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This is the final course of the AI-100 Exam Preparation Learning Path.In this course, we will discuss how to implement various technologies for processing and ingesting your information,we will discuss how to implement Cognitive Services into your application and tie in Cognitive Search to your solution, andwe will discuss tools available for auditing and monitoring plus how to analyze an AI solution and migrate it to another solution if it does not meet requirements.
In this lab, you will create an Azure Web App in the portal and add a staging slot. Then, using Visual Studio you will create a .Net application. You will read environmental variables from a file, then remove the dependency on that file with application settings in Azure. You will view default logs using log streaming in Azure and then create custom log messages in the application. You will explore slot deployment by deploying these changes to Stage and then swapping them to Production.
This is the second course of the AI-100 Exam Preparation Learning Path.In this course, we will discuss how to analyze the different business scenarios and translate them into different tools available,we will design a solution using Cognitive Services, we will discuss various use cases related to bot services and LUIS and discuss how to design a solution using these technologies,we will discuss the various High Performance Computing solutions that rely on computer infrastructure within the cloud, on-premises, and within hybrid scenarios, andwe will discuss security, compliance, and governance as it pertains to designing an AI solution in the cloud.
Azure Management Groups enable many of Azure’s governance and reporting features to be centrally managed using an organization-wide hierarchy, rather than being managed on each individual subscription. This enables an efficient and reliable approach to implementing governance at scale across an organization.In this class, you will learn how to design and build a management group hierarchy, and how to use management groups to implement governance and reporting across an organization.
Many teams prefer to define their build and release pipelines using YAML (Yet Another Markup Language). This allows them to access the same pipeline features as those using the visual designer, but with a markup file that can be managed like any other source file. YAML build definitions can be added to a project by simply adding their source file to the root of the repository. Azure DevOps also provides default templates for popular project types, as well as a YAML designer to simplify the process of defining build and release tasks. In this lab, you will learn how to configure continuous integration (CI) and continuous deployment (CD) for your applications using Build and Release in Azure Pipelines.
The course will educate you on securing data within Office 365, by implement protections used to encrypt data, as well as restrict end user capabilities. The course will also walk-through the implementation and management of Cloud App Security protections.
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.
Role-based access control is a fundamental pillar of good governance in Azure. Properly deployed, it enables an organization to control how users access and administer the organization’s Azure resources, implementing a ‘least privilege’ model in which users have only the permissions they need, to only the resources they need. This course provides a deep-dive into role-based access control in Azure. The course starts by explaining how user and system identities are managed in Azure AD, and how Azure roles are defined. It then explains how roles can be assigned, and how multiple role assignments interact. Finally, the course shows how you can implement tailored access control policies by creating and assigning your own custom role definitions.
In this lab, you will learn how to make direct calls to the Azure Resource Manager REST API. There are various different tools available to make these API calls Each exercise focuses on a different tool, and on different features of the REST API.
Cost management and cost optimization are key concerns of all Azure customers. In this class, students will first learn the principles of how Azure accounts are managed and billed. Next, students learn how a variety of commonly-used IaaS and PaaS resources are priced. This is followed by a deep-dive on cost optimization techniques you can to reduce your bill without impacting your applications. Finally, the class includes a deep-dive on Azure Cost Management, which enables you to track, analyze and forecast your Azure spend to providing accurate cost estimates and reduced billing risk.
In this lab, you will learn how to manage Users and Groups using both MSOnline and AzureAD PowerShell Modules. You will create, manage and remove both users and groups, followed by managing permissions within Azure Active Directory.
This course will provide an overview of how to use features within Teams such as chat, online meetings, calls and more. Learn the core features of Teams and how it relates to other Office 365 apps to make your team more productive.
In this lab, you will learn about the agile planning and portfolio management tools and processes provided by Azure Boards and how they can help you quickly plan, manage, and track work across your entire team. You will explore the product backlog, sprint backlog, and task boards which can be used to track the flow of work during the course of an iteration.
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.
Students will learn the fundamentals about Cloud App Security to gain visibility around all your cloud apps and services.Security is a primary goal for any organization, in this course the attendees will learn about the threat management to protect their environment and to monitor it using the cloud platform tools. This training will prepare it's audiences for, MS-101: Microsoft 365 Mobility and Security exam.
Students will learn about the modern workplace philosophy and how to embrace it, evolving the company paradigm into a flexible environment which allows collaboration while maintaining the security principals and improving the business through the adoption of the new platforms and concepts.
Students will learn how to prevent scenarios where leaked information could cause damage to their organizations, by gaining the ability to create, publish, and apply labels to documents. Students will learn to set the retention policies to those documents to be compliant with regulations that apply to their organizations.This training will prepare it's audiences for, MS-101: Microsoft 365 Mobility and Security exam.
This course introduces you to the key components of Office 365 and then focuses on what it takes to move your organization to Office 365. You will spend time learning how to plan an Office 365 deployment.It will also cover the design and planning tools and top to handle on-prem and cloud workloads and have a whole support platform to work based on the business requirements.
This course will cover the management of authentication and authorization services in Azure Active Directory and Microsoft 365. It will include concepts of authentication process on-prem and the design best practices for a successful business migration.Multi-Factor Authentication and Application access will also be part of the content to provide a complete picture of these features and their usage on authentication and authorization, covering internal and external requests and providing a full understanding of the service.
In this course, you will learn learn how to manage user security groups and licenses for cloud identities, and how to plan and implement identity synchronization, federated identities, applications, and external access.This course focuses on the management tasks for identity and role administration from the Microsoft 365 platform perspective to cover security, compliance and supporting roles; it will also elaborate on tips for monitoring the integration and hybrid services used on identity management.
In this hands-on lab, you will learn how to configure client and end-user devices for Office 365. You will learn how to set device access rules using the Microsoft Online Services PowerShell module, plus learn how to perform an automated installation of Office 365 ProPlus. The lab wraps up on installing the Microsoft Support and Recovery assistant so you understand how to trouble shoot common deployment issues.
In this lab, you will verify the networking configuration of an Ubuntu VM. You will login to a live virtual machine running Ubuntu Linux and explore several networking commands to provide more insight into the virtual machine's network configuration.
In this lab, you will learn how to install the Microsoft Teams application, create your first Team, and then explore the Microsoft Team's Admin Center. From there, you will get some hands-on practice managing Teams and Channels.
This course will mainly cover connectivity. You will learn all about the main protocol that makes networking on the internet and most organizations work. TCP/IP isn’t the only protocol, but it is the most important and most often used. It’s also the main protocol used in in the Network+ certification exam.
This course covers LAN and WAN topics, we will discuss what happens to packets as they traverse the network. We will also cover TCP/IP classes and what they mean to connectivity. We will finish with discussing WAN technologies both past and present. We will discuss analog and digital connectivity and the various ways ISP’s connect us to the internet.
This course dives into the Presentation layer of the OSI model and discusses port traffic. Ports are also known as doors and act as doorways in and out of a network. Understanding how to open or close a port and why is a great asset to have in your knowledge of networking.
This course covers wireless networking also described as WIFI. We will learn about the wireless standards and protocols, and types of security that wireless entails.
This course answers questions on encryption. What encryption is and the different forms it takes in networking. We also discuss certificates and what roles they play in TCP/IP. By encrypting our data, we secure our data. Security plays an ever-important roles in networking today.
This course will cover advanced networking a high-end consultant might implement in their day to day job in networks and security. We cover splitting up networks into virtual LANs, encrypting the stream using virtual private networks, and devices that can inform us of an impending intrusion.
This course will discuss cloud and mobile devices. Many companies are moving their data to the cloud and networking is essential to that process. Questions about what the cloud is and how it works are answered in this course, along with mobile connectivity using cellular networks and security.
This course gives you a working demonstration of setting up a real-world network using computers, switches and servers. We will discuss the different ways that the networks can be connected to the host devices and show how they communicate.
This course covers physical connectivity of networking. Cables need to plug in both sides, but there’s many types of cables, standards, and ways to connect. This course will review these various ways to connect your network using physical cabling.
In this course, we discusses real world tools both software and hardware. These tools help to connect and troubleshoot networks, so data runs smoothly, and we will discuss repairs when they don’t.
This course covers the track contents and how it is organized. It also introduces you to the AWS certification and how it is organized.
This course gives a high-level introduction to CloudWatch, monitoring EC2, EBS, ELB and Elasticache and services with a brief description for each service to get you acquainted to the offerings.
This course covers Elasticity vs Scalability and the core concepts behind both. In addition, it explores various cost optimization methods, as well as scaling up vs scaling out.
This course covers the entirety of the High Availability question domain. We will go through several services and explain how they can be used as HA design elements, and discuss the operations required to implement each service. Understanding trade-offs is an important element of HA design and we cover few examples of service and feature choice based on requirement.
This course is a comprehensive coverage of S3 Lifecycle and Encryption. The course also covers AWS Security Token Service and shared responsibility model.
This course will go over security assessment services and how to ensure compliance from a security perspective.
This course covers different network services in AWS and cover the operations required over time for each.
This course covers building your own custom VPC.
This course covers the concept of automation in AWS. There are several ways to automate tasks in the AWS ecosystem. We go over each of these services and describe how each can be used to implement frequently-performed tasks.
In this lab we'll guide you through the steps to deploy a request splitting ambassador that will split 10% of the incoming HTTP requests to an experimental server and the rest to a primary web server using Azure Kubernetes Service (AKS). This pattern is commonly used for testing new features or user experience to a small subset of users.
In this lab, you will learn to use a Managed Identity with Azure PowerShell by creating a virtual machine with a system managed identity. You will then assign the identity to a resource group using role-based access control (RBAC).
In this lab, you will provision an Azure Web App and App Service Plan. Then, you will configure a "Staging" Deployment Slot and deploy source code to it from a Github repository. Finally, you will perform a deployment slot swap to push the code deployment from Staging into Production.
In this course, you will deep dive into the Azure Policy service, which is one of the fundamental governance services in Azure. You will learn how to apply Azure Policy to your subscriptions and the wide range of scenarios it supports. You will also deep dive on the policy definition language, so you can fully understand built-in policies and create your own custom policies. You will also learn how to use Azure Policy compliance reports, and how to investigate and remediate non-compliant resources. The course closes with an overview of Azure VM guest policy and overall policy management best practices.
In this lab, you will create a Linux virtual machine running in Azure, and connect to it using SSH. You will then delete the virtual machine, and clean up associated resources.
In this lab, you will create a Windows virtual machine running in Azure, and connect to it using Remote Desktop. You will then delete the virtual machine, and clean up associated resources.
In this lab, you will get started with Azure Key Vault to create a hardened container (a vault) in Azure, to store and manage cryptographic keys and secrets in Azure. First you will use Azure PowerShell. Then you will store a password as a secret that could then be used with an Azure application.
In this lab, you learn how to configure virtual networking peering.Virtual network peering enables you to seemlessly connect two Azure virtual networks. Once peered, the virtual networks appear as one, for connectivity purposes. The traffic between virtual machines in the peered virtual networks is routed through the Microsoft backbone infrastructure, much like traffic is routed between virtual machines in the same virtual network, through private IP addresses only.Note 1: This lab will connect two virtual networks within the same region. Peering across regions is currently in preview.Note 2: If you want a more in-depth view of virtual network connectivity (including site-to-site and point-to-site) try the Introduction to Virtual Network Connectivity lab.
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.
The course will educate you implementing and managing identity and access within Microsoft 365. Starting with securing a Hybrid configuration, which focuses on selecting the correct authentication option and user account controls. It will also walk-through implementing conditional access policies for allowing and controlling access to the Microsoft 365 services, to implementing identity and privileged account protections using Azure Active Directory Privileged Identity Management and Azure Active Directory Identity Protection.
You are the leader of a group of climate scientists who are concerned about the dwindling polar-bear population in the Arctic. As such, your team has placed hundreds of motion-activated cameras at strategic locations throughout the region. Rather than manually examine each photograph to determine whether it contains a polar bear, you have been challenged to devise an automated system that processes data from these cameras in real time and displays an alert on a map when a polar bear is photographed. You need a solution that incorporates real-time stream processing to analyze raw data for potential sightings, and one that incorporates artificial intelligence (AI) and machine learning to determine with a high degree of accuracy whether a photo contains a polar bear. And you need it fast, because climate change won’t wait.In this lab, you will build such a system using Microsoft Azure and Microsoft Cognitive Services. Specifically, you will use an Azure IoT hub to ingest streaming data from simulated cameras, Azure Storage to store photographs, Azure Stream Analytics to process real-time data streams, Azure Functions to process output from Stream Analytics, Microsoft’s Custom Vision Service to analyze photographs for polar pears, Microsoft Power BI to build a dashboard for visualizing results, and Azure SQL Database as a data source for Power BI.
In this course, you will learn how to get started using the Azure PowerShell cmdlets to perform common management tasks with Azure Infrastructure as a Service. This course will teach you the foundations of interacting with Azure networking services such as virtual networks, network security groups, and the Azure load balancer as well as virtual machines. You will learn how to configure VM storage, networking and compute as well as automatic configuration using the Custom Script Extension and the PowerShell Desired State Configuration extension.
In this lab you will learn how to work with Azure Storage using Azure Storage Explorer. All aspects of Azure Storage will be explored including: Blobs, Files, Tables and Queues.
In this lab, you will build and run container based on IIS Server, ASP.NET 4.5 and ASP.Net Core Frameworks. You will use Dockerfile to create container image and then use Docker CLI commands to launch thecontainers. Finally, you will work work with docker commands to access container logs and stats including CPU and memory.
Azure Container Instances enables deployment of Docker containers onto Azure infrastructure without provisioning any virtual machines or adopting any higher-level service. In this tutorial, you build a small web application in Node.js and package it in a container that can be run using Azure Container Instances.
In this lab, you will practice using Azure Policy and Azure Role-Based Access Control (RBAC) to implement some simple governance scenarios in Azure. You will use Azure Policy to apply a permitted locations rule to the Azure subscription, and RBAC to grant permissions to a new user.
In this lab, you will learn the fundamentals of configuring and managing virtual machine diagnostics and alerts as well as learn some useful troubleshooting techniques for Azure Virtual Machines.This lab pre-provisions an environment that you will use for testing diagnostics capabilities and may take up to 30 minutes before it's ready.
In this lab, you will use Azure's Update Management solution to manage patches and updates for virtual machines. This involves enabling update management for a VM, assessing the status of updates, configuring alerts, scheduling update deployments, and finally viewing the results of update deployments.
In this lab, you will use the Azure PowerShell cmdlets to manage common tasks with Azure Blob Storage.You will learn how to create an Azure Storage Account, create and manage containers, upload and download blobs, and manage leases and snapshots.
In this lab, you will create a virtual network, network security groups and an application security group. From there you will associate several security rules and then create several virtual machines associated with them to test filtering network traffic.
This course will discusses the implementation of cloud security in Microsoft 365, in addition to compliance and privacy concerns. You will learn about various identity and security methods as well as discussing the use of Azure Active Directory and AD DS. It will also discuss mobile device and application management and the use of Windows Intune.
This course will discuss the various licensing and subscription options available in Microsoft 365. It will also discuss the pricing and models for other cloud services and a comparison between cloud services versus on-premise. Finally, it will look at the process for creating a support request.
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.
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.
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.
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.
In this course, you will learn how to get started using the Azure PowerShell cmdlets. This will cover how to use the Azure Cloud Shell or install the Azure PowerShell cmdlets on your local computer. You will also learn how to navigate Azure Resources using the Cloud Shell and the Azure Cmdlets. Finally, the course will explore the various ways you can connect to Microsoft Azure; including logging in interactively, using a service principal or a managed identity.
This is the first course of the AI-100 Exam Preparation Learning Path. In this course, we will discuss all the different APIs available and appropriate use cases for each API,we will discuss the various tools, technologies, and processes available to secure your AI data, andwe will discuss the various analytics solutions, storage solutions, and other services available to create an end to end solution.
In this hands-on lab, you will learn how Trey Research can leverage Deep Learning technologies to scan through their vehicle specification documents to find compliance issues with new regulations. You will standardize the model format to ONNX and observe how this simplifies inference runtime code, enabling pluggability of different models and targeting a broad range of runtime environments and most importantly, improves inferencing speed over the native model. You will build a DevOps pipeline to coordinate retrieving the latest best model from the model registry, packaging the web application, deploying the web application and inferencing web service. After a first successful deployment, you will make updates to both the model, the and web application, and execute the pipeline once to achieve an updated deployment. You will also learn how to monitor the model’s performance after it is deployed so Trey Research can be proactive with performance issues.At the end of this hands-on lab, you will be better able to implement end-to-end solutions that fully operationalize deep learning models, inclusive of all application components that depend on the model.
In this lab, you will learn to use service principals with Azure PowerShell by first creating a service principal, assigning permissions to that principal, and finally logging into Azure with the service principal.
In this lab, you will train a classification model using Python in an Azure Machine Learning Notebook VM. The model will predict what type of bicycle a customer is most likely to buy. Some exploratory data analysis and feature engineering will be required.
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.
In this lab, you will train the model you developed in the last lab on Azure using the Azure Machine Learning service and its Python SDK. After it has been trained, you will register the model to the registry and perform the steps necessary to deploy your model to Azure Machine Learning service where it can be leveraged by your company’s applications.
In this hands-on lab, you will use Azure Databricks in combination with Azure Machine Learning service to build, train and deploy desired models. You will learn how to train a forecasting model against time-series data, without any code, by using automated machine learning, and how to score data in real-time using Spark Structure Streaming within Azure Databricks. You will create a recurrent neural network (RNN) model using PyTorch in Azure Databricks that can be used to forecast against time-series data and train a Natural Language Processing (NLP) text classification model using Keras.At the end of this lab, you will be better able to build solutions leveraging the Azure Machine Learning service and Azure Databricks.
Opsgility leadership has read several books and attended several leadership seminars on DevOps and is convinced that there is real value in the concepts they have learned. To keep it real, they have tasked you with implementing the first software project using some of these concepts and have been given you the go-ahead to try out Azure DevOps as part of an early experiment.In this Live Hackathon, you or your team will be tasked with implementing continuous delivery and integration for an existing application, as well as setting up boards and a sprint schedule for upcoming improvements.
In this lab, you will use the Azure Migrate service to migrate the SmartHotel app which is currently hosted on an on-premises infrastructure hosted in Hyper-V to Azure Virtual Machines. During the lab, you will migrate this entire application stack to Azure using the Azure Migrate service. Note: this lab takes 60-75 minutes to fully deploy.
In this hands-on lab, you will implement a solution which combines both pre-built artificial intelligence (AI) in the form of various Cognitive Services, with custom AI in the form of services built and deployed with Azure Machine Learning service. You will learn to create intelligent solutions atop unstructured text data by designing and implementing a text analytics pipeline. You will discover how to build a binary classifier using a simple neural network that can be used to classify the textual data, as well as how to deploy multiple kinds of predictive services using Azure Machine Learning and learn to integrate with the Computer Vision API and the Text Analytics API from Cognitive Services.
In this lab, you will practice introductory concepts in managing Azure with PowerShell. You will learn to manage subscriptions, create resources, view resources, tag resources, and view resource tags. You will finally learn to delete resources.