Microsoft Azure

Skill Me Up Provides comprehensive Microsoft training for Data Specialists focusing on Microsoft Azure for Data Science, Big Data, Data Processing, Document Based or Relational Workloads.

Live Course Schedule
learning path
4 (87)
4 Lectures | 2 Labs | 8h 33m | Intermediate | Certification Prep

In this learning path, you will learn key concepts about the cloud and various Microsoft Azure Services. From there, you will learn core concepts such as various PaaS and IaaS services including management tools. This course will also cover several key concepts for security and compliance, as well as a brief look at a Azure pricing and support. This course will help you prepare for AZ 900 Microsoft Azure Fundamentals.

learning path
5 (17)
2 Lectures | 6 Labs | 15h 7m | Advanced

In this learning path, you will learn the fundamentals of Azure DataBricks and as new courses are added to the path you will progressively learn more advanced topics.

learning path
5 (5)
4 Lectures | 6 Labs | 22h 36m | Advanced

In this learning path, you will take a deep dive into Azure Cosmos DB, Throughout the path you will design documents and collections for real time implementations, create user-defined functions, stored procedures and triggers, tuning databases, monitoring performance along with troubleshooting techniques and best practices.

learning path
5 (10)
4 Lectures | 0 Labs | 5h 30m | Intermediate

In this learning path, you will learn the basics of data science including what data science is, some of the common programming languages used in data science (R and Python) as well as an introduction to machine learning.

learning path
4 (6)
3 Lectures | 6 Labs | 11h 23m | Intermediate | Certification Prep

This learning path contains a collection of courses and hands-on labs designed to help you pass the exam DP-200: Implementing an Azure Data Solution

learning path
5 (1)
3 Lectures | 0 Labs | 6h 24m | Intermediate | Certification Prep

This learning path contains a collection of courses and hands-on labs designed to help you pass the exam DP-201: Designing an Azure Data Solution

learning path
5 (9)
5 Lectures | 6 Labs | 7h 59m | Beginner | Certification Prep

In this this learning path you will explore Power BI Desktop and the the Power of PowerBI.com deploy datasets and reports as well as deploying, sharing, and securing assets in PowerBI.com. You will learn how to model data using DAX, as well as build reports and visualizations through on-demand courses and interactive hands-on labs.

learning path
5 (26)
3 Lectures | 2 Labs | 9h 11m | Advanced

In this learning path, you will learn how to implement Azure Database. Topics will include understanding to design and deploy databases using SQL DB and SQL Datawarehouse along with more advanced topics of performance and troubleshooting for SQL.

learning path
0 (0)
3 Lectures | 4 Labs | 8h | Intermediate | Certification Prep

This track has a collection of demonstrations, presentations, and interactive labs designed to prepare you for the Microsoft DP-100 exam.

lecture
0 (0)
5h 38m | Intermediate | Apr 12 2019 |

In this course, you will explore the Spark Internals and Architecture. The course will start with a brief introduction to Scala. Using the Scala programming language, you will be introduced to the core functionalities and use cases of Apache Spark including Spark SQL, Spark Streaming, MLlib, and GraphFrames.

lecture
5 (2)
1h 37m | Intermediate | Aug 12 2019 |

This course is an introduction to Microsoft Azure Machine Learning Services. In this course you will learn to navigate the AML Services interface, create notebook servers, create compute clusters, manage AML Services from a notebook, deploy models, and create an Automated Machine Learning experiment.

lecture
5 (3)
4h 42m | Advanced | Sep 15 2017 |

This course will be a deep dive into Azure SQL Database performance. We will look at designing an Azure SQL Database architecture for performance. We will look at performance specific features of Azure SQL Database. We will also cover monitoring and troubleshooting.

lecture
0 (0)
33m | Intermediate | Apr 3 2020 |

In this course, you will learn techniques for making your application scale and be ready for production. We’ll explore common troubleshooting techniques you can use for your application, as well discuss how to design for data concurrency. This course will also explore the Cosmos DB Change Feed feature for building event driven applications with Cosmos DB. Finally, the course will close on how to distribute your Cosmos backend globally using multiple Azure regions.

lecture
0 (0)
44m | Intermediate | Apr 3 2020 |

In this course, you will learn how to model data using the JSON based document model, and understand how data schemas are still applicable in Cosmos DB. From there, this course will take a look at one of the most important aspects of building a high-performance database and that is data partitioning.

lecture
5 (1)
1h 35m | Beginner | Mar 6 2020 |

In this course we will cover Data Modeling and the xVelocity Engine. We will also discuss DAX Basics along with Advanced DAX and optimizing the data model.

lecture
0 (0)
33m | Beginner | Mar 6 2020 |

This course will cover the basics of acquiringdata in Power BI Desktop andbuilds on the data acquisition basics and adds performance optimization and re-usability techniques.

lecture
0 (0)
Define and Prepare the Development Environment
Beginner | Coming Soon!

The student will learn how Azure services can support the data science process. They’ll explore common architectures, learn to assess business goals and constraints for determining the correct environment, and setup the relevant development environments to support data science deployments in Azure.

lecture
5 (1)
3h 6m | Intermediate | Nov 27 2019 |

In this course, students will gain knowledge and skills needed to design data storage solutions. Topics will include recommending the correct storage based on business and technical requirements, designing relational and non-relational cloud data stores. Specific focus points will be around data distribution, partitioning, designing for scale, high availability and disaster recovery on Cosmos DB, SQL Database, Azure Synapse Analytics, Data Lake Store Gen2 and Blob storage.

lecture
0 (0)
1h 57m | Intermediate | Oct 11 2019 |

This course covers designing of data processing solutions. We will look at leveraging Data Factory and Databricks and choosing optimal batch processing technology. The course will also include the design of real-time processing solutions with Stream Analytics and Azure Databricks.

lecture
0 (0)
1h 20m | Intermediate | Jan 20 2020 |

This course covers designing for data security and compliance. We will discuss securing source data access with endpoint security and authentication, securing data with encryption at rest and in transit. We will also cover data governance and compliance topics such as auditing, classification and data retention policies.

lecture
0 (0)
Developing Models
Beginner | Coming Soon!

The student will learn how develop robust models. Starting from selecting the right metric to meet business goals, through to building tuned models, and then evaluating the models produced for fitness.

lecture
5 (3)
2h 42m | Intermediate | Dec 30 2019 |

This course covers implementing Azure Data Storage services. We start off by reviewing Azure Portal and Storage concepts, then move on to implementing Azure SQL Data Warehouse, Azure SQL DB, Azure Data Lake, Azure Storage, and Azure Cosmos DB.

lecture
5 (7)
23m | Beginner | Aug 24 2016 |

In this hands-on course, students will learn about Azure SQL Data Warehouse. This course will review basic architecture of Azure SQL Data Warehouse. We will cover tools used with Azure SQL Data Warehouse, loading SQL Data Warehouse and basic workload management in SQL Data Warehouse.

lecture
5 (12)
1h 15m | Beginner | Sep 17 2016 |

In the course Introduction to Azure SQL Database we will discuss the configuration, performance, security, availability, recovery and automation of Azure SQL Database. We will also review hybrid solutions with SQL Server Stretch Database. This course will partially help prepare you for exam 70-473 Designing and Implementing Cloud Data Platform Solutions.This course will help you prepare for Microsoft Exam 70-533 - Implementing Azure Infrastructure Solutions and 70-532 Developing Azure Solutions as well.

lecture
5 (5)
45m | Beginner | Jan 14 2019 |

This course covers the necessary tools and concepts used in the data science industry to include machine learning, statistical inference, working with data at scale and much more.

lecture
5 (8)
54m | Intermediate | Jul 4 2018 |

This training provides an overview of Azure Databricks and Spark. In this course you will learn where Azure Databricks fits in the big data landscape in Azure. Key features of Azure Databricks such as Workspaces and Notebooks will be covered. Students will also learn the basic architecture of Spark and cover basic Spark internals including core APIs, job scheduling and execution. This class will prepare developers and administrators for more advanced work in Azure Databricks such as Python or Scala development.

lecture
5 (1)
32m | Beginner | Mar 6 2020 |

Welcome to this introduction to Power BI for data professionals. In this course, we will have an overview of the Power BI ecosystem. Then we will have a tour of Power BI Desktop.

lecture
5 (1)
1h 8m | Beginner | Sep 9 2019 |

This course is an introduction to Python. In this course you will learn which IDE is right for you, print statements, data types, control flow, Python functions and anonymous functions, methods, file io, and an introduction to Python packages.

lecture
5 (2)
1h 59m | Intermediate | Jul 2 2019 |

This course covers introduction to the R Language. We start off with an introduction to R verisons and R Editions then move to R the language. From there will dive into one of R’s strongest features, Graphics. Using base R graphics and GGPlot you will learn how to get started, and learn how to create your own visualizations.

lecture
5 (1)
56m | Beginner | Mar 6 2020 |

In this course we will discuss an overview of the Power BI Service. We will also cover sharing and securing your report and designing Enterprise Solutions in Power BI.

lecture
0 (0)
1h 28m | Intermediate | Jan 24 2020 |

This course covers configuring, managing and deploying Azure data processing solutions. We start with an overview of big data environments, including Hadoop clusters, then cover how to plan for and implement Azure Databricks, Azure Stream Analytics, Event Hubs, Azure Data Factory and how these fit with Azure Data Warehouse solutions.

lecture
0 (0)
52m | Intermediate | Feb 14 2020 |

This course covers configuring, managing and deploying monitoring for Azure Storage and data store solutions. We start with an overview of monitoring concepts, then focus on monitoring Azure Storage, Azure Data Lake, Azure Data Warehouse, Azure SQL DB and other services.

lecture
0 (0)
Performing Feature Engineering
Beginner | Coming Soon!

The student will learn how develop effective and reusable features ready for modeling. Using manual techniques and then automated techniques, the data scientist will be able to handle core data types using SciKit-Learn and Microsoft Python libraries like MMLSpark and Azure Machine Learning Data Prep SDK.

lecture
0 (0)
30m | Intermediate | Apr 3 2020 |

In this course, you will learn how to use the SQL API to write T-SQL like queries against your Cosmos DB collections. We’ll explore how partitioning and partition keys affect query performance and how to tune for faster results. This course will also explore how to write server-side queries, such as stored procedures, triggers, and user-defined functions.

lecture
5 (1)
36m | Beginner | Mar 9 2020 |

In this course you will learn about building interactive reports. We will also discuss helpful data visualization techniques in Power BI.

lecture
4 (4)
1h 1m | Beginner | Feb 12 2019 |

In this module, you will focus on pricing and support models available with Microsoft to include but not limited to Azure subscriptions, planning and managing costs, support options available with Azure, and the service lifecycle in Azure.

lecture
5 (13)
58m | Beginner | Feb 12 2019 |

In this module you will learn basic cloud concepts to include but not limited to the following: Why Cloud Services?, Infrastructure-as-a-Service (IaaS), Platform-as-a-Service (PaaS), Software-as-a-Service (SaaS), Public, Private, and Hybrid cloud models.

lecture
4 (4)
1h 32m | Beginner | Feb 12 2019 |

In this module, you will learn the basics of core services available within Microsoft Azure to include but not limited to Core Azure architectural components, Core Azure Services and Products, Azure Solutions, and Azure management tools.

lecture
4 (5)
2h 6m | Beginner | Feb 12 2019 |

In this module, you will learn about security, privacy, compliance, and trust with Microsoft Azure. You will become familiar with the following topics: securing network connectivity in Azure, core Azure identity services, security tools and features, Azure governance methodologies, monitoring and reporting in Azure, and privacy, compliance and data protection standards in Azure.

lecture
0 (0)
38m | Intermediate | Apr 2 2020 |

In this course, you will learn how the resource model works in Cosmos DB. We will discuss containers, databases, and understand how request units translates to the Cosmos DB billing model as well as how reserved capacity can be used to save on your Azure bill.

real-time lab
5 (1)
1h 15m | Beginner | Oct 10 2019 |

In this lab, you will provision how to provision a Databricks workspace, an Azure storage account, and a Spark cluster. You will learn to use the Spark cluster to explore data using Spark Resilient Distributed Datasets (RDDs) and Spark Dataframes.

real-time lab
0 (0)
4h | Intermediate | Feb 20 2019 |

In this lab, you will author and execute multiple stored procedures within your Azure Cosmos DB instance. You will explore features unique to JavaScript stored procedures such as throwing errors for transaction rollback, logging using the JavaScript console and implementing a continuation model within a bounded execution enviornment.

real-time lab
5 (1)
45m | Beginner | Mar 3 2020 |

In this lab, you will create a report that contains multiple visuals as well as text boxes and buttons. You will add bookmarks to allow users to see a particular view.

real-time lab
0 (0)
1h 30m | Intermediate | Jan 12 2020 |

The students will be able to describe and demonstrate the capabilities that Azure Cosmos DB can bring to an organization. They will be able to create a Cosmos DB instance and show how to upload and query data through a portal and through a .Net application. They will then be able to demonstrate how to enable global scale of the Cosmos DB database.

real-time lab
5 (2)
3h 20m | Advanced | Jan 17 2019 |

In this workshop, you will deploy a web app using Machine Learning Services to predict travel delays given flight delay data and weather conditions. Plan a bulk data import operation, followed by preparation, such as cleaning and manipulating the data for testing, and training your machine learning model.At the end of this workshop, you will be better able to build a complete machine learning model in Azure Databricks for predicting if an upcoming flight will experience delays. In addition, you will learn to store the trained model in Azure Machine Learning Model Management, then deploy to Docker containers for scalable on-demand predictions, use Azure Data Factory (ADF) for data movement and operationalizing ML scoring, summarize data with Azure Databricks and Spark SQL, and visualize batch predictions on a map using Power BI.

real-time lab
5 (1)
2h 55m | Advanced | Sep 26 2018 |

In this lab, you will learn techniques for troubleshooting and turning performance with a Cosmos DB database. You will learn about the different consistency levels Cosmos offers for your data, as well as work with different data partitioning strategies that impact the performance of your queries. From there, you will learn how to monitor the performance of your queries.

real-time lab
0 (0)
4h | Intermediate | Feb 20 2019 |

In this lab, you will create multiple Azure Cosmos DB containers. Some of the containers will be unlimited and configured with a partition key, while others will be fixed-sized. You will then use the SQL API and .NET SDK to query specific containers using a single partition key or across multiple partition keys.

real-time lab
0 (0)
5h | Intermediate | Jan 20 2020 |

In this hands-on lab, you will step through 10 exercises where you will use Azure Machine Learning to accomplish several tasks that are essential to the DP 100 Designing and Implementing a Data Science Solution on Azure exam.You will learn how to Create and Deploy a Training Pipeline, Run Experiments and Manage Models, understand how to work with data stores and data sets, work with environments and compute targets. create and configure a publishing pipeline, understand how to automate machine learning, as well as learn how to monitor with application insights and detect data drift.

real-time lab
0 (0)
1h | Beginner | Jan 11 2020 |

In this lab you will be able to explain why Azure Databricks can be used to help in Data Science projects. You will provision and Azure Databricks instance and will then create a workspace that will be used to perform a simple data preparation task from a Data Lake Store Gen II store. Finally, the student will perform a walk-through of performing transformations using Azure Databricks.

real-time lab
5 (1)
30m | Beginner | Mar 4 2020 |

In this lab, you will learn the basics of acquiring data using Power BI Desktop. You will import Excel files into Power BI Desktop and transform the data. You will use Power Query/M to connect to data sources such as SQL Databases, Excel files, text files, JSON files, and websites and then cleanand shape the data with Power Query/M.

real-time lab
4 (34)
1h 40m | Beginner | Oct 22 2019 |

In this lab, you will create a virtual network that will allow the virtual machines you create to securely connect with each other. You will then create two virtual machines and specify the virtual network configuration and the availability set configuration along with storage for the virtual machine.

real-time lab
5 (27)
1h 15m | Intermediate | Nov 26 2019 |

In this lab, you will create an Azure Web App and a SQL Database and configure the popular content management system (CMS) Orchard CMS. You will then configure the web app to automatically scale based on actual CPU usage.

real-time lab
5 (1)
1h 10m | Advanced | Apr 7 2020 |

In this lab, we will explore the use of columnstore indexes in Azure SQL Database. We will evaluate the performance improvements we get when we implement columnstore indexes on tables for with analytical workloads. 

real-time lab
5 (1)
1h | Beginner | Oct 10 2019 |

Spark structured streaming enables you to use the dataframe API to read and process an unbounded stream of data. This kind of processing is used in real-time scenarios to aggregate data over temporal intervals or windows. You can use Spark to process streaming data from a wide range of sources, including Azure Event Hubs, Kafka, and others. In this lab, you will run a Spark job to continually process a real-time stream of data.

real-time lab
5 (1)
40m | Beginner | Nov 28 2019 |

In this lab, you will learn the basics of importing CSV files into a Power BI model and adjusting query and column properties to prepare them for your data model. Then you will set table and column properties in the data model and create relationships between tables.

real-time lab
5 (1)
1h | Beginner | Oct 10 2019 |

Spark includes an API named Spark MLLib (often referred to as Spark ML), which you can use to create machine learning solutions. Machine learning is a technique in which you train a predictive model using a large volume of data so that when new data is submitted to the model it can predict unknown values. The most common types of machine learning are supervised learning and unsupervised learning. In a supervised learning scenario, you start with a large volume of data that includes both features (categorical and numeric values that describe characteristics of the entity you’re trying to predict something about) and labels (the value your model will predict. Training the model involves applying a statistical algorithm that fits the features to the labels. Because your initial data includes known values for the labels, you can train the model and test its accuracy with these known label values – giving you confidence that the model will work accurately with new data for which the label values aren’t known. Unsupervised learning is a technique in which there are no known label values, and the model is trained to group (or cluster) similar entities together based on their features.In this lab, we’ll focus on supervised learning; and specifically a type of machine learning called classification in which you train a model to identify which category, or class an entity belongs to. You will train a classifier to use features of flights that are enroute to an airport, and predict whether they will be late or on-time.

real-time lab
5 (3)
1h 40m | Intermediate | Feb 15 2019 |

In this lab, you will use PowerShell to manage Azure SQL Database. You will create a logical Azure SQL Server via PowerShell. You will then manage the firewall to allow remote connectivity to allow for client access. You will restore a database from an existing BACPAC file. Finally, you will use PowerShell to scale the database performance and pricing tier.

real-time lab
5 (4)
1h 15m | Beginner | Feb 1 2019 |

In this lab, you will learn how to configure and manage an Azure Cosmos DB Account (formerly Azure DocumentDB), including how to query and manage JSON documents within a Collection. Among the topics covered are using SQL language syntax to perform document queries that return JSON results, and implementing and testing global data replication and fail over.

real-time lab
5 (2)
1h | Beginner | Oct 10 2019 |

In this lab, you will provision how to provision a Databricks workspace, an Azure storage account, and a Spark cluster. You will then execute and manage a Spark Job.

real-time lab
5 (1)
30m | Beginner | Mar 3 2020 |

In this lab, you will import Excel and CSV files into Power BI Desktop and then merge queries, group data, and group queries in the query pane. It is common to have to pull data from transactional systems and shape them. It is also common to add data from other sources to provide a more complete picture.First, you will stage the data from the multiple sources. Then you will merge and group data to get final reporting tables to be used in Power BI. Then you will disable staging queries. Finally, you will organize your queries into folders for better organization.

real-time lab
0 (0)
1h 15m | Intermediate | Jan 12 2020 |

In this module, you will learn how Azure Data factory can be used to orchestrate the data movement from a wide range of data platform technologies. You will be able to explain the capabilities of the technology and be able to set up an end to end data pipeline that ingests data from SQL Database and load the data into SQL Data Warehouse. You will also demonstrate how to call a compute resource.

real-time lab
4 (1)
45m | Intermediate | Jan 12 2020 |

The students will be able to describe what data streams are and how event processing works and choose an appropriate data stream ingestion technology for the AdventureWorks case study. They will provision the chosen ingestion technology and integrate this with Stream Analytics to create a solution that works with streaming data.

real-time lab
5 (1)
30m | Beginner | Mar 3 2020 |

In this lab, you will implement basic row-level security in Power BI Desktop and PowerBI.com. First, you will create roles on a model in Power BI and add filters for each role. Then you will deploy the model and test the row-level security in PowerBI.com. Then you will add members to the role in PowerBI.com.

real-time lab
0 (0)
4h | Intermediate | Feb 20 2019 |

In this lab, you will query an Azure Cosmos DB database instance using the SQL language. You will use features common in SQL such as projection using SELECT statements and filtering using WHERE clauses. You will also get to use features unique to Azure Cosmos DB’s SQL API such as projection into JSON, intra-document JOIN and filtering to a range of partition keys.

real-time lab
0 (0)
4h | Intermediate | Feb 20 2019 |

In this lab, you will use the .NET SDK to tune an Azure Cosmos DB request to optimize performance of your application.

real-time lab
0 (0)
1h | Beginner | Oct 8 2019 |

In this lab, you want to see if there are models that perform better than the one you might manually create. You decide to use Azure Machine Learning service’s AutoML and HyperDrive to simultaneously execute a number of different types of classification models, compare the results, and recommend the best performing model. This will save you a lot of time picking the best model so you can get the solution delivered sooner.

real-time lab
0 (0)
50m | Beginner | Nov 28 2019 |

In this lab, you will learn the basics of time intelligence measures to show year-to-date, quarter-to-date, and month-to-date totals. Then you will use DAX to enhance the data model and build a table that lets users choose which measures they want to see.

real-time lab
5 (2)
45m | Beginner | Jan 11 2020 |

In this lab, you will create Azure storage accounts and Data Lake Storage account and explain the difference between Data Lake Storage version 1 and version 2. You will also demonstrate how to perform data loads into the data storage of choice.

real-time lab
0 (0)
1h 5m | Intermediate | Jan 12 2020 |

The students will be able to provision an Azure SQL Database and Azure Synapse Analytics server and be able to issue queries against one of the instances that are created. They will be also be able to integrate a data warehouse with a number of other data platform technologies and use PolyBase to load data from one data source into Azure Synapse Analytics.

learning path
4 (87)
4 Lectures | 2 Labs | 8h 33m | Intermediate | Certification Prep

In this learning path, you will learn key concepts about the cloud and various Microsoft Azure Services. From there, you will learn core concepts such as various PaaS and IaaS services including management tools. This course will also cover several key concepts for security and compliance, as well as a brief look at a Azure pricing and support. This course will help you prepare for AZ 900 Microsoft Azure Fundamentals.

learning path
5 (17)
2 Lectures | 6 Labs | 15h 7m | Advanced

In this learning path, you will learn the fundamentals of Azure DataBricks and as new courses are added to the path you will progressively learn more advanced topics.

learning path
5 (5)
4 Lectures | 6 Labs | 22h 36m | Advanced

In this learning path, you will take a deep dive into Azure Cosmos DB, Throughout the path you will design documents and collections for real time implementations, create user-defined functions, stored procedures and triggers, tuning databases, monitoring performance along with troubleshooting techniques and best practices.

learning path
5 (10)
4 Lectures | 0 Labs | 5h 30m | Intermediate

In this learning path, you will learn the basics of data science including what data science is, some of the common programming languages used in data science (R and Python) as well as an introduction to machine learning.

learning path
4 (6)
3 Lectures | 6 Labs | 11h 23m | Intermediate | Certification Prep

This learning path contains a collection of courses and hands-on labs designed to help you pass the exam DP-200: Implementing an Azure Data Solution

learning path
5 (1)
3 Lectures | 0 Labs | 6h 24m | Intermediate | Certification Prep

This learning path contains a collection of courses and hands-on labs designed to help you pass the exam DP-201: Designing an Azure Data Solution

learning path
5 (9)
5 Lectures | 6 Labs | 7h 59m | Beginner | Certification Prep

In this this learning path you will explore Power BI Desktop and the the Power of PowerBI.com deploy datasets and reports as well as deploying, sharing, and securing assets in PowerBI.com. You will learn how to model data using DAX, as well as build reports and visualizations through on-demand courses and interactive hands-on labs.

learning path
5 (26)
3 Lectures | 2 Labs | 9h 11m | Advanced

In this learning path, you will learn how to implement Azure Database. Topics will include understanding to design and deploy databases using SQL DB and SQL Datawarehouse along with more advanced topics of performance and troubleshooting for SQL.

learning path
0 (0)
3 Lectures | 4 Labs | 8h | Intermediate | Certification Prep

This track has a collection of demonstrations, presentations, and interactive labs designed to prepare you for the Microsoft DP-100 exam.

lecture
0 (0)
5h 38m | Intermediate | Apr 12 2019 |

In this course, you will explore the Spark Internals and Architecture. The course will start with a brief introduction to Scala. Using the Scala programming language, you will be introduced to the core functionalities and use cases of Apache Spark including Spark SQL, Spark Streaming, MLlib, and GraphFrames.

lecture
5 (2)
1h 37m | Intermediate | Aug 12 2019 |

This course is an introduction to Microsoft Azure Machine Learning Services. In this course you will learn to navigate the AML Services interface, create notebook servers, create compute clusters, manage AML Services from a notebook, deploy models, and create an Automated Machine Learning experiment.

lecture
5 (3)
4h 42m | Advanced | Sep 15 2017 |

This course will be a deep dive into Azure SQL Database performance. We will look at designing an Azure SQL Database architecture for performance. We will look at performance specific features of Azure SQL Database. We will also cover monitoring and troubleshooting.

lecture
0 (0)
33m | Intermediate | Apr 3 2020 |

In this course, you will learn techniques for making your application scale and be ready for production. We’ll explore common troubleshooting techniques you can use for your application, as well discuss how to design for data concurrency. This course will also explore the Cosmos DB Change Feed feature for building event driven applications with Cosmos DB. Finally, the course will close on how to distribute your Cosmos backend globally using multiple Azure regions.

lecture
0 (0)
44m | Intermediate | Apr 3 2020 |

In this course, you will learn how to model data using the JSON based document model, and understand how data schemas are still applicable in Cosmos DB. From there, this course will take a look at one of the most important aspects of building a high-performance database and that is data partitioning.

lecture
5 (1)
1h 35m | Beginner | Mar 6 2020 |

In this course we will cover Data Modeling and the xVelocity Engine. We will also discuss DAX Basics along with Advanced DAX and optimizing the data model.

lecture
0 (0)
33m | Beginner | Mar 6 2020 |

This course will cover the basics of acquiringdata in Power BI Desktop andbuilds on the data acquisition basics and adds performance optimization and re-usability techniques.

lecture
0 (0)
Define and Prepare the Development Environment
Beginner | Coming Soon!

The student will learn how Azure services can support the data science process. They’ll explore common architectures, learn to assess business goals and constraints for determining the correct environment, and setup the relevant development environments to support data science deployments in Azure.

lecture
5 (1)
3h 6m | Intermediate | Nov 27 2019 |

In this course, students will gain knowledge and skills needed to design data storage solutions. Topics will include recommending the correct storage based on business and technical requirements, designing relational and non-relational cloud data stores. Specific focus points will be around data distribution, partitioning, designing for scale, high availability and disaster recovery on Cosmos DB, SQL Database, Azure Synapse Analytics, Data Lake Store Gen2 and Blob storage.

lecture
0 (0)
1h 57m | Intermediate | Oct 11 2019 |

This course covers designing of data processing solutions. We will look at leveraging Data Factory and Databricks and choosing optimal batch processing technology. The course will also include the design of real-time processing solutions with Stream Analytics and Azure Databricks.

lecture
0 (0)
1h 20m | Intermediate | Jan 20 2020 |

This course covers designing for data security and compliance. We will discuss securing source data access with endpoint security and authentication, securing data with encryption at rest and in transit. We will also cover data governance and compliance topics such as auditing, classification and data retention policies.

lecture
0 (0)
Developing Models
Beginner | Coming Soon!

The student will learn how develop robust models. Starting from selecting the right metric to meet business goals, through to building tuned models, and then evaluating the models produced for fitness.

lecture
5 (3)
2h 42m | Intermediate | Dec 30 2019 |

This course covers implementing Azure Data Storage services. We start off by reviewing Azure Portal and Storage concepts, then move on to implementing Azure SQL Data Warehouse, Azure SQL DB, Azure Data Lake, Azure Storage, and Azure Cosmos DB.

lecture
5 (7)
23m | Beginner | Aug 24 2016 |

In this hands-on course, students will learn about Azure SQL Data Warehouse. This course will review basic architecture of Azure SQL Data Warehouse. We will cover tools used with Azure SQL Data Warehouse, loading SQL Data Warehouse and basic workload management in SQL Data Warehouse.

lecture
5 (12)
1h 15m | Beginner | Sep 17 2016 |

In the course Introduction to Azure SQL Database we will discuss the configuration, performance, security, availability, recovery and automation of Azure SQL Database. We will also review hybrid solutions with SQL Server Stretch Database. This course will partially help prepare you for exam 70-473 Designing and Implementing Cloud Data Platform Solutions.This course will help you prepare for Microsoft Exam 70-533 - Implementing Azure Infrastructure Solutions and 70-532 Developing Azure Solutions as well.

lecture
5 (5)
45m | Beginner | Jan 14 2019 |

This course covers the necessary tools and concepts used in the data science industry to include machine learning, statistical inference, working with data at scale and much more.

lecture
5 (8)
54m | Intermediate | Jul 4 2018 |

This training provides an overview of Azure Databricks and Spark. In this course you will learn where Azure Databricks fits in the big data landscape in Azure. Key features of Azure Databricks such as Workspaces and Notebooks will be covered. Students will also learn the basic architecture of Spark and cover basic Spark internals including core APIs, job scheduling and execution. This class will prepare developers and administrators for more advanced work in Azure Databricks such as Python or Scala development.

lecture
5 (1)
32m | Beginner | Mar 6 2020 |

Welcome to this introduction to Power BI for data professionals. In this course, we will have an overview of the Power BI ecosystem. Then we will have a tour of Power BI Desktop.

lecture
5 (1)
1h 8m | Beginner | Sep 9 2019 |

This course is an introduction to Python. In this course you will learn which IDE is right for you, print statements, data types, control flow, Python functions and anonymous functions, methods, file io, and an introduction to Python packages.

lecture
5 (2)
1h 59m | Intermediate | Jul 2 2019 |

This course covers introduction to the R Language. We start off with an introduction to R verisons and R Editions then move to R the language. From there will dive into one of R’s strongest features, Graphics. Using base R graphics and GGPlot you will learn how to get started, and learn how to create your own visualizations.

lecture
5 (1)
56m | Beginner | Mar 6 2020 |

In this course we will discuss an overview of the Power BI Service. We will also cover sharing and securing your report and designing Enterprise Solutions in Power BI.

lecture
0 (0)
1h 28m | Intermediate | Jan 24 2020 |

This course covers configuring, managing and deploying Azure data processing solutions. We start with an overview of big data environments, including Hadoop clusters, then cover how to plan for and implement Azure Databricks, Azure Stream Analytics, Event Hubs, Azure Data Factory and how these fit with Azure Data Warehouse solutions.

lecture
0 (0)
52m | Intermediate | Feb 14 2020 |

This course covers configuring, managing and deploying monitoring for Azure Storage and data store solutions. We start with an overview of monitoring concepts, then focus on monitoring Azure Storage, Azure Data Lake, Azure Data Warehouse, Azure SQL DB and other services.

lecture
0 (0)
Performing Feature Engineering
Beginner | Coming Soon!

The student will learn how develop effective and reusable features ready for modeling. Using manual techniques and then automated techniques, the data scientist will be able to handle core data types using SciKit-Learn and Microsoft Python libraries like MMLSpark and Azure Machine Learning Data Prep SDK.

lecture
0 (0)
30m | Intermediate | Apr 3 2020 |

In this course, you will learn how to use the SQL API to write T-SQL like queries against your Cosmos DB collections. We’ll explore how partitioning and partition keys affect query performance and how to tune for faster results. This course will also explore how to write server-side queries, such as stored procedures, triggers, and user-defined functions.

lecture
5 (1)
36m | Beginner | Mar 9 2020 |

In this course you will learn about building interactive reports. We will also discuss helpful data visualization techniques in Power BI.

lecture
4 (4)
1h 1m | Beginner | Feb 12 2019 |

In this module, you will focus on pricing and support models available with Microsoft to include but not limited to Azure subscriptions, planning and managing costs, support options available with Azure, and the service lifecycle in Azure.

lecture
5 (13)
58m | Beginner | Feb 12 2019 |

In this module you will learn basic cloud concepts to include but not limited to the following: Why Cloud Services?, Infrastructure-as-a-Service (IaaS), Platform-as-a-Service (PaaS), Software-as-a-Service (SaaS), Public, Private, and Hybrid cloud models.

lecture
4 (4)
1h 32m | Beginner | Feb 12 2019 |

In this module, you will learn the basics of core services available within Microsoft Azure to include but not limited to Core Azure architectural components, Core Azure Services and Products, Azure Solutions, and Azure management tools.

lecture
4 (5)
2h 6m | Beginner | Feb 12 2019 |

In this module, you will learn about security, privacy, compliance, and trust with Microsoft Azure. You will become familiar with the following topics: securing network connectivity in Azure, core Azure identity services, security tools and features, Azure governance methodologies, monitoring and reporting in Azure, and privacy, compliance and data protection standards in Azure.

lecture
0 (0)
38m | Intermediate | Apr 2 2020 |

In this course, you will learn how the resource model works in Cosmos DB. We will discuss containers, databases, and understand how request units translates to the Cosmos DB billing model as well as how reserved capacity can be used to save on your Azure bill.

real-time lab
5 (1)
1h 15m | Beginner | Oct 10 2019 |

In this lab, you will provision how to provision a Databricks workspace, an Azure storage account, and a Spark cluster. You will learn to use the Spark cluster to explore data using Spark Resilient Distributed Datasets (RDDs) and Spark Dataframes.

real-time lab
0 (0)
4h | Intermediate | Feb 20 2019 |

In this lab, you will author and execute multiple stored procedures within your Azure Cosmos DB instance. You will explore features unique to JavaScript stored procedures such as throwing errors for transaction rollback, logging using the JavaScript console and implementing a continuation model within a bounded execution enviornment.

real-time lab
5 (1)
45m | Beginner | Mar 3 2020 |

In this lab, you will create a report that contains multiple visuals as well as text boxes and buttons. You will add bookmarks to allow users to see a particular view.

real-time lab
0 (0)
1h 30m | Intermediate | Jan 12 2020 |

The students will be able to describe and demonstrate the capabilities that Azure Cosmos DB can bring to an organization. They will be able to create a Cosmos DB instance and show how to upload and query data through a portal and through a .Net application. They will then be able to demonstrate how to enable global scale of the Cosmos DB database.

real-time lab
5 (2)
3h 20m | Advanced | Jan 17 2019 |

In this workshop, you will deploy a web app using Machine Learning Services to predict travel delays given flight delay data and weather conditions. Plan a bulk data import operation, followed by preparation, such as cleaning and manipulating the data for testing, and training your machine learning model.At the end of this workshop, you will be better able to build a complete machine learning model in Azure Databricks for predicting if an upcoming flight will experience delays. In addition, you will learn to store the trained model in Azure Machine Learning Model Management, then deploy to Docker containers for scalable on-demand predictions, use Azure Data Factory (ADF) for data movement and operationalizing ML scoring, summarize data with Azure Databricks and Spark SQL, and visualize batch predictions on a map using Power BI.

real-time lab
5 (1)
2h 55m | Advanced | Sep 26 2018 |

In this lab, you will learn techniques for troubleshooting and turning performance with a Cosmos DB database. You will learn about the different consistency levels Cosmos offers for your data, as well as work with different data partitioning strategies that impact the performance of your queries. From there, you will learn how to monitor the performance of your queries.

real-time lab
0 (0)
4h | Intermediate | Feb 20 2019 |

In this lab, you will create multiple Azure Cosmos DB containers. Some of the containers will be unlimited and configured with a partition key, while others will be fixed-sized. You will then use the SQL API and .NET SDK to query specific containers using a single partition key or across multiple partition keys.

real-time lab
0 (0)
5h | Intermediate | Jan 20 2020 | | Pausable for 72 hours

In this hands-on lab, you will step through 10 exercises where you will use Azure Machine Learning to accomplish several tasks that are essential to the DP 100 Designing and Implementing a Data Science Solution on Azure exam.You will learn how to Create and Deploy a Training Pipeline, Run Experiments and Manage Models, understand how to work with data stores and data sets, work with environments and compute targets. create and configure a publishing pipeline, understand how to automate machine learning, as well as learn how to monitor with application insights and detect data drift.

real-time lab
0 (0)
1h | Beginner | Jan 11 2020 |

In this lab you will be able to explain why Azure Databricks can be used to help in Data Science projects. You will provision and Azure Databricks instance and will then create a workspace that will be used to perform a simple data preparation task from a Data Lake Store Gen II store. Finally, the student will perform a walk-through of performing transformations using Azure Databricks.

real-time lab
5 (1)
30m | Beginner | Mar 4 2020 |

In this lab, you will learn the basics of acquiring data using Power BI Desktop. You will import Excel files into Power BI Desktop and transform the data. You will use Power Query/M to connect to data sources such as SQL Databases, Excel files, text files, JSON files, and websites and then cleanand shape the data with Power Query/M.

real-time lab
4 (34)
1h 40m | Beginner | Oct 22 2019 |

In this lab, you will create a virtual network that will allow the virtual machines you create to securely connect with each other. You will then create two virtual machines and specify the virtual network configuration and the availability set configuration along with storage for the virtual machine.

real-time lab
5 (27)
1h 15m | Intermediate | Nov 26 2019 |

In this lab, you will create an Azure Web App and a SQL Database and configure the popular content management system (CMS) Orchard CMS. You will then configure the web app to automatically scale based on actual CPU usage.

real-time lab
5 (1)
1h 10m | Advanced | Apr 7 2020 |

In this lab, we will explore the use of columnstore indexes in Azure SQL Database. We will evaluate the performance improvements we get when we implement columnstore indexes on tables for with analytical workloads. 

real-time lab
5 (1)
1h | Beginner | Oct 10 2019 |

Spark structured streaming enables you to use the dataframe API to read and process an unbounded stream of data. This kind of processing is used in real-time scenarios to aggregate data over temporal intervals or windows. You can use Spark to process streaming data from a wide range of sources, including Azure Event Hubs, Kafka, and others. In this lab, you will run a Spark job to continually process a real-time stream of data.

real-time lab
5 (1)
40m | Beginner | Nov 28 2019 |

In this lab, you will learn the basics of importing CSV files into a Power BI model and adjusting query and column properties to prepare them for your data model. Then you will set table and column properties in the data model and create relationships between tables.

real-time lab
5 (1)
1h | Beginner | Oct 10 2019 |

Spark includes an API named Spark MLLib (often referred to as Spark ML), which you can use to create machine learning solutions. Machine learning is a technique in which you train a predictive model using a large volume of data so that when new data is submitted to the model it can predict unknown values. The most common types of machine learning are supervised learning and unsupervised learning. In a supervised learning scenario, you start with a large volume of data that includes both features (categorical and numeric values that describe characteristics of the entity you’re trying to predict something about) and labels (the value your model will predict. Training the model involves applying a statistical algorithm that fits the features to the labels. Because your initial data includes known values for the labels, you can train the model and test its accuracy with these known label values – giving you confidence that the model will work accurately with new data for which the label values aren’t known. Unsupervised learning is a technique in which there are no known label values, and the model is trained to group (or cluster) similar entities together based on their features.In this lab, we’ll focus on supervised learning; and specifically a type of machine learning called classification in which you train a model to identify which category, or class an entity belongs to. You will train a classifier to use features of flights that are enroute to an airport, and predict whether they will be late or on-time.

real-time lab
5 (3)
1h 40m | Intermediate | Feb 15 2019 |

In this lab, you will use PowerShell to manage Azure SQL Database. You will create a logical Azure SQL Server via PowerShell. You will then manage the firewall to allow remote connectivity to allow for client access. You will restore a database from an existing BACPAC file. Finally, you will use PowerShell to scale the database performance and pricing tier.

real-time lab
5 (4)
1h 15m | Beginner | Feb 1 2019 |

In this lab, you will learn how to configure and manage an Azure Cosmos DB Account (formerly Azure DocumentDB), including how to query and manage JSON documents within a Collection. Among the topics covered are using SQL language syntax to perform document queries that return JSON results, and implementing and testing global data replication and fail over.

real-time lab
5 (2)
1h | Beginner | Oct 10 2019 |

In this lab, you will provision how to provision a Databricks workspace, an Azure storage account, and a Spark cluster. You will then execute and manage a Spark Job.

real-time lab
5 (1)
30m | Beginner | Mar 3 2020 |

In this lab, you will import Excel and CSV files into Power BI Desktop and then merge queries, group data, and group queries in the query pane. It is common to have to pull data from transactional systems and shape them. It is also common to add data from other sources to provide a more complete picture.First, you will stage the data from the multiple sources. Then you will merge and group data to get final reporting tables to be used in Power BI. Then you will disable staging queries. Finally, you will organize your queries into folders for better organization.

real-time lab
0 (0)
1h 15m | Intermediate | Jan 12 2020 |

In this module, you will learn how Azure Data factory can be used to orchestrate the data movement from a wide range of data platform technologies. You will be able to explain the capabilities of the technology and be able to set up an end to end data pipeline that ingests data from SQL Database and load the data into SQL Data Warehouse. You will also demonstrate how to call a compute resource.

real-time lab
4 (1)
45m | Intermediate | Jan 12 2020 |

The students will be able to describe what data streams are and how event processing works and choose an appropriate data stream ingestion technology for the AdventureWorks case study. They will provision the chosen ingestion technology and integrate this with Stream Analytics to create a solution that works with streaming data.

real-time lab
5 (1)
30m | Beginner | Mar 3 2020 |

In this lab, you will implement basic row-level security in Power BI Desktop and PowerBI.com. First, you will create roles on a model in Power BI and add filters for each role. Then you will deploy the model and test the row-level security in PowerBI.com. Then you will add members to the role in PowerBI.com.

real-time lab
0 (0)
4h | Intermediate | Feb 20 2019 |

In this lab, you will query an Azure Cosmos DB database instance using the SQL language. You will use features common in SQL such as projection using SELECT statements and filtering using WHERE clauses. You will also get to use features unique to Azure Cosmos DB’s SQL API such as projection into JSON, intra-document JOIN and filtering to a range of partition keys.

real-time lab
0 (0)
4h | Intermediate | Feb 20 2019 |

In this lab, you will use the .NET SDK to tune an Azure Cosmos DB request to optimize performance of your application.

real-time lab
0 (0)
1h | Beginner | Oct 8 2019 |

In this lab, you want to see if there are models that perform better than the one you might manually create. You decide to use Azure Machine Learning service’s AutoML and HyperDrive to simultaneously execute a number of different types of classification models, compare the results, and recommend the best performing model. This will save you a lot of time picking the best model so you can get the solution delivered sooner.

real-time lab
0 (0)
50m | Beginner | Nov 28 2019 |

In this lab, you will learn the basics of time intelligence measures to show year-to-date, quarter-to-date, and month-to-date totals. Then you will use DAX to enhance the data model and build a table that lets users choose which measures they want to see.

real-time lab
5 (2)
45m | Beginner | Jan 11 2020 |

In this lab, you will create Azure storage accounts and Data Lake Storage account and explain the difference between Data Lake Storage version 1 and version 2. You will also demonstrate how to perform data loads into the data storage of choice.

real-time lab
0 (0)
1h 5m | Intermediate | Jan 12 2020 |

The students will be able to provision an Azure SQL Database and Azure Synapse Analytics server and be able to issue queries against one of the instances that are created. They will be also be able to integrate a data warehouse with a number of other data platform technologies and use PolyBase to load data from one data source into Azure Synapse Analytics.