machine Learning for running and managing machine learning experiments at scale.
  • Familiarize with best practices for integrating Azure Databricks with Azure Machine Learning to create end-to-end machine learning solutions.