Video Training

Azure identity and governance services help you secure access to your resources. In this course, instructor Sharon Bennett delves into this essential topic, showing Azure administrators what they need to know to ensure that the right people can access the right resources. Sharon steps through how to manage device settings and create users and groups. She also discusses important security considerations around role-based access controls, Azure policies, subscriptions, and resource groups. Plus, you can use this course to prep for the Manage Azure Identities and Governance domain in the Microsoft Azure Administrator exam

This training course introduces participants to migrating workloads to Google Cloud Platform. The course explains the strategies to migrate from the source environment to the cloud. Participants are introduced to Google Cloud Platform's fundamental concepts and more in depth topics, like managing virtual machines and configuring networks. In addition to learning how to use Google Cloud Platform, the participants learn how to leverage Google's workload mobility application, Migrate for Compute Engine. The training covers the installation and migration process, including special features like test clones and wave migrations. The course also covers topics related to governance, including resource hierarchy, user identities in the cloud, and Active Directory. Lastly, participants learn how to monitor and log their environment with Stackdriver, leverage the elasticity of the cloud with managed instance groups, and use a global load balancer.

Follow right on the heels of the Elastic Stack Essentials course with the Elasticsearch Deep Dive. Get to understand and go hands-on with the core functionality of Elasticsearch (installing, indexing, querying). Next, learn how to configure it for production use with TLS encryption, user access control, monitoring, and alerting with X-Pack and automated management with Elasticsearch Curator. Get to understand best practices around heap and cluster sizing, hardware requirements, and performing live upgrades.

This is the third course of the Advanced Machine Learning on GCP specialization. In this course,
We will take a look at different strategies for building an image classifier using convolutional neural networks. We'll improve the model's accuracy with augmentation, feature extraction, and fine-tuning hyperparameters while trying to avoid overfitting our data. We will also look at practical issues that arise, for example, when you don't have enough data and how to incorporate the latest research findings into our models.

Mobile augmented reality (AR) is currently the most popular and pervasive form of AR in the market. The applications of AR for the architecture, engineering, and construction (AEC) industries have already started to prove themselves indispensable. In this course, learn how to use the Unity game engine to create an AR mobile application for iOS or Android to view and interact with a 3D model in the real world. As a bonus, instructor Roger Miller also looks at working with the PiXYZ Unity plugin to help get CAD and BIM data into Unity.

For a few tense days in June 1944, the success of the greatest military invasion the world had ever seen depended on weather readings taken by 21-year-old Maureen Sweeney at the remote Blacksod weather station on Ireland's west coast.

AKS is a super-charged Kubernetes managed service which makes creating and running a Kubernetes cluster a breeze!

Meet Lily, an eight-year-old wild black bear, described by some as the most popular bear in the world. Why? Thanks to bear biologist Dr Lynn Rogers, from day one her life has been documented online. Dr Rogers has a unique relationship with Lily and all of his study bears, feeding them by hand and walking with them in the Northwoods of Minnesota. But his methods have divided opinion, resulting in a bounty being put on Lily's head. With hunting season fast approaching, this is the latest and possibly most challenging chapter in her remarkable life.

Incorporating machine learning into data pipelines increases the ability of businesses to extract insights from their data. This course covers several ways machine learning can be included in data pipelines on Google Cloud Platform depending on the level of customization required. For little to no customization, this course covers AutoML. For more tailored machine learning capabilities, this course introduces AI Platform Notebooks and BigQuery Machine Learning. Also, this course covers how to productionalize machine learning solutions using Kubeflow. Learners will get hands-on experience building machine learning models on Google Cloud Platform using QwikLabs.

Easy5 Advanced Controls & Systems Simulation Accurately simulate control systems, hydraulics (including thermal effects), pneumatics gaseous flow, thermal, electrical, mechanical, refrigeration environment control, lubrication or fuel systems, and sampled-data/discrete-time behavior