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Data Professional
Skill Me Up expert on-demand training for Security Professional. Modernize your skills with cloud computing from providers such as Microsoft Azure, Amazon Web Services and much more along with core foundational IT training.
8 Results
Learning Path
0 (0)
10 Lectures
0 Labs
Intermediate

This learning path contains a collection of OpenEdx courses designed to teach you about Artificial Intelligence.

Learning Path
4 (4)
1 Lectures
1 Labs
5h 3m
Intermediate

In this learning path, you will learn how to use services such as Power BI and Spark to surface, process and analyze data to generate intelligence to make more well informed business decisions.

Learning Path
4 (37)
3 Lectures
7 Labs
15h 6m
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
4 (46)
5 Lectures
5 Labs
17h 22m
Intermediate

In this learning path, you will learn how to build and architect big data solutions in Microsoft Azure. Topics will include architecting solutions using HD Insight, machine learning, visualizing data with Power BI, understanding lambda architecture patterns and IoT data ingestion. This path will help you prepare for exam Designing and Implementing Big Data Platform Solutions - exam 70-475 and will help you prepare for your MIcrosoft certification.

Learning Path
4 (73)
4 Lectures
6 Labs
19h 49m
Advanced

In this learning path, you will learn how to build and architect SQL focused solutions in Microsoft Azure. Topics will include SQL Server in Azure IaaS, SQL Database and SQL Data warehouse. This course will help you prepare for exam 70-473 Implementing Cloud Data Platform Solutions and prepare for your Microsoft certification.

Learning Path
5 (19)
1 Lectures
9 Labs
1 day, 1h 2m
Intermediate

In this learning path you will find courses and Real Time Labs to help you learn Microsoft Azure Cosmos DB.

Learning Path
5 (6)
1 Lectures
6 Labs
8h 49m
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
4 (9)
2 Lectures
4 Labs
6h 54m
Advanced

In this learning path, you will learn from the fundamentals of SQL Server relational databases to advanced capabilities,

34 Results
Lecture
3 (11)
Feb 15 2018
Beginner
1h 39m
Peter De Tender

In this module, attendees will learn how to design solutions using Azure Infrastructure as a Service Components. This module will focus on core capabilities, use cases, and general best practices as well as discuss peripheral services such as Azure Backup and Site Recovery.

Lecture
3 (8)
Mar 6 2017
Intermediate
2h 48m
Jen Stirrup

This course gives you an introduction to Azure Machine Learning (ML) and associated technologies, such as R, Power BI and RStudio. This course begins by covering an introduction to Azure ML, and then we walk through Azure ML as if we were working our way through a Data Science Project. Once the Data Science project is complete, we will look at how you can set up and report on the Azure ML modelling process with Power BI.

Lecture
5 (3)
Sep 15 2017
Advanced
4h 42m
Paul Burpo

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
5 (10)
Apr 17 2017
Intermediate
2h 2m
Paul Burpo

This module will cover all aspects of big data storage and batch processing. We will start by making the case for big data in Azure. Then we will look at Azure service topics to include Blob Storage, Azure Data Lake Store, Azure Data Lake Analytics, and HDInsight clusters running Hadoop, Hive, Interactive Hive (LLAP) and Spark. Storage topics will focus on choosing the right storage, configuring storage and storage optimization. We will also cover Big Data scenarios including batch processing, interactive clusters, multi-cluster deployments and on-demand clusters.

Lecture
Jan 31 2019
Intermediate
Opsgility

This course is part of the Microsoft Professional Program in Artificial Intelligence.Computer Vision is the art of distilling actionable information from images.In this hands-on course, we'll learn about Image Analysis techniques using OpenCV and the Microsoft Cognitive Toolkit to segment images into meaningful parts. We'll explore the evolution of Image Analysis, from classical to Deep-Learning techniques.We'll use Transfer Learning and Microsoft ResNet to train a model to perform Semantic Segmentation.

Lecture
Jan 31 2019
Intermediate
Opsgility

This course is part of the Microsoft Professional Program Certificate in Data Science and Microsoft Professional Program in Artificial Intelligence.Data scientists are often trained in the analysis of data. However, the goal of data science is to produce a good understanding of some problem or idea and build useful models on this understanding. Because of the principle of "garbage in, garbage out,"it is vital that a data scientist know how to evaluate the quality of information that comes into a data analysis. This is especially the case when data are collected specifically for some analysis (e.g., a survey).In this course, you will learn the fundamentals of the research process—from developing a good question to designing good data collection strategies to putting results in context. Although a data scientist may often play a key part in data analysis, the entire research process must work cohesively for valid insights to be gleaned.Developed as a powerful and flexible language used in everything from Data Science to cutting-edge and scalable Artificial Intelligence solutions, Python has become an essential tool for doing Data Science and Machine Learning. With this edition of Data Science Research Methods, all of the labs are done with Python, while the videos are language-agnostic. If you prefer your Data Science to be done with R, please see Data Science Research Methods: R Edition.

Lecture
Jan 31 2019
Intermediate
Opsgility

This course is part of the Microsoft Professional Program in Artificial Intelligence.achine learning uses computers to run predictive models that learn from existing data to forecast future behaviors, outcomes, and trends. Deep learning is a sub-field of machine learning, where models inspired by how our brain works are expressed mathematically, and the parameters defining the mathematical models, which can be in the order of few thousands to 100+ million, are learned automatically from the data.Deep learning is a key enabler of AI powered technologies being developed across the globe. In this deep learning course, you will learn an intuitive approach to building complex models that help machines solve real-world problems with human-like intelligence. The intuitive approaches will be translated into working code with practical problems and hands-on experience. You will learn how to build and derive insights from these models using Python Jupyter notebooks running on your local Windows or Linux machine, or on a virtual machine running on Azure. Alternatively, you can leverage the Microsoft Azure Notebooks platform for free.This course provides the level of detail needed to enable engineers / data scientists / technology managers to develop an intuitive understanding of the key concepts behind this game changing technology. At the same time, you will learn simple yet powerful "motifs" that can be used with lego-like flexibility to build an end-to-end deep learning model. You will learn how to use the Microsoft Cognitive Toolkit — previously known as CNTK — to harness the intelligence within massive datasets through deep learning with uncompromised scaling, speed, and accuracy.

Lecture
Jan 31 2019
Intermediate
Opsgility

This course is part of the Microsoft Professional Program Certificate in Data Science and Microsoft Professional Program in Artificial Intelligence.Corporations, governments, and individuals have powerful tools in Analytics and AI to create real-world outcomes, for good or for ill.Data professionals today need both the frameworks and the methods in their job to achieve optimal results while being good stewards of their critical role in society today.In this course, you'll learn to apply ethical and legal frameworks to initiatives in the data profession. You'll explore practical approaches to data and analytics problems posed by work in Big Data, Data Science, and AI. You'll also investigate applied data methods for ethical and legal work in Analytics and AI.

Lecture
5 (1)
Mar 19 2019
Beginner
1h 29m
Tim Bitzer

The course will teach you the fundamentals of the relational database model and how to access data stored in relational databases. The course will give students an understanding of relational database concepts and teach the practical application of these concepts through the T-SQL programming language for Microsoft SQL Server and Azure SQL Database.

Lecture
Aug 30 2017
Beginner
Opsgility

In this course, you will learn fundamental database concepts for Microsoft SQL Server 2016, including database types, database languages and database designs.This course incorporates material from the Official Microsoft Learning Product 10985: Introduction to SQL Databases.

Lecture
Aug 30 2017
Intermediate
Opsgility

Update your SQL Server skills with this introduction to the new features of SQL Server 2016. You’ll learn the new features for performance, security, availability and scalability, reporting and Power BI, data access, and SQL Server OLAP, and you’ll learn about new SQL Server cloud functionality.

Lecture
Aug 30 2017
Intermediate
Opsgility

In this course you will learn how to implement a SQL Server 2016 Reporting Services solution for data analysis in an organization. You will discover how to use the Reporting Services development tools to create and manage reports and implement self-service BI solutions.

Lecture
Jan 23 2018
Beginner
Opsgility

This course is designed to introduce students to Transact-SQL. It is designed in such a way that the first three days can be taught as a course to students requiring the knowledge for other courses in the SQL Server curriculum.

Lecture
Aug 30 2017
Intermediate
Opsgility

In this course, professionals who administer and maintain SQL Server databases and who develop applications that deliver content from SQL Server databases will gain the knowledge and skills to administer a SQL server database infrastructure.This course incorporates material from the Official Microsoft Learning Product 20764: Administering a SQL Database Infrastructure and can assist you in preparing for the 70-764: Administering a SQL Database Infrastructure exam.

Lecture
Aug 30 2017
Intermediate
Opsgility

This course provides you with the knowledge and skills to provision a Microsoft SQL Server 2016 database. You will cover SQL Server 2016 provision both on-premise and in Azure, and you’ll cover installing from new and migrating from an existing install.This course incorporates material from the Official Microsoft Learning Product 20765: Provisioning SQL Databases, and it can assist you in your preparation for Exam 70-765: Provisioning SQL Databases

Lecture
Aug 30 2017
Intermediate
Opsgility

In this course, you will learn how to implement a data warehouse platform to support a business intelligence (BI) solution. You will discover how to create a data warehouse, how to implement extract, transform, and load (ETL) with SQL Server Integration Services (SSIS), and how to validate and cleanse data with Data Quality Services (DQS) and Master Data Services.This course incorporates material from the Official Microsoft Learning Product 20767: and it can assist you in your preparation for Exam 70-767: Implementing a SQL Data Warehouse.

Lecture
Aug 30 2017
Intermediate
Opsgility

In this course, you will learn about business intelligence (BI) solutions that implement multidimensional databases and create tabular semantic data models for analysis using SQL Server Analysis Services (SSAS).

Lecture
Sep 4 2017
Advanced
Opsgility

This is a custom 3-day SQL Server 2016 training course. This 400 level course covers In-Memory OLTP, Column store Indexing, Real-time Analytics, Query Store, JSON data in SQL Server and Extended Events with Availability Groups.

Lecture
Jan 31 2019
Beginner
Opsgility

This course is part of the Microsoft Professional Program in Artificial Intelligence.Artificial Intelligence will define the next generation of software solutions. This computer science course provides an overview of AI, and explains how it can be used to build smart apps that help organizations be more efficient and enrich people’s lives. It uses a mix of engaging lectures and hands-on activities to help you take your first steps in the exciting field of AI.Discover how machine learning can be used to build predictive models for AI. Learn how software can be used to process, analyze, and extract meaning from natural language; and to process images and video to understand the world the way we do. Find out how to build intelligent bots that enable conversational communication between humans and AI systems.

Lecture
5 (9)
Sep 21 2017
Beginner
57m
Chris Pietschmann

This course explores the NoSQL storage options available within the Microsoft Azure Cosmos DB database service. Formerly DocumentDB, Azure Cosmos DB is no longer just a Document-based NoSQL store, and it includes support for all 4 primary NoSQL data models (Document, Graph, Key/Value, Column). In addition to learning about NoSQL with Cosmos DB, students will also learn about the cloud-native features that make Cosmos DB a great NoSQL database-as-a-service in the Microsoft Azure cloud.

Lecture
5 (7)
Aug 24 2016
Beginner
23m
Paul Burpo

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 (11)
Sep 17 2016
Beginner
1h 15m
Paul Burpo

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 (1)
Oct 30 2018
Beginner
50m
Paul Burpo

This course introduces students to Azure Data Factory V2. Students will learn about the different phases of a Data Factory Pipeline. Students will then cover Data Factory Architecture, terminology, the copy activity, file formats, integration runtimes, scheduling and triggers, and data factory management.

Lecture
5 (4)
Jul 4 2018
Intermediate
54m
Paul Burpo

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
Jan 31 2019
Intermediate
Opsgility

This course is part of the Microsoft Professional Program Certificate in Data Science and Microsoft Professional Program in Artificial Intelligence.Python is a very powerful programming language used for many different applications. Over time, the huge community around this open source language has created quite a few tools to efficiently work with Python. In recent years, a number of tools have been built specifically for data science. As a result, analyzing data with Python has never been easier.In this practical course, you will start from the very beginning, with basic arithmetic and variables, and learn how to handle data structures, such as Python lists, Numpy arrays, and Pandas DataFrames. Along the way, you’ll learn about Python functions and control flow. Plus, you’ll look at the world of data visualizations with Python and create your own stunning visualizations based on real data.

Lecture
Jan 31 2019
Intermediate
Opsgility

This course is part of the Microsoft Professional Program in Artificial Intelligence.Natural language processing (NLP) is one of the most important technologies of the information age. Understanding complex language utterances is also a crucial part of artificial intelligence.In this course, you will be given a thorough overview of Natural Language Processing and how to use classic machine learning methods. You will learn about Statistical Machine Translation as well as Deep Semantic Similarity Models (DSSM) and their applications.We will also discuss deep reinforcement learning techniques applied in NLP and Vision-Language Multimodal Intelligence.

Lecture
5 (10)
Apr 23 2017
Intermediate
1h 8m
Paul Burpo

This module will provide an overview of big data, IoT and machine learning solutions in Azure. We will define the meaning of big data and look at the reasons why you might need a big data solution. We will then move on to a discussion of the analytics maturity model to understand how machine learning extracts value from big data. Next, we will review the lambda architecture which is the dominant architecture for big data solutions. We will look at the Azure components used in big data solutions and how they fit together to build an end-to-end lambda architecture in Azure. Finally, we will wrap up with a discussion of the Cortana Intelligence Suite and the value that it brings to big data and analytics solutions in Azure.

Lecture
4 (3)
May 9 2018
Beginner
1h 33m
Paul Burpo

This course builds on your Power BI skills and walks you through the interfaces of both the Online and Desktop offerings before embarking on a journey that will show you how to ingest data, transform data, create reports and dashboards before publishing and using your data sets, reports and dashboards in the Power BI online tenant.The course will help prepare students to take the Microsoft 70-778, Analyzing and Visualizing Data with Power BI certification exam.

Lecture
Jan 31 2019
Intermediate
Opsgility

This course is part of the Microsoft Professional Program Certificate in Data Science and Microsoft Professional Program in Artificial Intelligence.Machine learning uses computers to run predictive models that learn from existing data in order to forecast future behaviors, outcomes, and trends.In this data science course, you will be given clear explanations of machine learning theory combined with practical scenarios and hands-on experience building, validating, and deploying machine learning models. You will learn how to build and derive insights from these models using Python, and Azure Notebooks.

Lecture
5 (9)
Jan 4 2017
Intermediate
43m
Chris Pietschmann

The Real-Time Ingestion and Processing in Azure course covers information about implementing real-time event stream ingestion and processing within Microsoft Azure. The course starts with an overview of the Lambda Architecture and what a Message Broker is used for. The course continues to cover the Azure Event Hubs and Azure IoT Hub services used for event stream ingestion, and Azure Stream Analytics and HDInsight for integrating real-time event processing. Finally, the course finishes with an overview of a few example architectures to give a better perspective on architecting Real-Time Ingestion and Processing solutions within the Microsoft Azure cloud. This course should help in preparation for the 70-534 exam, Architecting Microsoft Azure Solutions.

Lecture
Jan 31 2019
Intermediate
Opsgility

This course is part of the Microsoft Professional Program in Artificial Intelligence.Reinforcement Learning (RL) is an area of machine learning, where an agent learns by interacting with its environment to achieve a goal.In this course, you will be introduced to the world of reinforcement learning. You will learn how to frame reinforcement learning problems and start tackling classic examples like news recommendation, learning to navigate in a grid-world, and balancing a cart-pole.You will explore the basic algorithms from multi-armed bandits, dynamic programming, TD (temporal difference) learning, and progress towards larger state space using function approximation, in particular using deep learning. You will also learn about algorithms that focus on searching the best policy with policy gradient and actor critic methods. Along the way, you will get introduced to Project Malmo, a platform for Artificial Intelligence experimentation and research built on top of the Minecraft game.

Lecture
Jan 31 2019
Intermediate
Opsgility

This course is part of the Microsoft Professional Program in Artificial Intelligence.Developing and understanding Automatic Speech Recognition (ASR) systems is an inter-disciplinary activity, taking expertise in linguistics, computer science, mathematics, and electrical engineering.When a human speaks a word, they cause their voice to make a time-varying pattern of sounds. These sounds are waves of pressure that propagate through the air. The sounds are captured by a sensor, such as a microphone or microphone array, and turned into a sequence of numbers representing the pressure change over time. The automatic speech recognition system converts this time-pressure signal into a time-frequency-energy signal. It has been trained on a curated set of labeled speech sounds, and labels the sounds it is presented with. These acoustic labels are combined with a model of word pronunciation and a model of word sequences, to create a textual representation of what was said.Instead of exploring one part of this process deeply, this course is designed to give an overview of the components of a modern ASR system. In each lecture, we describe a component's purpose and general structure. In each lab, the student creates a functioning block of the system. At the end of the course, we will have built a speech recognition system almost entirely out of Python code.

Lecture
4 (5)
Feb 23 2017
Advanced
2h 44m
Joseph D'Antoni

This course covers In-Memory OLTP, Columnstore Indexing, Real-time Analytics, Query Store, JSON data in SQL Server and Extended Events with Availability Groups.

Lecture
5 (7)
May 9 2017
Intermediate
2h 19m
Paul Burpo

In this hands-on course, students will learn about running SQL Server in Azure. This course will review basic Azure networking and storage using the Azure Resource Manager architecture to prepare students for building SQL Server solutions in Azure. The primary focus of this course is SQL Server cloud and hybrid-cloud solutions on Azure Infrastructure as a Service (IaaS). This course will cover best practices for deploying SQL Server on Azure Virtual Machines including standalone SQL Servers and hybrid Availability Groups. The course will look at SQL Server features that take advantage of Azure Storage such as SQL Server Managed Backup, Azure Snapshot Backups, and SQL Server data files hosted on Azure Storage.

34 Results
Real-Time Lab
5 (1)
Feb 4 2018
Intermediate
3h 30m
Opsgility

In this lab, you will learn to build powerful dashboards and reports in Power BI. You will learn to take advantage of advanced data analytics features of Power BI such as DAX queries, KPIs and R scripts.

Real-Time Lab
0 (0)
Apr 4 2019
Beginner
1h 15m
Opsgility

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)
Feb 20 2019
Intermediate
4h
Opsgility

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
0 (0)
Jan 17 2019
Advanced
2h 40m
Opsgility

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
0 (0)
Feb 21 2019
Intermediate
1h 45m
Opsgility

In this lab, you will create an Azure Data Lake Store Gen2 account. You will learn to lock down and manage access of the Data Lake Store, taking advantage of both role-based access control and Data Lake Store Azure AD integration. Finally, you will process a bulk ingest using Hadoop distcp utility.

Real-Time Lab
5 (1)
Sep 26 2018
Intermediate
2h 55m
Opsgility

In this lab, you will learn techniques for troubleshooting and turning performance with a Cosmos DB database.

Real-Time Lab
0 (0)
Feb 20 2019
Intermediate
4h
Opsgility

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
4 (6)
Apr 2 2019
Beginner
1h 15m
Opsgility

In this lab you will create an Azure SQL Database using the Azure Portal and connect to it using SQL Server Management Studio. You will then migrate a SQL Server database hosted on a virtual machine to an Azure SQL Database.

Real-Time Lab
5 (2)
May 4 2018
Beginner
1h 15m
Opsgility

Today, data is being collected in ever-increasing amounts, at ever-increasing velocities, and in an ever-expanding variety of formats. This explosion of data is colloquially known as the Big Data phenomenon.In order to gain actionable insights into big-data sources, new tools need to be leveraged that allow the data to be cleaned, analyzed, and visualized quickly and efficiently. Azure HDInsight provides a solution to this problem by making it exceedingly simple to create high-performance computing clusters provisioned with Apache Spark and members of the Spark ecosystem. Rather than spend time deploying hardware and installing, configuring, and maintaining software, you can focus on your research and apply your expertise to the data rather than the resources required to analyze that data.Apache Spark is an open-source parallel-processing platform that excels at running large-scale data analytics jobs. Spark’s combined use of in-memory and disk data storage delivers performance improvements that allow it to process some tasks up to 100 times faster than Hadoop. With Microsoft Azure, deploying Apache Spark clusters becomes significantly simpler and gets you working on your data analysis that much sooner.In this lab, you will experience HD Insight with Spark first-hand. After provisioning a Spark cluster, you will use the Microsoft Azure Storage Explorer to upload several Jupyter notebooks to the cluster. You will then use these notebooks to explore, visualize, and build a machine-learning model from food-inspection data — more than 100,000 rows of it — collected by the city of Chicago. The goal is to learn how to create and utilize your own Spark clusters, experience the ease with which they are provisioned in Azure, and, if you're new to Spark, get a working introduction to Spark data analytics.

Real-Time Lab
5 (1)
Aug 22 2018
Intermediate
2h 20m
Paul Burpo

In this lab, you will learn to build, monitor, manage and troubleshoot data pipelines with Azure Data Factory V2. You will learn to use the Copy Data wizard to build pipeline with no coding. You will build a custom pipeline to copy data from Blob storage to a table in Azure SQL Database. You will build a tumbling window pipeline to pick up data on a daily basis. Finally, you will learn to use the Management Monitoring tools to troubleshoot pipeline failures.

Real-Time Lab
5 (3)
Oct 10 2018
Intermediate
2h
Real-Time Lab
4 (27)
Feb 14 2019
Beginner
1h 50m
Opsgility

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 (1)
Sep 19 2017
Advanced
1h 10m
Paul Burpo

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
0 (0)
Sep 19 2017
Intermediate
1h 10m
Paul Burpo

In this lab, you will explore real-time operational analytics using Azure SQL Database. You will evaluate the performance improvements you will get when you add updateable non-clustered columnstore indexes on top of standard tables as well as memory-optimized tables.

Real-Time Lab
5 (1)
Jan 10 2018
Intermediate
40m
Edwin M Sarmiento

In this lab, you will explore the new SQL Server 2016 real-time operational analytics feature. You will evaluate the performance improvements you will get when you add updateable nonclustered columnstore indexes on top of disk-based tables as well as memory-optimized tables.

Real-Time Lab
4 (1)
Jan 10 2018
Intermediate
40m
Edwin M Sarmiento

In this lab, you will explore columnstore indexes in SQL Server 2016. You will evaluate the performance improvements you will get when you implement columnstore indexes on tables for your analytical workloads.

Real-Time Lab
0 (0)
Jan 4 2019
Beginner
1h
Opsgility

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
0 (0)
Sep 19 2017
Intermediate
1h 20m
Paul Burpo

In this lab, we will examine the use of In-Memory OLTP in Azure SQL Database. We will compare performance across standard and in-memory architectures including memory optimized tables and natively compiled stored procedures.

Real-Time Lab
5 (1)
Apr 2 2019
Intermediate
40m
Edwin M Sarmiento

In this lab, you will explore the new SQL Server 2016 In-Memory OLTP feature. You will evaluate the performance improvements you will get when you migrate disk-based tables and interpreted T-SQL stored procedures into memory-optimized tables and natively-compiled stored procedures, respectively.

Real-Time Lab
5 (1)
Sep 23 2018
Intermediate
45m
Opsgility

In this lab you will leverage the Azure Portal to create an instance of Azure Cosmos DB with SQL API. You will use the Data Explorer feature to create a database, create a collection and add documents to your collection. Next you will configure a Java application to connect to your Cosmos DB instance, create databases, create collections and query documents in the collection.

Real-Time Lab
5 (3)
May 23 2018
Intermediate
2h 10m
Chris Pietschmann

In this lab, you will use Visual Studio and ASP.NET to learn how to use Cosmos DB as a backend for an MVC application. You will learn how to programmatically read and write data, create and call a user-defined functions as well as understand management capabilities such as users and permissions, monitoring and scalability options.

Real-Time Lab
5 (2)
Sep 13 2018
Intermediate
45m
Opsgility

In this lab, you will deploy and configure an on-premises gateway to work with Azure Logic Apps. The on-premises data gateway acts as a bridge, providing quick and secure data transfer between on-premises data (data that is not in the cloud) and the Power BI, Microsoft Flow, Logic Apps, and PowerApps services.

Real-Time Lab
0 (0)
Jan 4 2019
Beginner
1h
Opsgility

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 (4)
Oct 10 2018
Intermediate
2h 5m
Paul Burpo

In this lab, you learn about leveraging Azure storage with SQL Server. We will cover hosting data files directly from Azure Storage, backup to URL and snapshot backups.

Real-Time Lab
5 (3)
Feb 15 2019
Intermediate
1h 40m
Opsgility

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)
Feb 1 2019
Beginner
1h 15m
Opsgility

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 (4)
Oct 10 2018
Advanced
1h 25m
Paul Burpo

In this lab, we will walk through management and monitoring of an Elastic Pool. First, we will create an Elastic Pool and add our databases to the pool. Then we will monitor the performance of our pool using TSQL Scripts and the Azure Portal.

Real-Time Lab
0 (0)
Apr 5 2019
Intermediate
40m
Edwin M Sarmiento

In this lab, you will configure and manage the query store in SQL Server 2016 to collect runtime statistics, queries, query plan history and other workload history within the database to assist with troubleshooting query performance issues, you will then identify and resolve poor performing queries in your database using SQL Server 2016 Query Store. You will also identify query plan regressions and how to address them with information gathered from the Query Store.

Real-Time Lab
5 (1)
Jan 4 2019
Beginner
1h
Opsgility

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
0 (0)
Feb 20 2019
Intermediate
4h
Opsgility

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
5 (1)
Sep 26 2018
Intermediate
1h
Cloud Trainer

In this lab you will learn to use Cosmos DB and Azure Databricks to build real-time stream processing solution. You will use a pre-built application to read the Twitter data stream into Cosmos DB. You will then configure Azure Databricks to be able to read the change feed of your Cosmos DB collection and you will use Scala to process the data and visualize the data stream in a Databricks Notebook.

Real-Time Lab
5 (1)
Apr 13 2018
Intermediate
2h 10m
Paul Burpo

In this lab, you learn about deploying SQL Server on Azure virtual machines. This lab will walk you through some common setup and configuration tasks for running SQL Server in Azure infrastructure as a service.

Real-Time Lab
0 (0)
Feb 20 2019
Intermediate
4h
Opsgility

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
5 (4)
Aug 3 2018
Beginner
1h
Paul Burpo

In this lab, you will build a machine learning experiment using Azure Machine Learning. You will start by creating a Machine Learning Workspace in the Azure Portal. You will then login to ML Studio where you will import an external dataset, clean the dataset, choose a machine learning algorithm and train your model. Finally, you will score and evaluate your model to determine its accuracy.

9 Results
Instructor-Led Course
3 Days
Beginner
Opsgility

In this course, you will learn fundamental database concepts for Microsoft SQL Server 2016, including database types, database languages and database designs.This course incorporates material from the Official Microsoft Learning Product 10985: Introduction to SQL Databases.

Instructor-Led Course
3 Days
Intermediate
Opsgility

Update your SQL Server skills with this introduction to the new features of SQL Server 2016. You’ll learn the new features for performance, security, availability and scalability, reporting and Power BI, data access, and SQL Server OLAP, and you’ll learn about new SQL Server cloud functionality.

Instructor-Led Course
2 Days
Intermediate
Opsgility

In this course you will learn how to implement a SQL Server 2016 Reporting Services solution for data analysis in an organization. You will discover how to use the Reporting Services development tools to create and manage reports and implement self-service BI solutions.

Instructor-Led Course
5 Days
Beginner
Opsgility

This course is designed to introduce students to Transact-SQL. It is designed in such a way that the first three days can be taught as a course to students requiring the knowledge for other courses in the SQL Server curriculum.

Instructor-Led Course
5 Days
Intermediate
Opsgility

In this course, professionals who administer and maintain SQL Server databases and who develop applications that deliver content from SQL Server databases will gain the knowledge and skills to administer a SQL server database infrastructure.This course incorporates material from the Official Microsoft Learning Product 20764: Administering a SQL Database Infrastructure and can assist you in preparing for the 70-764: Administering a SQL Database Infrastructure exam.

Instructor-Led Course
5 Days
Intermediate
Opsgility

This course provides you with the knowledge and skills to provision a Microsoft SQL Server 2016 database. You will cover SQL Server 2016 provision both on-premise and in Azure, and you’ll cover installing from new and migrating from an existing install.This course incorporates material from the Official Microsoft Learning Product 20765: Provisioning SQL Databases, and it can assist you in your preparation for Exam 70-765: Provisioning SQL Databases

Instructor-Led Course
5 Days
Intermediate
Opsgility

In this course, you will learn how to implement a data warehouse platform to support a business intelligence (BI) solution. You will discover how to create a data warehouse, how to implement extract, transform, and load (ETL) with SQL Server Integration Services (SSIS), and how to validate and cleanse data with Data Quality Services (DQS) and Master Data Services.This course incorporates material from the Official Microsoft Learning Product 20767: and it can assist you in your preparation for Exam 70-767: Implementing a SQL Data Warehouse.

Instructor-Led Course
3 Days
Intermediate
Opsgility

In this course, you will learn about business intelligence (BI) solutions that implement multidimensional databases and create tabular semantic data models for analysis using SQL Server Analysis Services (SSAS).

Instructor-Led Course
3 Days
Advanced
Opsgility

This is a custom 3-day SQL Server 2016 training course. This 400 level course covers In-Memory OLTP, Column store Indexing, Real-time Analytics, Query Store, JSON data in SQL Server and Extended Events with Availability Groups.