This course introduces administrative tasks that a system administrator can perform with Linux hosted on IBM Power servers. This includes virtualization concepts such as logical partitioning, installation of Linux, command-line operations, and more interesting administration and device management tasks. This course includes hands-on exercises with systems from an IBM data center.

Want to take the first steps to become a Cloud Application Developer? This course will lead you through the languages and tools you will need to develop your own Cloud Apps. Beginning with an explanation of how internet servers and clients work together to deliver applications to users, this course then takes you through the context for application development in the Cloud, introducing front-end, back-end, and full-stack development. You’ll then focus on the languages you need for front-end development, working with HTML, CSS, and JavaScript. Finally, you will discover tools that help you to store your projects and keep track of changes made to project files, such as Git and GitHub.

Data pipelines typically fall under one of the Extra-Load, Extract-Load-Transform or Extract-Transform-Load paradigms. This course describes which paradigm should be used and when for batch data. Furthermore, this course covers several technologies on Google Cloud Platform for data transformation including BigQuery, executing Spark on Cloud Dataproc, pipeline graphs in Cloud Data Fusion and serverless data processing with Cloud Dataflow. Learners will get hands-on experience building data pipeline components on Google Cloud Platform using Qwiklabs.

This course introduces you to NoSQL databases and the challenges they solve. Expert instructors will dive deep into Amazon DynamoDB topics such as recovery, SDKs, partition keys, security and encryption, global tables, stateless applications, streams, and best practices. DynamoDB is a key-value and document database that delivers single-digit millisecond performance at any scale. It's a fully managed, multiregion, multimaster database with built-in security, backup and restore, and in-memory caching for internet-scale applications. DynamoDB can handle more than 10 trillion requests per day and support peaks of more than 20 million requests per second. This course uses a combination of video-based lectures delivered by Amazon Web Services expert technical trainers, demonstrations, and hands-on lab exercises, that you run in your own AWS account to enable you to build, deploy and manage your own DynamoDB-powered application.

Salesforce Commerce Cloud, formerly called Demandware, is a cloud-based service for unifying the way businesses engage with customers over any channel or device. Now a days E-Commerce is growing rapidly. Every merchant or seller wants to do online selling. Salesforce Commerce Cloud is a platform where a large E-Commerce business can be handled very easily. All the cloud services make this very easy for Merchants as well as for Customers. Create Multi regional Online Stores , Easy Product selling , Best order management & customer handling. This Course is dedicated to : - Spread Knowledge of this Cloud base Salesforce product. - Easy tutorials for Merchants so that they can handle Business Manager/ Admin very easily. - Tutorials for beginers as well as Advance developers. - Coding Standards for Backend as well as frontend developers. - Solutions to common issues in Sales force commerce cloud development. Lets spread the knowledge of Salesforce Commerce Cloud . Topics covered in the sessions are as following : Introduction to Salesforce Commerce Cloud Understand Business Manager Connect Salesforce Commerce Cloud Using UXStudio & Eclipse Catalog & Products Campaigns & Promotions Customers Groups Cartridge or File Structure of Salesforce Commerce Cloud Concept of Pipelines At the End of course you will be able to start Administration & Development in Salesforce Commerce Cloud.

Cloud Computing has really changed the way companies looking into their digital Infrastructure now a days. Cloud computing with its unique paradigms brings in new opportunities and challenges for developers and administrators worldwide. With our unique curriculum we have tried to create the content which will bring beginners up to speed with Cloud technologies. The Course will start with basic introduction to cloud concepts like SAAS, PAAS and IAAS. You will also learn how Linux systems is changing the Infrastructure landscape worldwide. You will then learn to use popular cloud technologies like Google Compute Engine , Amazon AWS and Redhat open shift. The last unit covers Virtualization Technologies to provide you a holistic understanding of cloud computing environment. This course is surely the fastest and smartest way to get started with Cloud computing technologies.

This course provides a holistic experience of optimally configuring SAP on Google Cloud. Participants will learn to configure SAP on Google Cloud, and what best practices are, leaving the course with actionable experience to configure SAP on Google Cloud and run SAP workloads on Google Cloud. >>> By enrolling in this course you agree to the Qwiklabs Terms of Service as set out in the FAQ and located at: https://qwiklabs.com/terms_of_service <<<

This course introduces participants to the strategies to migrate from a source environment to Google Cloud. Participants are introduced to Google Cloud's fundamental concepts and more in depth topics, like creating virtual machines, configuring networks and managing access and identities. The course then covers the installation and migration process of Migrate for Compute Engine, including special features like test clones and wave migrations.

This course provides an introduction to data center networking technologies, more specifically software-defined networking. It covers the history behind SDN, description of networks in data-centers, a concrete data-center network architecture (Microsoft VL2), and traffic engineering.

This course provides an overview of Computer Vision (CV), Machine Learning (ML) with Amazon Web Services (AWS), and how to build and train a CV model using the Apache MXNet and GluonCV toolkit. The course discusses artificial neural networks and other deep learning concepts, then walks through how to combine neural network building blocks into complete computer vision models and train them efficiently. This course covers AWS services and frameworks including Amazon Rekognition, Amazon SageMaker, Amazon SageMaker GroundTruth, and Amazon SageMaker Neo, AWS Deep Learning AMIs via Amazon EC2, AWS Deep Learning Containers, and Apache MXNet on AWS. The course is comprised of video lectures, hands-on exercise guides, demonstrations, and quizzes. Each week will focus on different aspects of computer vision with GluonCV. In week one, we will present some basic concepts in computer vision, discuss what tasks can be solved with GluonCV and go over the benefits of Apache MXNet. In the second week, we will focus on the AWS services most appropriate to your task. We will use services such as Amazon Rekognition and Amazon SageMaker. We’ll review the differences between AWS Deep Learning AMIs and Deep Learning containers. Finally, there are demonstrations on how to set up each of the services covered in this module. Week three will focus on setting up GluonCV and MXNet. We will look at using pre-trained models for classification, detection and segmentation. During week four and five, we will go over the fundamentals of Gluon, the easy-to-use high-level API for MXNet: understanding when to use different Gluon blocks, how to combine those blocks into complete models, constructing datasets, and writing a complete training loop. In the final week, there will be a final project where you will apply everything you’ve learned in the course so far: select the appropriate pre-trained GluonCV model, apply that model to your dataset and visualize the output of your GluonCV model.