The two key components of any data pipeline are data lakes and warehouses. This course highlights use-cases for each type of storage and dives into the available data lake and warehouse solutions on Google Cloud Platform in technical detail. Also, this course describes the role of a data engineer, the benefits of a successful data pipeline to business operations, and examines why data engineering should be done in a cloud environment. Learners will get hands-on experience with data lakes and warehouses on Google Cloud Platform using QwikLabs.

Building Serverless Web Applications provides introduction to serverless architecture. It will walk you through the AWS serverless platform and discuss some use cases that are commonly addressed with serverless solutions. You will learn the two core components of the AWS serverless platform: AWS Lambda and Amazon DynamoDB. Then it will discuss how to design and build RESTful microservices and web applications using Amazon API Gateway in conjunction with Lambda, Dynamo DB, and S3. Finally, you will watch a demo building serverless dynamic web applications using the AWS console.

This course gives you the background needed to understand basic Cybersecurity. You will learn the history of Cybersecurity, types and motives of cyber attacks to further your knowledge of current threats to organizations and individuals. Key terminology, basic system concepts and tools will be examined as an introduction to the Cybersecurity field. You will learn about critical thinking and its importance to anyone looking to pursue a career in Cybersecurity. Finally, you will begin to learn about organizations and resources to further research cybersecurity issues in the Modern era. This course is intended for anyone who wants to gain a basic understanding of Cybersecurity or as the first course in a series of courses to acquire the skills to work in the Cybersecurity field as a Jr Cybersecurity Analyst. The completion of this course also makes you eligible to earn the Introduction to Cybersecurity Tools & Cyber Attacks IBM digital badge. More information about the badge can be found https://www.youracclaim.com/org/ibm/badge/introduction-to-cybersecurity-tools-cyber-attacks

Welcome to "Contact Center AI Conversational Design with Dialogflow", the first course in the "Customer Experiences with Contact Center AI" specialization. In this course, learn how to design, develop, and deploy customer conversational solutions using Contact Center Artificial Intelligence (CCAI). You will be introduced to Contact Center AI and its three pillars, Dialogflow, Agent Assist, and Insights, the concept of conversational experiences and how the study of them influences the design of your virtual agent, the objects, tools, and methods to get your basic virtual agent up and running, and using context so that you can take your virtual agent to the next level of intelligent conversation. This is an intermediate course, intended for learners with the following types of roles: • Architects and systems integrators implementing Contact Center AI • Conversational Architects • Contact center virtual agent and application developers • Business managers Prerequisite: To be successful in this course, learners should have completed Google Cloud Product Fundamentals or have equivalent experience.

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.