Lokendra Kumar Ved
Date d'abonnement : 2019
Ligue de bronze
1300 points
Scientific Data Processing
Earned mai 20, 2020 EDT
Cloud Engineering
Earned jan. 4, 2020 EST
Corporate Apps on AWS for Windows
Earned déc. 31, 2019 EST
Databases on AWS for Windows
Earned déc. 31, 2019 EST
Programming Windows on AWS
Earned déc. 31, 2019 EST
Security on AWS
Earned déc. 31, 2019 EST
Cloud Development
Earned oct. 15, 2019 EDT
Alexa Skills Development
Earned oct. 14, 2019 EDT
DEPRECATED Cloud Architecture
Earned août 23, 2019 EDT
Security & Identity Fundamentals
Earned mars 29, 2019 EDT
NCAA® March Madness®: Bracketology with Google Cloud
Earned mars 22, 2019 EDT
Deprecated Kubernetes Solutions
Earned mars 12, 2019 EDT
Baseline: Infrastructure
Earned mars 11, 2019 EDT
Google Cloud Essentials
Earned mars 8, 2019 EST
Kubernetes in Google Cloud
Earned mars 7, 2019 EST
Big data, machine learning, and scientific data? It sounds like the perfect match. In this course, you will get hands-on practice with GCP services like BigQuery, Managed Service for Apache Spark, and Tensorflow by applying them to use cases that employ real-life, scientific data sets. By getting experience with tasks like earthquake data analysis and satellite image aggregation, Scientific Data Processing will expand your skill set in big data and machine learning so you can start tackling your own problems across a spectrum of scientific disciplines.
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This fundamental-level quest is unique amongst the other quest offerings. The labs have been curated to give IT professionals hands-on practice with topics and services that appear in the Google Cloud Certified Associate Cloud Engineer Certification. From IAM, to networking, to Kubernetes engine deployment, this quest is composed of specific labs that will put your Google Cloud knowledge to the test. Be aware that while practice with these labs will increase your skills and abilities, we recommend that you also review the exam guide and other available preparation resources.
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Learn how to deploy Microsoft Windows Server-based applications in the AWS cloud, including Microsoft Exchange, Dynamics CRM and SharePoint.
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Learn how to deploy and administer databases running on Microsoft Windows Server in Amazon EC2 and Amazon RDS.
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Learn how to develop applications in Microsoft Visual Studio leveraging AWS services.
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This quest is designed to teach you how to apply AWS Identity and Access Management, in concert with several other AWS Services, to address real-world application and service security management scenarios.
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The hands-on labs in this Quest are structured to give experienced app developers hands-on practice with the state-of-the-art developing applications in Google Cloud. The topics align with the Google Cloud Certified Professional Cloud Developer Certification. These labs follow the sequence of activities needed to create and deploy an app in Google Cloud from beginning to end. Be aware that while practice with these labs will increase your skills and abilities, it is recommended that you also review the exam guide and other available preparation resources.
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In this Quest, you will learn how to create Alexa skills that respond to voice commands and which can be used on the Amazon Echo, Dot, and Tap devices. You will create back-end functions in AWS Lambda, and then connect them with voice response logic using the Alexa Skills Kit. You will use both the AWS Console and the Amazon Developer Portal in these labs, the latter requiring you to have or create a no-cost, no-credit-card-required account. No hardware device is required for any lab; an Alexa voice response simulation system is provided in the Amazon Developer Portal.
Templates used in these labs can be adapted and extended to create your own Alexa skills and offer them to the worldwide Alexa user community.
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This fundamental-level quest is unique amongst the other quest offerings. The labs have been curated to give IT professionals hands-on practice with topics and services that appear in the Google Cloud Certified Professional Cloud Architect Certification. From IAM, to networking, to Kubernetes engine deployment, this quest is composed of specific labs that will put your Google Cloud knowledge to the test. Be aware that while practice with these labs will increase your skills and abilities, we recommend that you also review the exam guide and other available preparation resources.
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Security is an uncompromising feature of Google Cloud services, and Google Cloud has developed specific tools for ensuring safety and identity across your projects. In this fundamental-level quest, you will get hands-on practice with Google Cloud’s Identity and Access Management (IAM) service, which is the go-to for managing user and virtual machine accounts. You will get experience with network security by provisioning VPCs and VPNs, and learn what tools are available for security threat and data loss protections.
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In this series of labs you will learn how to use BigQuery to analyze NCAA basketball data with SQL. Build a Machine Learning Model to predict the outcomes of NCAA March Madness basketball tournament games.
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Containerized applications have changed the game and are here to stay. With Kubernetes, you can orchestrate containers with ease, and integration with the Google Cloud Platform is seamless. In this advanced-level quest, you will be exposed to a wide range of Kubernetes use cases and will get hands-on practice architecting solutions over the course of 8 labs. From building Slackbots with NodeJS, to deploying game servers on clusters, to running the Cloud Vision API, Kubernetes Solutions will show you first-hand how agile and powerful this container orchestration system is.
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If you are a novice cloud developer looking for hands-on practice beyond Google Cloud Essentials, this course is for you. You will get practical experience through labs that dive into Cloud Storage and other key application services like Monitoring and Cloud Functions. You will develop valuable skills that are applicable to any Google Cloud initiative. 1-minute videos walk you through key concepts for these labs.
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In this introductory-level course, you get hands-on practice with the Google Cloud’s fundamental tools and services. Optional videos are provided to provide more context and review for the concepts covered in the labs. Google Cloud Essentials is a recommendeded first course for the Google Cloud learner - you can come in with little or no prior cloud knowledge, and come out with practical experience that you can apply to your first Google Cloud project. From writing Cloud Shell commands and deploying your first virtual machine, to running applications on Kubernetes Engine or with load balancing, Google Cloud Essentials is a prime introduction to the platform’s basic features.
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Kubernetes is the most popular container orchestration system, and Google Kubernetes Engine was designed specifically to support managed Kubernetes deployments in Google Cloud. In this course, you will get hands-on practice configuring Docker images, containers, and deploying fully-fledged Kubernetes Engine applications.
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