This course provides an introduction to the development and support for Cloud-native applications, more specifically it delves into best practices of developing applications; migrating on premise applications to the cloud; the basic building blocks and properties expected from Cloud applications. The course also provide highlights of some novel cloud applications, including geo-distributed computations.

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.

Cloud computing has taken over the IT landscape and is soon to outpace on-premise and in-house data centers as companies are starting to realize the efficiencies, cost savings, and flexibility the cloud can provide. Computing resources can be created and destroyed simply by calling an API. Entire virtual data centers can be created in a matter of minutes or hours. Whether your company or application was born in the cloud or transitioning to the cloud, you need tools to build and manage your infrastructure. Terraform from Hashicorp is one such tool that allows you to declare infrastructure as code in a simple, easy to understand language. Managing your infrastructure as code bridges the gap between dev and ops and provides an opportunity to include infrastructure management as part of the development lifecycle. When environments are declared in code they can be shared and used across your organization to provide consistent environments that align with your production environment. Managing infrastructure as code also provides a far more robust process for managing and tracking infrastructure since these processes can now be incorporated into CI/CD tooling and other automation processes. In this course I will teach you the fundamentals of Terraform using Amazon Web Services as an example. Together we will walk through the basics of Terraform and ultimately create real infrastructure in AWS along the way. This course makes use of the AWS Free Tier which offers the general public a certain number of FREE computing hours and storage space for one year. It is recommended that students sign up for an AWS Free Tier account. Udemy and the author of this course are not liable for any cloud service provider charges you may incur while executing the exercises in this course.

Internet of Things (IoT) is an emerging area of information and communications technology (ICT) involving many disciplines of computer science and engineering including sensors/actuators, communications networking, server platforms, data analytics and smart applications. IoT is considered to be an essential part of the 4th Industrial Revolution along with AI and Big Data. This course will be very useful to senior undergraduate and graduate students as well as engineers who are working in the industry. This course aims at introducing the general concepts and architecture of IoT applications, networking technologies involved, IoT development kits including Arduino, Raspberry Pi, Samsung ARTIK, and how to program them. This course will be offered in English. Subtitles/captions in both of English and Korean will be also provided. IoT (Internet of Things, 사물인터넷)는 최근 중요한 정보통신기술로 주목 받고 있으며 센서/ 제어기, 통신 네트워크, 서버 플랫폼, 데이터 분석, 스마트 앱 등의 컴퓨터공학 기술들이 융합된 기술입니다. IoT는 인공지능, 빅데이터와 함께, 4차산업혁명의 3대 핵심 기술 중 하나로 손꼽히고 있습니다. 본 강좌는 현재 대학에서 공부를 하고 있는 학부 3-4학년 및 대학원생들에게 뿐만 아니라 현장의 개발자, 엔지니어들에게도 도움이 될 거라 믿습니다. IoT의 개념부터 아키텍처, 네트워크기술들을 소개하고 IoT 앱들을 개발할 때 많이 사용되는 Arduino, Raspberry Pi와 삼성전자의 ARTIK 플랫폼을 소개합니다. 본 과목은 영어로 진행되며, 영문과 한글 자막을 제공합니다.

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.