Professional Machine Learning Engineer Study Guide
Earned نوفمبر 10, 2024 EST
Responsible AI for Developers: Interpretability & Transparency
Earned نوفمبر 10, 2024 EST
Responsible AI for Developers: Fairness & Bias
Earned نوفمبر 10, 2024 EST
Create Generative AI Apps on Google Cloud
Earned أكتوبر 18, 2024 EDT
Generative AI Explorer - Vertex AI
Earned أكتوبر 17, 2024 EDT
Machine Learning Operations (MLOps) for Generative AI
Earned أكتوبر 17, 2024 EDT
Introduction to Large Language Models
Earned أكتوبر 17, 2024 EDT
Machine Learning Operations (MLOps): Getting Started
Earned أكتوبر 17, 2024 EDT
Introduction to Generative AI
Earned أكتوبر 17, 2024 EDT
Production Machine Learning Systems
Earned أكتوبر 16, 2024 EDT
Build and Deploy Machine Learning Solutions on Vertex AI
Earned أكتوبر 9, 2024 EDT
Classify Images with TensorFlow on Google Cloud
Earned أكتوبر 3, 2024 EDT
BigQuery for Machine Learning
Earned أكتوبر 1, 2024 EDT
Introduction to AI and Machine Learning on Google Cloud
Earned سبتمبر 24, 2024 EDT
Serverless Data Processing with Dataflow: Operations
Earned مايو 21, 2024 EDT
Trust and Security with Google Cloud
Earned أبريل 30, 2024 EDT
Innovating with Google Cloud Artificial Intelligence
Earned أبريل 30, 2024 EDT
Essential Google Cloud Infrastructure: Foundation
Earned أبريل 29, 2024 EDT
Build a Data Mesh with Dataplex
Earned أبريل 26, 2024 EDT
Serverless Data Processing with Dataflow: Develop Pipelines
Earned أبريل 24, 2024 EDT
Serverless Data Processing with Dataflow: Foundations
Earned مارس 31, 2024 EDT
Prepare Data for ML APIs on Google Cloud
Earned مارس 31, 2024 EDT
Preparing for your Professional Data Engineer Journey
Earned مارس 26, 2024 EDT
Engineer Data for Predictive Modeling with BigQuery ML
Earned مارس 26, 2024 EDT
Create ML Models with BigQuery ML
Earned مارس 26, 2024 EDT
Smart Analytics, Machine Learning, and AI on Google Cloud
Earned مارس 25, 2024 EDT
Building Resilient Streaming Analytics Systems on Google Cloud
Earned مارس 25, 2024 EDT
Building Batch Data Pipelines on Google Cloud
Earned مارس 24, 2024 EDT
Build a Data Warehouse with BigQuery
Earned مارس 23, 2024 EDT
Modernizing Data Lakes and Data Warehouses with Google Cloud
Earned مارس 23, 2024 EDT
Google Cloud Big Data and Machine Learning Fundamentals
Earned مارس 19, 2024 EDT
Derive Insights from BigQuery Data
Earned يناير 6, 2023 EST
Implement Cloud Security Fundamentals on Google Cloud
Earned يناير 6, 2023 EST
Deploy Kubernetes Applications on Google Cloud
Earned يناير 6, 2023 EST
Scaling with Google Cloud Operations
Earned يناير 2, 2023 EST
Infrastructure and Application Modernization with Google Cloud
Earned يناير 2, 2023 EST
Exploring Data Transformation with Google Cloud
Earned يناير 2, 2023 EST
Digital Transformation with Google Cloud
Earned يناير 2, 2023 EST
Google Cloud Fundamentals: Core Infrastructure
Earned يناير 2, 2023 EST
DEPRECATED Exploring APIs
Earned يناير 2, 2023 EST
Using the Cloud SDK Command Line
Earned ديسمبر 30, 2022 EST
Build a Secure Google Cloud Network
Earned ديسمبر 30, 2022 EST
Google Cloud Essentials
Earned ديسمبر 30, 2022 EST
Develop your Google Cloud Network
Earned مارس 24, 2022 EDT
Cloud Logging
Earned مارس 24, 2022 EDT
DEPRECATED Google Cloud's Operations Suite on GKE
Earned مارس 24, 2022 EDT
Monitor and Log with Google Cloud Observability
Earned مارس 23, 2022 EDT
Anthos Service Mesh
Earned مارس 11, 2022 EST
[DEPRECATED] Secure Workloads in Google Kubernetes Engine
Earned يناير 14, 2022 EST
Kubernetes in Google Cloud
Earned يناير 10, 2022 EST
Build Infrastructure with Terraform on Google Cloud
Earned يناير 8, 2022 EST
Implement DevOps Workflows in Google Cloud
Earned ديسمبر 9, 2021 EST
Set Up an App Dev Environment on Google Cloud
Earned نوفمبر 26, 2021 EST
Implement Load Balancing on Compute Engine
Earned نوفمبر 24, 2021 EST
This course helps learners create a study plan for the PMLE (Professional Machine Learning Engineer) certification exam. Learners explore the breadth and scope of the domains covered in the exam. Learners assess their exam readiness and create their individual study plan.
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This course introduces concepts of AI interpretability and transparency. It discusses the importance of AI transparency for developers and engineers. It explores practical methods and tools to help achieve interpretability and transparency in both data and AI models.
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This course introduces concepts of responsible AI and AI principles. It covers techniques to practically identify fairness and bias and mitigate bias in AI/ML practices. It explores practical methods and tools to implement Responsible AI best practices using Google Cloud products and open source tools.
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Generative AI applications can create new user experiences that were nearly impossible before the invention of large language models (LLMs). As an application developer, how can you use generative AI to build engaging, powerful apps on Google Cloud?
In this course, you'll learn about generative AI applications and how you can use prompt design and retrieval augmented generation (RAG) to build powerful applications using LLMs. You'll learn about a production-ready architecture that can be used for generative AI applications and you'll build an LLM and RAG-based chat application.
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The Generative AI Explorer - Vertex Quest is a collection of labs on how to use Generative AI on Google Cloud. Through the labs, you will learn about how to use the models in the Vertex AI PaLM API family, including text-bison, chat-bison, and textembedding-gecko. You will also learn about prompt design, best practices, and how it can be used for ideation, text classification, text extraction, text summarization, and more. You will also learn how to tune a foundation model by training it via Vertex AI custom training and deploy it to a Vertex AI endpoint.
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This course is dedicated to equipping you with the knowledge and tools needed to uncover the unique challenges faced by MLOps teams when deploying and managing Generative AI models, and exploring how Vertex AI empowers AI teams to streamline MLOps processes and achieve success in Generative AI projects.
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This is an introductory level micro-learning course that explores what large language models (LLM) are, the use cases where they can be utilized, and how you can use prompt tuning to enhance LLM performance. It also covers Google tools to help you develop your own Gen AI apps.
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This course introduces participants to MLOps tools and best practices for deploying, evaluating, monitoring and operating production ML systems on Google Cloud. MLOps is a discipline focused on the deployment, testing, monitoring, and automation of ML systems in production. Machine Learning Engineering professionals use tools for continuous improvement and evaluation of deployed models. They work with (or can be) Data Scientists, who develop models, to enable velocity and rigor in deploying the best performing models.
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This is an introductory level microlearning course aimed at explaining what Generative AI is, how it is used, and how it differs from traditional machine learning methods. It also covers Google Tools to help you develop your own Gen AI apps.
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This course covers how to implement the various flavors of production ML systems— static, dynamic, and continuous training; static and dynamic inference; and batch and online processing. You delve into TensorFlow abstraction levels, the various options for doing distributed training, and how to write distributed training models with custom estimators.
This is the second course of the Advanced Machine Learning on Google Cloud series. After completing this course, enroll in the Image Understanding with TensorFlow on Google Cloud course.
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Earn the intermediate skill badge by completing the Build and Deploy Machine Learning Solutions with Vertex AI course, where you will learn how to use Google Cloud's Vertex AI platform, AutoML, and custom training services to train, evaluate, tune, explain, and deploy machine learning models. This skill badge course is for professional Data Scientists and Machine Learning Engineers. 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, and the final assessment challenge lab, to receive a digital badge that you can share with your network.
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Earn the intermediate skill badge by completing the Classify Images with TensorFlow on Google Cloud course where you will learn how to use TensorFlow and Vertex AI to create and train machine learning models. You will primarily interact with Vertex AI Workbench user-managed notebooks. 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, and the final assessment challenge lab, to receive a digital badge that you can share with your network.
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Want to build ML models in minutes instead of hours using just SQL? BigQuery ML democratizes machine learning by letting data analysts create, train, evaluate, and predict with machine learning models using existing SQL tools and skills. In this series of labs, you will experiment with different model types and learn what makes a good model. 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 this quest to receive an exclusive Google Cloud digital badge.
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This course introduces the AI and machine learning (ML) offerings on Google Cloud that build both predictive and generative AI projects. It explores the technologies, products, and tools available throughout the data-to-AI life cycle, encompassing AI foundations, development, and solutions. It aims to help data scientists, AI developers, and ML engineers enhance their skills and knowledge through engaging learning experiences and practical hands-on exercises.
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In the last installment of the Dataflow course series, we will introduce the components of the Dataflow operational model. We will examine tools and techniques for troubleshooting and optimizing pipeline performance. We will then review testing, deployment, and reliability best practices for Dataflow pipelines. We will conclude with a review of Templates, which makes it easy to scale Dataflow pipelines to organizations with hundreds of users. These lessons will help ensure that your data platform is stable and resilient to unanticipated circumstances.
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As organizations move their data and applications to the cloud, they must address new security challenges. The Trust and Security with Google Cloud course explores the basics of cloud security, the value of Google Cloud's multilayered approach to infrastructure security, and how Google earns and maintains customer trust in the cloud.
Part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.
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Artificial intelligence (AI) and machine learning (ML) represent an important evolution in information technologies that are quickly transforming a wide range of industries. “Innovating with Google Cloud Artificial Intelligence” explores how organizations can use AI and ML to transform their business processes.
Part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.
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This accelerated on-demand course introduces participants to the comprehensive and flexible infrastructure and platform services provided by Google Cloud with a focus on Compute Engine. Through a combination of video lectures, demos, and hands-on labs, participants explore and deploy solution elements, including infrastructure components such as networks, virtual machines and applications services. You will learn how to use the Google Cloud through the console and Cloud Shell. You'll also learn about the role of a cloud architect, approaches to infrastructure design, and virtual networking configuration with Virtual Private Cloud (VPC), Projects, Networks, Subnetworks, IP addresses, Routes, and Firewall rules.
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Complete the introductory Build a Data Mesh with Dataplex skill badge to demonstrate skills in the following: building a data mesh with Dataplex to facilitate data security, governance, and discovery on Google Cloud. You practice and test your skills in tagging assets, assigning IAM roles, and assessing data quality in Dataplex. 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, and the final assessment challenge lab, to receive a digital badge that you can share with your network.
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In this second installment of the Dataflow course series, we are going to be diving deeper on developing pipelines using the Beam SDK. We start with a review of Apache Beam concepts. Next, we discuss processing streaming data using windows, watermarks and triggers. We then cover options for sources and sinks in your pipelines, schemas to express your structured data, and how to do stateful transformations using State and Timer APIs. We move onto reviewing best practices that help maximize your pipeline performance. Towards the end of the course, we introduce SQL and Dataframes to represent your business logic in Beam and how to iteratively develop pipelines using Beam notebooks.
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This course is part 1 of a 3-course series on Serverless Data Processing with Dataflow. In this first course, we start with a refresher of what Apache Beam is and its relationship with Dataflow. Next, we talk about the Apache Beam vision and the benefits of the Beam Portability framework. The Beam Portability framework achieves the vision that a developer can use their favorite programming language with their preferred execution backend. We then show you how Dataflow allows you to separate compute and storage while saving money, and how identity, access, and management tools interact with your Dataflow pipelines. Lastly, we look at how to implement the right security model for your use case on Dataflow.
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Complete the introductory Prepare Data for ML APIs on Google Cloud skill badge to demonstrate skills in the following: cleaning data with Dataprep by Trifacta, running data pipelines in Dataflow, creating clusters and running Apache Spark jobs in Dataproc, and calling ML APIs including the Cloud Natural Language API, Google Cloud Speech-to-Text API, and Video Intelligence API. 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 course, and the final assessment challenge lab, to receive a skill badge that you can share with your network.
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This course helps learners create a study plan for the PDE (Professional Data Engineer) certification exam. Learners explore the breadth and scope of the domains covered in the exam. Learners assess their exam readiness and create their individual study plan.
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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. 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 course, and final assessment challenge lab, to receive a digital badge that you can share with your network.
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Complete the intermediate Create ML Models with BigQuery ML skill badge to demonstrate skills in the following: creating and evaluating machine learning models with BigQuery ML to make data predictions. 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 course, and the final assessment challenge lab, to receive a skill badge that you can share with your network.
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Incorporating machine learning into data pipelines increases the ability to extract insights from data. This course covers ways machine learning can be included in data pipelines on Google Cloud. For little to no customization, this course covers AutoML. For more tailored machine learning capabilities, this course introduces Notebooks and BigQuery machine learning (BigQuery ML). Also, this course covers how to productionalize machine learning solutions by using Vertex AI.
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Processing streaming data is becoming increasingly popular as streaming enables businesses to get real-time metrics on business operations. This course covers how to build streaming data pipelines on Google Cloud. Pub/Sub is described for handling incoming streaming data. The course also covers how to apply aggregations and transformations to streaming data using Dataflow, and how to store processed records to BigQuery or Bigtable for analysis. Learners get hands-on experience building streaming data pipeline components on Google Cloud by using QwikLabs.
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Data pipelines typically fall under one of the Extract and Load (EL), Extract, Load and Transform (ELT) or Extract, Transform and Load (ETL) paradigms. This course describes which paradigm should be used and when for batch data. Furthermore, this course covers several technologies on Google Cloud for data transformation including BigQuery, executing Spark on Dataproc, pipeline graphs in Cloud Data Fusion and serverless data processing with Dataflow. Learners get hands-on experience building data pipeline components on Google Cloud using Qwiklabs.
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Complete the intermediate Build a Data Warehouse with BigQuery skill badge 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. 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 course, and final assessment challenge lab, to receive a digital badge that you can share with your network. For practice with BigQuery fundamentals (including working with the console and command line), complete the course titled BigQuery Basics for Data Analysts.
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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 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.
This is the first course of the Data Engineering on Google Cloud series. After completing this course, enroll in the Building Batch Data Pipelines on Google Cloud course.
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This course introduces the Google Cloud big data and machine learning products and services that support the data-to-AI lifecycle. It explores the processes, challenges, and benefits of building a big data pipeline and machine learning models with Vertex AI on Google Cloud.
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Complete the introductory Derive Insights from BigQuery Data skill badge to demonstrate skills in the following: write SQL queries, query public tables, load sample data into BigQuery, troubleshoot common syntax errors with the query validator in BigQuery, and create reports in Looker Studio by connecting to BigQuery data. 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 course, and the final assessment challenge lab, to receive a skill badge that you can share with your network.
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Complete the intermediate Implement Cloud Security Fundamentals on Google Cloud skill badge 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. 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 course, and final assessment challenge lab, to receive a digital badge that you can share with your network.
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Complete the intermediate Deploy Kubernetes Applications on Google Cloud skill badge 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, and deploying Kubernetes applications with robust continuous delivery (CD) practices. 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 course and the final assessment challenge lab to receive a skill badge that you can share with your network.
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Organizations of all sizes are embracing the power and flexibility of the cloud to transform how they operate. However, managing and scaling cloud resources effectively can be a complex task.
Scaling with Google Cloud Operations explores the fundamental concepts of modern operations, reliability, and resilience in the cloud, and how Google Cloud can help support these efforts.
Part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.
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Many traditional enterprises use legacy systems and applications that often struggle to achieve the scale and speed needed to meet modern customer expectations. Business leaders and IT decision makers constantly have to choose between maintenance of legacy systems and investing in innovative new products and services.
This course explores the challenges of an outdated IT infrastructure and how businesses can modernize it using cloud technology. It begins by exploring the different compute options available in the cloud and the benefits of each, before turning to application modernization and Application Programming Interfaces (APIs). The course also considers a range of Google Cloud solutions that can help businesses to better develop and manage their systems, such as Compute Engine, App Engine, and Apigee.
This is the third course in the Cloud Digital Leader series. At the end of this course, enroll in the Understanding Google Cloud Security and Operations course.
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Cloud technology can bring great value to an organization, and combining the power of cloud technology with data has the potential to unlock even more value and create new customer experiences.
“Exploring Data Transformation with Google Cloud” explores the value data can bring to an organization and ways Google Cloud can make data useful and accessible.
Part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.
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There's much excitement about cloud technology and digital transformation, but often many unanswered questions.
For example: What is cloud technology? What does digital transformation mean? How can cloud technology help your organization? Where do you even begin?
If you've asked yourself any of these questions, you're in the right place. This course provides an overview of the types of opportunities and challenges that companies often encounter in their digital transformation journey. If you want to learn about cloud technology so you can excel in your role and help build the future of your business, then this introductory course on digital transformation is for you. This course is part of the Cloud Digital Leader learning path.
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Google Cloud Fundamentals: Core Infrastructure introduces important concepts and terminology for working with Google Cloud. Through videos and hands-on labs, this course presents and compares many of Google Cloud's computing and storage services, along with important resource and policy management tools.
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Google Cloud Application Programming Interfaces are the mechanism to interact with Google Cloud Services programmatically. This quest will give you hands-on practice with a variety of GCP APIs, which you will learn through working with Google’s APIs Explorer, a tool that allows you to browse APIs and run their methods interactively. By learning how to transfer data between Cloud Storage buckets, deploy Compute Engine instances, configure Dataproc clusters and much more, Exploring APIs will show you how powerful APIs are and why they are used almost exclusively by proficient GCP users. Enroll in this quest today.
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For everyone using Google Cloud Platform for the first time, getting familar with gcloud, Google Cloud's command line, will help you get up to speed faster. In this quest, you'll learn how to install and configure Cloud SDK, then use gcloud to perform some basic operations like creating VMs, networks, using BigQuery, and using gsutil to perform operations.
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Earn a skill badge by completing the Build and Secure Networks in Google Cloud course, where you will learn about multiple networking-related resources to build, scale, and secure your applications on Google Cloud. 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, and final assessment challenge lab, to receive a digital badge that you can share with your network.
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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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Earn a skill badge by completing the Develop your Google Cloud Network course, where you learn multiple ways to deploy and monitor applications including how to: explore IAM rols 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. A skill badge is an exclusivedigital 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, and the final assessment challenge lab, to receive a skill badge that you can share with your network.
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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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In this fundamental-level course, you will learn the ins and outs of Google Cloud's operations suite running on Google Kubernetes Engine, an important service for generating insights into the health of your applications. It provides a wealth of information in application monitoring, report logging, and diagnoses. The labs in this course will give you hands-on practice with and will teach you how to monitor virtual machines, generate logs and alerts, and create custom metrics for application data. It is recommended that the students have at least earned a Badge by completing the Google Cloud Essentials course. Additional lab experience with the labs in the Baseline - Infrastructure course will also be useful. Looking for a hands-on challenge lab to demonstrate your skills and validate your knowledge? On completing this course, enroll in and finish the additional challenge lab at the end of this course to receive an exclusive Google Cloud digital badge.
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Complete the introductory Monitor and Log with Google Cloud Observability skill badge 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. 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 course and the final assessment challenge lab to receive a skill badge that you can share with your network.
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This intermediate-level quest is unique among Qwiklabs quests. These labs have been curated to give operators hands-on practice with Anthos—a new, open application modernization platform on Google Cloud. Anthos enables you to build and manage modern hybrid applications. Tasks include: installing service mesh, collecting telemetry, and securing your microservices with service mesh policies. This quest is composed of labs targeted to teach you everything you need to know to introduce service mesh, and Anthos, into your next hybrid cloud project.
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Earn a skill badge by completing the Secure Workloads in Google Kubernetes Engine quest, where you learn about security at scale on Google Kubernetes Engine (GKE) including how to: migrate containers from virtual machines to Google Kubernetes Engine, restrict network connections in GKE using firewalls and Network Policies, use role-based access controls (RBAC) in GKE, use Binary Authorization for security controls of your images, secure applications in GKE using 3 access levels: host, network, Kubernetes API, and harden GKE cluster configurations. 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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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 advanced-level quest, you will get hands-on practice configuring Docker images, containers, and deploying fully-fledged Kubernetes Engine applications. This quest will teach you the practical skills needed for integrating container orchestration into your own workflow. Looking for a hands-on challenge lab to demonstrate your skills and validate your knowledge? On completing this quest, finish the additional Challenge Lab at the end of the Deploy to Kubernetes in Google Cloud Quest to receive an exclusive Google Cloud digital badge.
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Complete the intermediate Build Infrastructure with Terraform on Google Cloud skill badge to demonstrate skills in the following: Infrastructure as Code (IaC) principles using Terraform, provisioning and managing Google Cloud resources with Terraform configurations, effective state management (local and remote), and modularizing Terraform code for reusability and organization. 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 course and the final assessment challenge lab to receive a skill badge that you can share with your network.
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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. 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 course and the final assessment challenge lab to receive a skill badge that you can share with your network.
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Earn a skill badge by completing the Set Up an App Dev Environment on Google Cloud course, where you learn how to build and connect storage-centric cloud infrastructure using the basic capabilities of the of the following technologies: Cloud Storage, Identity and Access Management, Cloud Functions, and Pub/Sub. 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, and the final assessment challenge lab, to receive a skill badge that you can share with your network.
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Complete the introductory Implement Load Balancing on Compute Engine skill badge to demonstrate skills in the following: writing gcloud commands and using Cloud Shell, creating and deploying virtual machines in Compute Engine, and configuring network and HTTP load balancers. 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, and the final assessment challenge lab, to receive a skill badge that you can share with your network.
Professional Machine Learning Engineer Study Guide
Earned نوفمبر 10, 2024 EST
Responsible AI for Developers: Interpretability & Transparency
Earned نوفمبر 10, 2024 EST
Responsible AI for Developers: Fairness & Bias
Earned نوفمبر 10, 2024 EST
Create Generative AI Apps on Google Cloud
Earned أكتوبر 18, 2024 EDT
Generative AI Explorer - Vertex AI
Earned أكتوبر 17, 2024 EDT
Machine Learning Operations (MLOps) for Generative AI
Earned أكتوبر 17, 2024 EDT
Introduction to Large Language Models
Earned أكتوبر 17, 2024 EDT
Machine Learning Operations (MLOps): Getting Started
Earned أكتوبر 17, 2024 EDT
Introduction to Generative AI
Earned أكتوبر 17, 2024 EDT
Production Machine Learning Systems
Earned أكتوبر 16, 2024 EDT
Build and Deploy Machine Learning Solutions on Vertex AI
Earned أكتوبر 9, 2024 EDT
Classify Images with TensorFlow on Google Cloud
Earned أكتوبر 3, 2024 EDT
BigQuery for Machine Learning
Earned أكتوبر 1, 2024 EDT
Introduction to AI and Machine Learning on Google Cloud
Earned سبتمبر 24, 2024 EDT
Serverless Data Processing with Dataflow: Operations
Earned مايو 21, 2024 EDT
Trust and Security with Google Cloud
Earned أبريل 30, 2024 EDT
Innovating with Google Cloud Artificial Intelligence
Earned أبريل 30, 2024 EDT
Essential Google Cloud Infrastructure: Foundation
Earned أبريل 29, 2024 EDT
Build a Data Mesh with Dataplex
Earned أبريل 26, 2024 EDT
Serverless Data Processing with Dataflow: Develop Pipelines
Earned أبريل 24, 2024 EDT
Serverless Data Processing with Dataflow: Foundations
Earned مارس 31, 2024 EDT
Prepare Data for ML APIs on Google Cloud
Earned مارس 31, 2024 EDT
Preparing for your Professional Data Engineer Journey
Earned مارس 26, 2024 EDT
Engineer Data for Predictive Modeling with BigQuery ML
Earned مارس 26, 2024 EDT
Create ML Models with BigQuery ML
Earned مارس 26, 2024 EDT
Smart Analytics, Machine Learning, and AI on Google Cloud
Earned مارس 25, 2024 EDT
Building Resilient Streaming Analytics Systems on Google Cloud
Earned مارس 25, 2024 EDT
Building Batch Data Pipelines on Google Cloud
Earned مارس 24, 2024 EDT
Build a Data Warehouse with BigQuery
Earned مارس 23, 2024 EDT
Modernizing Data Lakes and Data Warehouses with Google Cloud
Earned مارس 23, 2024 EDT
Google Cloud Big Data and Machine Learning Fundamentals
Earned مارس 19, 2024 EDT
Derive Insights from BigQuery Data
Earned يناير 6, 2023 EST
Implement Cloud Security Fundamentals on Google Cloud
Earned يناير 6, 2023 EST
Deploy Kubernetes Applications on Google Cloud
Earned يناير 6, 2023 EST
Scaling with Google Cloud Operations
Earned يناير 2, 2023 EST
Infrastructure and Application Modernization with Google Cloud
Earned يناير 2, 2023 EST
Exploring Data Transformation with Google Cloud
Earned يناير 2, 2023 EST
Digital Transformation with Google Cloud
Earned يناير 2, 2023 EST
Google Cloud Fundamentals: Core Infrastructure
Earned يناير 2, 2023 EST
DEPRECATED Exploring APIs
Earned يناير 2, 2023 EST
Using the Cloud SDK Command Line
Earned ديسمبر 30, 2022 EST
Build a Secure Google Cloud Network
Earned ديسمبر 30, 2022 EST
Google Cloud Essentials
Earned ديسمبر 30, 2022 EST
Develop your Google Cloud Network
Earned مارس 24, 2022 EDT
Cloud Logging
Earned مارس 24, 2022 EDT
DEPRECATED Google Cloud's Operations Suite on GKE
Earned مارس 24, 2022 EDT
Monitor and Log with Google Cloud Observability
Earned مارس 23, 2022 EDT
Anthos Service Mesh
Earned مارس 11, 2022 EST
![Badge for [DEPRECATED] Secure Workloads in Google Kubernetes Engine](https://cdn.qwiklabs.com/wwGqG64Yt6I9sIdca%2FP9D3rXEyISvE9Q0nNOKpVfOws%3D)
[DEPRECATED] Secure Workloads in Google Kubernetes Engine
Earned يناير 14, 2022 EST
Kubernetes in Google Cloud
Earned يناير 10, 2022 EST
Build Infrastructure with Terraform on Google Cloud
Earned يناير 8, 2022 EST
Implement DevOps Workflows in Google Cloud
Earned ديسمبر 9, 2021 EST
Set Up an App Dev Environment on Google Cloud
Earned نوفمبر 26, 2021 EST
Implement Load Balancing on Compute Engine
Earned نوفمبر 24, 2021 EST