Microsoft DP-3014 - Build Machine Learning Solutions using Azure Databricks

What you’ll learn

After completing this course, students will be able to:

• Provision an Azure Databricks workspace

• Identify core workloads and personas for Azure Databricks

• Describe key concepts of an Azure Databricks solution

• Describe key elements of the Apache Spark architecture

• Create and configure a Spark cluster

• Describe use cases for Spark

• Use Spark to process and analyse data stored in files

• Use Spark to visualise data

• Prepare data for machine learning

• Train a machine learning model

• Evaluate a machine learning model

• Use MLflow to log parameters, metrics, and other details from experiment runs

• Use MLflow to manage and deploy trained models

• Use the Hyperopt library to optimise hyperparameters

• Distribute hyperparameter tuning across multiple worker nodes

• Use the AutoML user interface in Azure Databricks

• Use the AutoML API in Azure Databricks

• Train a deep learning model in Azure Databricks

• Distribute deep learning training by using the Horovod library

Microsoft Azure at Lumify Work

As part of Lumify Group, Lumify Work has skilled more people in Microsoft technologies than any other organisation in Australia and New Zealand. We have a campus in the Philippines, too. We offer the broadest range of instructor-led training courses, from end user to architect level.  We are proud to be the winner of the Microsoft MCT Superstars Award for FY24, which formally recognises us as having the highest quality Microsoft Certified Trainers in ANZ. 

View all Microsoft Azure at Lumify Work courses

Who is the course for?

This course is designed for aspiring data scientists and AI engineers who need to train and manage machine learning models by using Azure Databricks.

Prerequisites

• Experience using Python to explore data and train machine learning models with common open source frameworks, like Scikit-Learn, PyTorch, and TensorFlow. 

Terms & Conditions

The supply of this course by Lumify Work is governed by the booking terms and conditions. Please read the terms and conditions carefully before enrolling in this course, as enrolment in the course is conditional on acceptance of these terms and conditions.