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Apply your skills in Google Cloud console

Muhammad Zain Farooq

Member since 2020

Silver League

12380 points
Set Up a Google Cloud Network Earned May 18, 2022 EDT
Engineer Data for Predictive Modeling with BigQuery ML Earned May 18, 2022 EDT
Build a Secure Google Cloud Network Earned May 18, 2022 EDT
[DEPRECATED] Build Interactive Apps with Google Assistant Earned May 18, 2022 EDT
Prepare Data for Looker Dashboards and Reports Earned May 17, 2022 EDT
Implement Cloud Security Fundamentals on Google Cloud Earned May 17, 2022 EDT
Create ML Models with BigQuery ML Earned May 17, 2022 EDT
Monitor and Log with Google Cloud Observability Earned May 16, 2022 EDT
Implement DevOps Workflows in Google Cloud Earned May 14, 2022 EDT
Build a Data Warehouse with BigQuery Earned May 14, 2022 EDT
Deploy Kubernetes Applications on Google Cloud Earned May 19, 2021 EDT
Develop Serverless Apps with Firebase Earned May 19, 2021 EDT
Set Up an App Dev Environment on Google Cloud Earned May 18, 2021 EDT
Implementing Cloud Load Balancing for Compute Engine Earned May 17, 2021 EDT
Develop Your Google Cloud Network Earned May 17, 2021 EDT
DEPRECATED BigQuery for Marketing Analysts Earned Sep 29, 2020 EDT
Scientific Data Processing Earned Sep 29, 2020 EDT
[DEPRECATED] Data Engineering Earned Sep 28, 2020 EDT
Data Science on Google Cloud Earned Sep 27, 2020 EDT
Intermediate ML: TensorFlow on Google Cloud Earned Sep 27, 2020 EDT
Data Science on Google Cloud: Machine Learning Earned Sep 27, 2020 EDT
Advanced ML: ML Infrastructure Earned Sep 26, 2020 EDT
Intro to ML: Image Processing Earned Sep 26, 2020 EDT
DEPRECATED Explore Machine Learning Models with Explainable AI Earned Sep 25, 2020 EDT
Use Machine Learning APIs on Google Cloud Earned Sep 24, 2020 EDT
NCAA® March Madness®: Bracketology with Google Cloud Earned Sep 24, 2020 EDT
DEPRECATED BigQuery Basics for Data Analysts Earned Sep 24, 2020 EDT
Intro to ML: Language Processing Earned Sep 24, 2020 EDT
Cloud Logging Earned Jun 22, 2020 EDT
Security & Identity Fundamentals Earned Jun 22, 2020 EDT
Automate Deployment and Manage Traffic on a Google Cloud Network Earned Jun 22, 2020 EDT
Understand Your Google Cloud Costs Earned Jun 21, 2020 EDT
Baseline: Infrastructure Earned Jun 20, 2020 EDT
Google Cloud Essentials Earned Jun 20, 2020 EDT

Earn a skill badge by completing the Set Up a Google Cloud Network skill badge course, where you will learn how to perform basic networking tasks on Google Cloud Platform - create a custom network, add subnets firewall rules, then create VMs and test the latency when they communicate with each other.

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Complete the intermediate Engineer Data for Predictive Modeling with BigQuery ML skill badge to demonstrate skills in the following: building data transformation pipelines to BigQuery using Dataprep by Trifacta; using Cloud Storage, Dataflow, and BigQuery to build extract, transform, and load (ETL) workflows; and building machine learning models using BigQuery ML.

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Earn a skill badge by completing the Build a Secure Google Cloud Network skill badge course, where you will learn about multiple networking-related resources to build, scale, and secure your applications on Google Cloud.

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Earn a skill badge by completing the Build Interactive Apps with Google Assistant quest, where you will learn how to build Google Assistant applications, including how to: create an Actions project, integrate Dialogflow with an Actions project, test your application with Actions simulator, build an Assistant application with flash cards template, integrate customer MP3 files with your Assistant application, add Cloud Translation API to your Assistant application, and use APIs and integrate them into your applications. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete the skill badge quest, and final assessment challenge lab, to receive a digital badge that you can share with your network.

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Complete the introductory Prepare Data for Looker Dashboards and Reports skill badge course to demonstrate skills in the following: filtering, sorting, and pivoting data; merging results from different Looker Explores; and using functions and operators to build Looker dashboards and reports for data analysis and visualization.

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Complete the intermediate Implement Cloud Security Fundamentals on Google Cloud skill badge course to demonstrate skills in the following: creating and assigning roles with Identity and Access Management (IAM); creating and managing service accounts; enabling private connectivity across virtual private cloud (VPC) networks; restricting application access using Identity-Aware Proxy; managing keys and encrypted data using Cloud Key Management Service (KMS); and creating a private Kubernetes cluster.

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Complete the intermediate Create ML Models with BigQuery ML skill badge to demonstrate skills in creating and evaluating machine learning models with BigQuery ML to make data predictions.

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Complete the introductory Monitor and Log with Google Cloud Observability skill badge course to demonstrate skills in the following: monitoring virtual machines in Compute Engine, utilizing Cloud Monitoring for multi-project oversight, extending monitoring and logging capabilities to Cloud Functions, creating and sending custom application metrics, and configuring Cloud Monitoring alerts based on custom metrics.

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Complete the intermediate Implement DevOps Workflows in Google Cloud skill badge to demonstrate skills in the following: creating git repositories with Cloud Source Repositories, launching, managing, and scaling deployments on Google Kubernetes Engine (GKE), and architecting CI/CD pipelines that automate container image builds and deployments to GKE.

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Complete the intermediate Build a Data Warehouse with BigQuery skill badge course to demonstrate skills in the following: joining data to create new tables, troubleshooting joins, appending data with unions, creating date-partitioned tables, and working with JSON, arrays, and structs in BigQuery.

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Complete the intermediate Deploy Kubernetes Applications on Google Cloud skill badge course to demonstrate skills in the following: Configuring and building Docker container images.Creating and managing Google Kubernetes Engine (GKE) clusters.Utilizing kubectl for efficient cluster management.Deploying Kubernetes applications with robust continuous delivery (CD) practices.

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Complete the intermediate Develop Serverless Apps with Firebase skill badge course to demonstrate skills in the following: architecting and building serverless web applications with Firebase, utilizing Firestore for database management, automating deployment processes using Cloud Build, and integrating Google Assistant functionality into your applications.

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Earn a skill badge by completing the Set Up an App Dev Environment on Google Cloud skill badge course, where you learn how to build and connect storage-centric cloud infrastructure using the basic capabilities of the following technologies: Cloud Storage, Identity and Access Management, Cloud Functions, and Pub/Sub.

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Complete the introductory Implementing Cloud Load Balancing for Compute Engine skill badge to demonstrate skills in the following: creating and deploying virtual machines in Compute Engine and configuring network and application load balancers.

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Earn a skill badge by completing the Develop your Google Cloud Network skill badge course, where you learn multiple ways to deploy and monitor applications including how to: explore IAM roles and add/remove project access, create VPC networks, deploy and monitor Compute Engine VMs, write SQL queries, deploy and monitor VMs in Compute Engine, and deploy applications using Kubernetes with multiple deployment approaches.

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Want to turn your marketing data into insights and build dashboards? Bring all of your data into one place for large-scale analysis and model building. Get repeatable, scalable, and valuable insights into your data by learning how to query it and using BigQuery. BigQuery is Google's fully managed, NoOps, low cost analytics database. With BigQuery you can query terabytes and terabytes of data without having any infrastructure to manage or needing a database administrator. BigQuery uses SQL and can take advantage of the pay-as-you-go model. BigQuery allows you to focus on analyzing data to find meaningful insights.

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Big data, machine learning, and scientific data? It sounds like the perfect match. In this advanced-level quest, you will get hands-on practice with GCP services like Big Query, Dataproc, 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 advanced-level quest is unique amongst the other catalog 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 Data Engineer Certification. From Big Query, to Dataprep, to Cloud Composer, this quest is composed of specific labs that will put your Google Cloud data engineering knowledge to the test. Be aware that while practice with these labs will increase your skills and abilities, you will need other preparation, too. The exam is quite challenging and external studying, experience, and/or background in cloud data engineering is recommended. Looking for a hands on challenge lab to demonstrate your skills and validate your knowledge? On completing this quest, enroll in and finish the additional challenge lab at the end of the Engineer Data in the Google Cloud to receive an exclusive Google Cloud digital badge.

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This is the first of two Quests of hands-on labs is derived from the exercises from the book Data Science on Google Cloud Platform, 2nd Edition by Valliappa Lakshmanan, published by O'Reilly Media, Inc. In this first Quest, covering up through chapter 8, you are given the opportunity to practice all aspects of ingestion, preparation, processing, querying, exploring and visualizing data sets using Google Cloud tools and services.

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TensorFlow is an open source software library for high performance numerical computation that's great for writing models that can train and run on platforms ranging from your laptop to a fleet of servers in the Cloud to an edge device. This quest takes you beyond the basics of using predefined models and teaches you how to build, train and deploy your own on Google Cloud.

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This is the second of two Quests of hands-on labs derived from the exercises from the book Data Science on Google Cloud Platform, 2nd Edition by Valliappa Lakshmanan, published by O'Reilly Media, Inc. In this second Quest, covering chapter 9 through the end of the book, you extend the skills practiced in the first Quest, and run full-fledged machine learning jobs with state-of-the-art tools and real-world data sets, all using Google Cloud tools and services.

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Machine Learning is one of the most innovative fields in technology, and the Google Cloud Platform has been instrumental in furthering its development. With a host of APIs, Google Cloud has a tool for just about any machine learning job. In this advanced-level course, you will get hands-on practice with machine learning at scale and how to employ the advanced ML infrastructure available on Google Cloud.

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Using large scale computing power to recognize patterns and "read" images is one of the foundational technologies in AI, from self-driving cars to facial recognition. The Google Cloud Platform provides world class speed and accuracy via systems that can utilized by simply calling APIs. With these and a host of other APIs, GCP has a tool for just about any machine learning job. In this introductory quest, you will get hands-on practice with machine learning as it applies to image processing by taking labs that will enable you to label images, detect faces and landmarks, as well as extract, analyze, and translate text from within images.

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Earn a skill badge by completing the Explore Machine Learning Models with Explainable AI quest, where you will learn how to do the following using Explainable AI: build and deploy a model to an AI platform for serving (prediction), use the What-If Tool with an image recognition model, identify bias in mortgage data using the What-If Tool, and compare models using the What-If Tool to identify potential bias. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete this skill badge quest and the final assessment challenge lab to receive a skill badge that you can share with your network.

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Earn the advanced skill badge by completing the Use Machine Learning APIs on Google Cloud course, where you learn the basic features for the following machine learning and AI technologies: Cloud Vision API, Cloud Translation API, and Cloud Natural Language API.

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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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Want to scale your data analysis efforts without managing database hardware? Learn the best practices for querying and getting insights from your data warehouse with this interactive series of BigQuery labs. BigQuery is Google's fully managed, NoOps, low cost analytics database. With BigQuery you can query terabytes and terabytes of data without having any infrastructure to manage or needing a database administrator. BigQuery uses SQL and can take advantage of the pay-as-you-go model. BigQuery allows you to focus on analyzing data to find meaningful insights.

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It’s no secret that machine learning is one of the fastest growing fields in tech, and the Google Cloud Platform has been instrumental in furthering its development. With a host of APIs, GCP has a tool for just about any machine learning job. In this introductory course, you will get hands-on practice with machine learning as it applies to language processing by taking labs that will enable you to extract entities from text, and perform sentiment and syntactic analysis as well as use the Speech to Text API for transcription.

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Cloud Logging is a fully managed service that performs at scale. It can ingest application and system log data from thousands of VMs and, even better, analyze all that log data in real time. In this fundamental-level Quest, you learn how to store, search, analyze, monitor, and alert on log data and events from Google Cloud. The labs in the Quest give you hands-on practice using Cloud Logging to maximize your learning experience and provide insight on how you can use Cloud Logging to your own Google Cloud environment.

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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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Networking is a principle theme of cloud computing. It’s the underlying structure of Google Cloud, and it’s what connects all your resources and services to one another. This course will cover essential Google Cloud networking services and will give you hands-on practice with specialized tools for developing mature networks. From learning the ins-and-outs of VPCs, to creating enterprise-grade load balancers, Automate Deployment and Manage Traffic on a Google Cloud Network will give you the practical experience needed so you can start building robust networks right away.

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This course is most suitable for those working in a technology or finance role who are responsible for managing Google Cloud costs. You’ll learn how to set up a billing account, organize resources, and manage billing access permissions. In the hands-on labs, you'll learn how to view your invoice, track your Google Cloud costs with Billing reports, analyze your billing data with BigQuery or Google Sheets, and create custom billing dashboards with Looker Studio. References made to links in the videos can be accessed in this Additional Resources document.

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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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