Tworzenie witryny w Google Cloud
Earned cze 13, 2021 EDT
This is the first of five courses in the Google Cloud Cybersecurity Certificate. In this course, you’ll explore the essentials of cybersecurity, including the security lifecycle, digital transformation, and key cloud computing concepts. You’ll identify common tools used by entry-level cloud security analysts to automate tasks.
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This is the second of five courses in the Google Cloud Cybersecurity Certificate. In this course, you’ll explore widely-used cloud risk management frameworks, exploring security domains, compliance lifecycles, and industry standards such as HIPAA, NIST CSF, and SOC. You'll develop skills in risk identification, implementation of security controls, compliance evaluation, and data protection management. Additionally, you'll gain hands-on experience with Google Cloud and multi-cloud tools specific to risk and compliance. This course also incorporates job application and interview preparation techniques, offering a comprehensive foundation to understand and effectively navigate the complex landscape of cloud risk management.
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Earn a skill badge by completing the The Basics of Google Cloud Compute skill badge course, where you learn how to work with virtual machines (VMs), persistent disks, and web servers using Compute Engine.
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In this course you will learn how to use the new generative AI features in Dialogflow CX to create virtual agents that can have more natural and engaging conversations with customers. Discover how to deploy generative fallback responses to gracefully handle errors and omissions in customer conversations, deploy generators to increase intent coverage, and structure, ingest, and manage data in a data store. And explore how to deploy and maintain generative AI agents using your data, and deploy and maintain hybrid agents in combination with existing intent-based design paradigms.
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Course two of the Architecting Hybrid Cloud with Anthos series prepares students to operate and observe Anthos environments. Through presentations and hands-on labs, participants explore adjusting existing clusters, setting up advanced traffic routing policies, securing communication across workloads, and observing clusters in Anthos. This course is a continuation of course one, Multi-Cluster, Multi-Cloud with Anthos, and assumes direct experience with the topics covered in that course.
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Complete the intermediate Inspect Rich Documents with Gemini Multimodality and Multimodal RAG skill badge course to demonstrate skills in the following: using multimodal prompts to extract information from text and visual data, generating a video description, and retrieving extra information beyond the video using multimodality with Gemini; building metadata of documents containing text and images, getting all relevant text chunks, and printing citations by using Multimodal Retrieval Augmented Generation (RAG) with Gemini.
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Complete the intermediate Explore Generative AI with the Gemini API in Vertex AI skill badge to demonstrate skills in text generation, image and video analysis for enhanced content creation, and applying function calling techniques within the Gemini API. Discover how to leverage sophisticated Gemini techniques, explore multimodal content generation, and expand the capabilities of your AI-powered projects.
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Complete the introductory Build Real World AI Applications with Gemini and Imagen skill badge to demonstrate skills in the following: image recognition, natural language processing, image generation using Google's powerful Gemini and Imagen models, deploying applications on the Vertex AI platform.
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Earn a skill badge by completing the App Engine`:` 3 ways course, where you learn how to use App Engine with Python, Go, and PHP.
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This course provides an introduction to using Terraform for Google Cloud. It enables learners to describe how Terraform can be used to implement infrastructure as code and to apply some of its key features and functionalities to create and manage Google Cloud infrastructure.
Learners will get hands-on practice building and managing Google Cloud resources using Terraform.
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Complete the introductory Get Started with Dataplex skill badge to demonstrate skills in the following: creating Dataplex assets, creating aspect types, and applying aspects to entries in Dataplex.
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This is the second of five courses in the Google Cloud Cybersecurity Certificate. In this course, you’ll explore widely-used cloud risk management frameworks, exploring security domains, compliance lifecycles, and industry standards such as HIPAA, NIST CSF, and SOC. You'll develop skills in risk identification, implementation of security controls, compliance evaluation, and data protection management. Additionally, you'll gain hands-on experience with Google Cloud and multi-cloud tools specific to risk and compliance. This course also incorporates job application and interview preparation techniques, offering a comprehensive foundation to understand and effectively navigate the complex landscape of cloud risk management.
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Earn an introductory skill badge by completing the Get Started with Google Workspace Tools course, where you will get introduced to Google's collaborative platform and learn to use Gmail, Calendar, Meet, Drive, Sheets, and AppSheet.
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Welcome to Observability in Google Cloud, the second part of a two-part course series. It is suggested that you complete part 1, Logging and Monitoring in Google Cloud, prior to taking this course.
This course is all about application performance management tools, including Error Reporting, Cloud Trace, and Cloud Profiler.
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Complete the intermediate Manage Kubernetes in Google Cloud skill badge course to demonstrate skills in the following: managing deployments with kubectl, monitoring and debugging applications on Google Kubernetes Engine (GKE), and continuous delivery techniques.
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Cloud Monitoring helps you keep an eye on your cloud setup, making sure everything runs smoothly. Whether you're just getting started or already working in the cloud, this tool is perfect for managing your infrastructure and apps. Jump in, get hands-on experience, and earn your newest Google Cloud Credential—no prior knowledge required!
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The demand for cloud skills has surged by 30% in the past year, and this set of hands-on labs is designed to help you gain them and earn an exclusive Google Cloud credential! Learn how to migrate databases with Cloud SQL, explore AI using Gemini, deploy apps with Cloud Run Canary Deployments, analyze data in BigQuery, and more. All with no prior experience needed!
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Explore AI-powered search technologies, tools, and applications in this course. Learn semantic search utilizing vector embeddings, hybrid search combining semantic and keyword approaches, and retrieval-augmented generation (RAG) minimizing AI hallucinations as a grounded AI agent. Gain practical experience with Vertex AI Vector Search to build your intelligent search engine.
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Welcome to the two-part course on Logging, Monitoring, and Observability in Google Cloud. The core operations tools in Google Cloud break down into two major categories. The operations-focused components and the application performance management tools. This course, Logging and Monitoring in Google Cloud, covers the operations-focused components including Logging, Monitoring, and Service Monitoring. After taking this course, it is suggested that you complete part 2, Observability in Google Cloud, to learn about the available application performance management tools.
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This course equips students to build highly reliable and efficient solutions on Google Cloud using proven design patterns. It is a continuation of the Architecting with Google Compute Engine or Architecting with Google Kubernetes Engine courses and assumes hands-on experience with the technologies covered in either of those courses. Through a combination of presentations, design activities, and hands-on labs, participants learn to define and balance business and technical requirements to design Google Cloud deployments that are highly reliable, highly available, secure, and cost-effective.
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This is the first of five courses in the Google Cloud Cybersecurity Certificate. In this course, you’ll explore the essentials of cybersecurity, including the security lifecycle, digital transformation, and key cloud computing concepts. You’ll identify common tools used by entry-level cloud security analysts to automate tasks.
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To szkolenie wprowadza w ważne kwestie dotyczące prywatności i bezpieczeństwa w dziedzinie AI. W jego trakcie przedstawiamy praktyczne techniki i narzędzia, które umożliwiają wdrożenie sprawdzonych metod w zakresie prywatności i bezpieczeństwa AI przy użyciu usług Google Cloud oraz narzędzi open source.
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Na tym szkoleniu przedstawiamy koncepcje interpretowalności i przejrzystości AI. Omawiamy na nim, jak ważna jest przejrzystość AI dla deweloperów i inżynierów. Pokazujemy praktyczne techniki i narzędzia, które pomagają osiągnąć interpretowalność oraz przejrzystość zarówno w danych, jak i modelach AI.
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Na tym szkoleniu przedstawiamy koncepcje odpowiedzialnej AI i zasad dotyczących AI. Omawiamy praktyczne metody identyfikowania obiektywności i uprzedzeń, a także ograniczania występowania uprzedzeń podczas używania AI/ML. W trakcie szkolenia przedstawiamy też praktyczne techniki i narzędzia, które umożliwiają wdrożenie sprawdzonych metod w zakresie odpowiedzialnej AI przy użyciu usług Google Cloud oraz narzędzi open source.
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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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In this course, you will be learning from ML Engineers and Trainers who work with the state-of-the-art development of ML pipelines here at Google Cloud. The first few modules will cover about TensorFlow Extended (or TFX), which is Google’s production machine learning platform based on TensorFlow for management of ML pipelines and metadata. You will learn about pipeline components and pipeline orchestration with TFX. You will also learn how you can automate your pipeline through continuous integration and continuous deployment, and how to manage ML metadata. Then we will change focus to discuss how we can automate and reuse ML pipelines across multiple ML frameworks such as tensorflow, pytorch, scikit learn, and xgboost. You will also learn how to use another tool on Google Cloud, Cloud Composer, to orchestrate your continuous training pipelines. And finally, we will go over how to use MLflow for managing the complete machine learning life cycle.
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This course equips machine learning practitioners with the essential tools, techniques, and best practices for evaluating both generative and predictive AI models. Model evaluation is a critical discipline for ensuring that ML systems deliver reliable, accurate, and high-performing results in production.
Participants will gain a deep understanding of various evaluation metrics, methodologies, and their appropriate application across different model types and tasks. The course will emphasize the unique challenges posed by generative AI models and provide strategies for tackling them effectively. By leveraging Google Cloud's Vertex AI platform, participants will learn how to implement robust evaluation processes for model selection, optimization, and continuous monitoring.
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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.
Learners will get hands-on practice using Vertex AI Feature Store's streaming ingestion at the SDK layer.
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Learn how to use NotebookLM to create a personalized study guide for the Professional Machine Learning Engineer certification exam (PMLE). You'll review NotebookLM features, create a notebook, and use the study guide to practice for a certification exam.
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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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This course explores the benefits of using Vertex AI Feature Store, how to improve the accuracy of ML models, and how to find which data columns make the most useful features. This course also includes content and labs on feature engineering using BigQuery ML, Keras, and TensorFlow.
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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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In many IT organizations, incentives are not aligned between developers, who strive for agility, and operators, who focus on stability. Site reliability engineering, or SRE, is how Google aligns incentives between development and operations and does mission-critical production support. Adoption of SRE cultural and technical practices can help improve collaboration between the business and IT. This course introduces key practices of Google SRE and the important role IT and business leaders play in the success of SRE organizational adoption.
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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 course is an introduction to Vertex AI Notebooks, which are Jupyter notebook-based environments that provide a unified platform for the entire machine learning workflow, from data preparation to model deployment and monitoring. The course covers the following topics: (1) The different types of Vertex AI Notebooks and their features and (2) How to create and manage Vertex AI Notebooks.
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Complete the introductory Prompt Design in Vertex AI skill badge to demonstrate skills in the following: prompt engineering, image analysis, and multimodal generative techniques, within Vertex AI. Discover how to craft effective prompts, guide generative AI output, and apply Gemini models to real-world marketing scenarios.
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This course covers building ML models with TensorFlow and Keras, improving the accuracy of ML models and writing ML models for scaled use.
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Complete the intermediate Develop Gen AI Apps with Gemini and Streamlit skill badge course to demonstrate skills in text generation, applying function calls with the Python SDK and Gemini API, and deploying a Streamlit application with Cloud Run. In this course, you learn Gemini prompting, test Streamlit apps in Cloud Shell, and deploy them as Docker containers in Cloud Run.
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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps you use Google products and services to develop, test, deploy, and manage applications. With help from Gemini, you learn how to develop and build a web application, fix errors in the application, develop tests, and query data. Using a hands-on lab, you experience how Gemini improves the software development lifecycle (SDLC).
Duet AI was renamed to Gemini, our next-generation model.
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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps engineers manage infrastructure. You learn how to prompt Gemini to find and understand application logs, create a GKE cluster, and investigate how to create a build environment. Using a hands-on lab, you experience how Gemini improves the DevOps workflow.
Duet AI was renamed to Gemini, our next-generation model.
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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps you secure your cloud environment and resources. You learn how to deploy example workloads into an environment in Google Cloud, identify security misconfigurations with Gemini, and remediate security misconfigurations with Gemini. Using a hands-on lab, you experience how Gemini improves your cloud security posture.
Duet AI was renamed to Gemini, our next-generation model.
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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps network engineers create, update, and maintain VPC networks. You learn how to prompt Gemini to provide specific guidance for your networking tasks, beyond what you would receive from a search engine. Using a hands-on lab, you experience how Gemini makes it easier for you to work with Google Cloud VPC networks.
Duet AI was renamed to Gemini, our next-generation model.
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The course begins with a discussion about data: how to improve data quality and perform exploratory data analysis. We describe Vertex AI AutoML and how to build, train, and deploy an ML model without writing a single line of code. You will understand the benefits of Big Query ML. We then discuss how to optimize a machine learning (ML) model and how generalization and sampling can help assess the quality of ML models for custom training.
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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps analyze customer data and predict product sales. You also learn how to identify, categorize, and develop new customers using customer data in BigQuery. Using hands-on labs, you experience how Gemini improves data analysis and machine learning workflows.
Duet AI was renamed to Gemini, our next-generation model.
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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps administrators provision infrastructure. You learn how to prompt Gemini to explain infrastructure, deploy GKE clusters and update existing infrastructure. Using a hands-on lab, you experience how Gemini improves the GKE deployment workflow.
Duet AI was renamed to Gemini, our next-generation model.
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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps developers build applications. You learn how to prompt Gemini to explain code, recommend Google Cloud services, and generate code for your applications. Using a hands-on lab, you experience how Gemini improves the application development workflow.
Duet AI was renamed to Gemini, our next-generation model.
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This course takes a real-world approach to the ML Workflow through a case study. An ML team faces several ML business requirements and use cases. The team must understand the tools required for data management and governance and consider the best approach for data preprocessing.
The team is presented with three options to build ML models for two use cases. The course explains why they would use AutoML, BigQuery ML, or custom training to achieve their objectives.
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Enterprises of all sizes have trouble making their information readily accessible to employees and customers alike. Internal documentation is frequently scattered across wikis, file shares, and databases. Similarly, consumer-facing sites often offer a vast selection of products, services, and information, but customers are frustrated by ineffective site search and navigation capabilities.
This course teaches you to use Generative AI App Builder to integrate enterprise-grade generative AI search.
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In this beginner-level course, you will learn about the Data Analytics workflow on Google Cloud and the tools you can use to explore, analyze, and visualize data and share your findings with stakeholders. Using a case study along with hands-on labs, lectures, and quizzes/demos, the course will demonstrate how to go from raw datasets to clean data to impactful visualizations and dashboards. Whether you already work with data and want to learn how to be successful on Google Cloud, or you’re looking to progress in your career, this course will help you get started. Almost anyone who performs or uses data analysis in their work can benefit from this course.
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Google Cloud Fundamentals for AWS Professionals 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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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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Im szerzej wykorzystuje się w firmach sztuczną inteligencję i systemy uczące się, tym większej wagi nabiera odpowiedzialne podejście do opracowywania tych technologii. Wielu organizacjom trudniej jest jednak wprowadzić zasady odpowiedzialnej AI w praktyce niż tylko o tym rozmawiać. To szkolenie jest przeznaczone dla osób, które chcą się dowiedzieć, jak wdrożyć odpowiedzialną AI w swojej organizacji.
W jego trakcie dowiesz się, jak robimy to w Google Cloud, oraz poznasz sprawdzone metody i wnioski z naszych działań w tym zakresie. Pomoże Ci to opracować własne podejście do odpowiedzialnej AI.
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Celem tego szybkiego szkolenia dla początkujących jest wyjaśnienie, czym jest odpowiedzialna AI i dlaczego jest ważna, oraz przedstawienie, jak Google wprowadza ją w swoich usługach. Szkolenie zawiera także wprowadzenie do siedmiu zasad Google dotyczących sztucznej inteligencji.
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To szybkie szkolenie dla początkujących wyjaśnia, czym są duże modele językowe (LLM) oraz jakie są ich zastosowania. Przedstawia również możliwości zwiększenia ich wydajności przez dostrajanie przy użyciu promptów oraz narzędzia Google, które pomogą Ci tworzyć własne aplikacje korzystające z generatywnej AI.
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This course teaches you how to create an image captioning model by using deep learning. You learn about the different components of an image captioning model, such as the encoder and decoder, and how to train and evaluate your model. By the end of this course, you will be able to create your own image captioning models and use them to generate captions for images
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This course introduces you to the Transformer architecture and the Bidirectional Encoder Representations from Transformers (BERT) model. You learn about the main components of the Transformer architecture, such as the self-attention mechanism, and how it is used to build the BERT model. You also learn about the different tasks that BERT can be used for, such as text classification, question answering, and natural language inference.This course is estimated to take approximately 45 minutes to complete.
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This course gives you a synopsis of the encoder-decoder architecture, which is a powerful and prevalent machine learning architecture for sequence-to-sequence tasks such as machine translation, text summarization, and question answering. You learn about the main components of the encoder-decoder architecture and how to train and serve these models. In the corresponding lab walkthrough, you’ll code in TensorFlow a simple implementation of the encoder-decoder architecture for poetry generation from the beginning.
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This course will introduce you to the attention mechanism, a powerful technique that allows neural networks to focus on specific parts of an input sequence. You will learn how attention works, and how it can be used to improve the performance of a variety of machine learning tasks, including machine translation, text summarization, and question answering. This course is estimated to take approximately 45 minutes to complete.
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This course introduces diffusion models, a family of machine learning models that recently showed promise in the image generation space. Diffusion models draw inspiration from physics, specifically thermodynamics. Within the last few years, diffusion models became popular in both research and industry. Diffusion models underpin many state-of-the-art image generation models and tools on Google Cloud. This course introduces you to the theory behind diffusion models and how to train and deploy them on Vertex AI.
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Celem tego szybkiego szkolenia dla początkujących jest wyjaśnienie, czym jest generatywna AI oraz jakie są jej zastosowania. Szkolenie przedstawia również różnice pomiędzy tą technologią a tradycyjnymi systemami uczącymi się, a także narzędzia Google, które pomogą Ci tworzyć własne aplikacje korzystające z generatywnej AI.
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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 introduces Vertex AI Studio, a tool to interact with generative AI models, prototype business ideas, and launch them into production. Through an immersive use case, engaging lessons, and a hands-on lab, you’ll explore the prompt-to-product lifecycle and learn how to leverage Vertex AI Studio for Gemini multimodal applications, prompt design, prompt engineering, and model tuning. The aim is to enable you to unlock the potential of gen AI in your projects with Vertex AI Studio.
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Aby zdobyć odznakę umiejętności, ukończ szkolenia Introduction to Generative AI, Introduction to Large Language Models i Introduction to Responsible AI. Zdaj test i pokaż, że rozumiesz podstawowe koncepcje związane z generatywną AI.
Odznaka umiejętności to cyfrowa odznaka wydawana przez Google Cloud, która potwierdza Twoją wiedzę o produktach i usługach Google Cloud. Ustaw swój profil jako publiczny i dodaj odznakę umiejętności do profilu w mediach społecznościowych, aby pochwalić się swoim osiągnięciem.
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This course introduces Google Cloud's AI and machine learning (ML) capabilities, with a focus on developing both generative and predictive AI projects. It explores the various technologies, products, and tools available throughout the data-to-AI lifecycle, empowering data scientists, AI developers, and ML engineers to enhance their expertise through interactive exercises.
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The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide an overview of concepts central to cloud basics, big data, and machine learning, and where and how Google Cloud fits in.
By the end of the series of courses, learners will be able to articulate these concepts and demonstrate some hands-on skills.
The courses should be completed in the following order:
1. Google Cloud Computing Foundations: Cloud Computing Fundamentals
2. Google Cloud Computing Foundations: Infrastructure in Google Cloud
3. Google Cloud Computing Foundations: Networking and Security in Google Cloud
4. Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud
This final course in the series reviews managed big data services, machine learning and its value, and how to demonstrate your skill set in Google Cloud further by earning Skill Badges.
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The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide an overview of concepts central to cloud basics, big data, and machine learning, and where and how Google Cloud fits in.
By the end of the series of courses, learners will be able to articulate these concepts and demonstrate some hands-on skills.
The courses should be completed in the following order:
1. Google Cloud Computing Foundations: Cloud Computing Fundamentals
2. Google Cloud Computing Foundations: Infrastructure in Google Cloud
3. Google Cloud Computing Foundations: Networking and Security in Google Cloud
4. Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud
This third course covers cloud automation and management tools and building secure networks.
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Szkolenie Podstawy przetwarzania danych w Google Cloud pozwoli osobom z niewielkim
lub zerowym doświadczeniem z zakresu przetwarzania danych w chmurze szczegółowo
zapoznać się z najważniejszymi pojęciami z zakresu podstaw chmury, big data i systemów uczących się.
Zawiera także informacje o tym, gdzie i jak można wykorzystać Google Cloud.
Po zakończeniu szkolenia uczestnicy będą potrafili wyjaśnić pojęcia dotyczące przetwarzania danych w chmurze,
big data i systemów uczących się oraz zademonstrować wybrane umiejętności praktyczne.
To szkolenie należy do serii szkoleń o nazwie Google Cloud Computing Foundations (Podstawy usług w chmurze Google).
Szkolenia należy ukończyć w następującej kolejności:
Google Cloud Computing Foundations: Cloud Computing Fundamentals - Locales
Google Cloud Computing Foundations: Infrastructure in Google Cloud - Locales
Google Cloud Computing Foundations: Networking and Security in Google Cloud - Locales
Google Cloud Computing Foundation…
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Szkolenie Podstawy przetwarzania danych w Google Cloud pozwoli osobom z niewielkim lub zerowym doświadczeniem z zakresu
przetwarzania danych w chmurze szczegółowo zapoznać się z najważniejszymi pojęciami z zakresu podstaw chmury, big data i systemów uczących się.
Zawiera także informacje o tym, gdzie i jak można wykorzystać Google Cloud.
Po zakończeniu szkolenia uczestnicy będą potrafili wyjaśnić pojęcia dotyczące przetwarzania danych w chmurze, big data i systemów uczących się oraz
zademonstrować wybrane umiejętności praktyczne.
TTo szkolenie należy do serii szkoleń o nazwie Google Cloud Computing Foundations (Podstawy usług w chmurze Google).
Szkolenia należy ukończyć w następującej kolejności:
Google Cloud Computing Foundations: Cloud Computing Fundamentals - Locales
Google Cloud Computing Foundations: Infrastructure in Google Cloud - Locales
Google Cloud Computing Foundations: Networking and Security in Google Cloud - Locales
Google Cloud Computing Foundatio…
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Welcome to Cloud Hero, Gamers! Click "Join this Game" to start this game. To modify your player name or avatar, go to your My Account page at https://google.qwiklabs.com. Points are earned by completing the steps in the lab.... and bonus points are earned for speed....
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Welcome Gamers! You will compete to see who can finish the game with the highest score. Earn the points by completing the steps in the lab.... and get bonus points for speed! Be sure to click "End" when you're done with each lab to get the maximum points. All players will be awarded the game badge.
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Welcome Gamers! Today's game is all about experimenting with Big Query for Machine Learning! Use real life case studies to learn various concepts of BQML and have fun. Take labs to earn points. The faster you complete the lab objectives, the higher your score.
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Earn a skill badge by completing the Create Conversational AI Agents with Dialogflow CX quest, where you will learn how to create a conversational virtual agent, including how to: define intents and entities, use versions and environments, create conversational branching, and use IVR features. 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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Get started with Go (Golang) by reviewing Go code, and then creating and deploying simple Go apps on Google Cloud. Go is an open source programming language that makes it easy to build fast, reliable, and efficient software at scale. Go runs native on Google Cloud, and is fully supported on Google Kubernetes Engine, Compute Engine, App Engine, Cloud Run, and Cloud Functions. Go is a compiled language and is faster and more efficient than interpreted languages. As a result, Go requires no installed runtime like Node, Python, or JDK to execute.
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Cloud Hero is played around the world, in person and online. Today, you have the opportunity to become one of the Cloud Heroes! Today's game is all about Networking skills. Earn the most points by completing the steps in the lab.... and get bonus points for speed! Be sure to click "End" when you're done with each lab to get the maximum points. All players will be awarded the game badge.
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Get hands-on practice with Google Cloud! You will compete with your peers to see who can finish this game with the most points. Speed and accuracy will be used to calculate your scores — earn points by completing the labs accurately and bonus points for speed! Be sure to click “End” where you’re done with each lab to be rewarded your points.
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Complete the introductory Create and Manage Cloud SQL for PostgreSQL Instances skill badge to demonstrate skills in the following: migrating, configuring, and managing Cloud SQL for PostgreSQL instances and databases.
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Earn a skill badge by completing the Detect Manufacturing Defects using Visual Inspection AI course, where you learn how to use Visual Inspection AI to deploy a solution artifact and test that it can successfully identify defects in a manufacturing process.
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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 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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Earn the introductory skill badge by completing the Automate Data Capture at Scale with Document AI course. In this course, you learn how to extract, process, and capture data using Document AI.
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Blockchain and related technologies, such as distributed ledger and distributed apps, are becoming new value drivers and solution priorities in many industries. In this course you will gain hands-on experience with distributed ledger and the exploration of blockchain datasets in Google Cloud. It brings the research and solution work of Google's Allen Day into self-paced labs for you to run and learn directly. Since this course uses advanced SQL in BigQuery, a SQL-in-BigQuery refresher lab is at the start.
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Complete the intermediate Perform Predictive Data Analysis in BigQuery skill badge course to demonstrate skills in the following: creating datasets in BigQuery by importing CSV and JSON files; harnessing the power of BigQuery with sophisticated SQL analytical concepts, including using BigQuery ML to train an expected goals model on soccer event data and evaluate the impressiveness of World Cup goals.
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Get hands-on practice with Google Cloud! You will compete with your peers to see who can finish this game with the most points. Speed and accuracy will be used to calculate your scores — earn points by completing the labs accurately and bonus points for speed! Be sure to click “End” where you’re done with each lab to be rewarded your points.
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Ten kurs wprowadzający jest inny niż wszystkie pozostałe oferowane kursy. Jego moduły zostały wybrane tak, aby udostępnić specjalistom z branży IT praktyczne ćwiczenia w zakresie tematów i usług, znajomość których jest potrzebna do uzyskania certyfikatu Google Cloud Associate Cloud Engineer. Od uprawnień i zarządzania siecią po wdrażanie Kubernetes Engine – ten kurs składa się ze specjalnych modułów, w trakcie których sprawdzisz swoją wiedzę na temat Google Cloud. Ćwiczenia w ramach tych modułów pozwolą Ci zwiększyć swoje umiejętności i kompetencje, ale zalecamy również zapoznanie się z przewodnikiem po egzaminie i innymi dostępnymi materiałami przygotowawczymi.
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Earn the intermediate skill badge by completing the Build and Deploy Machine Learning Solutions on Vertex AI skill badge course, where you 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.
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Complete the introductory Migrate MySQL Data to Cloud SQL Using Database Migration Service skill badge course to demonstrate skills in the following: migrating MySQL data to Cloud SQL using different job types and connectivity options available in Database Migration Service and migrating MySQL user data when running Database Migration Service jobs.
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This course offers hands-on practice with migrating MySQL data to Cloud SQL using Database Migration Service. You start with an introductory lab that briefly reviews how to get started with Cloud SQL for MySQL, including how to connect to Cloud SQL instances using the Cloud Console. Then, you continue with two labs focused on migrating MySQL databases to Cloud SQL using different job types and connectivity options available in Database Migration Service. The course ends with a lab on migrating MySQL user data when running Database Migration Service jobs.
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Aby zdobyć odznakę umiejętności, ukończ szkolenie Budowanie bezpiecznej sieci Google Cloud, w trakcie którego poznasz różne związane z siecią zasoby do budowania, skalowania i zabezpieczania aplikacji w Google Cloud.
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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.
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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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Aby zdobyć odznakę umiejętności, ukończ szkolenie Budowanie sieci w Google Cloud, w trakcie którego poznasz różne sposoby wdrażania i monitorowania aplikacji i dowiesz się, jak: przeglądać role uprawnień, dodawać/usuwać dostęp do projektu, tworzyć sieci VPC, wdrażać i monitorować maszyny wirtualne Compute Engine, pisać zapytania SQL oraz wdrażać aplikacje przy użyciu różnych metod w Kubernetes.
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Obtain a competitive advantage through DevOps. DevOps is an organizational and cultural movement that aims to increase software delivery velocity, improve service reliability, and build shared ownership among software stakeholders. In this course you will learn how to use Google Cloud to improve the speed, stability, availability, and security of your software delivery capability. DevOps Research and Assessment has joined Google Cloud. How does your team measure up? Take this five question multiple-choice quiz and find out!
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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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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 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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Szkolenie Google Cloud Fundamentals: Core Infrastructure wprowadza ważne pojęcia i terminologię potrzebne w pracy z Google Cloud. Za pomocą filmów i praktycznych modułów szkolenie prezentuje oraz porównuje usługi Google Cloud umożliwiające między innymi przetwarzanie i przechowywanie danych, a także zawiera ważne materiały i narzędzia do zarządzania zasadami.
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Complete the intermediate Develop Serverless Applications on Cloud Run skill badge course to demonstrate skills in the following: integrating Cloud Run with Cloud Storage for data management, architecting resilient asynchronous systems using Cloud Run and Pub/Sub, constructing REST API gateways powered by Cloud Run, and building and deploying services on Cloud Run.
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Workspace is Google's collaborative applications platform, delivered from Google Cloud. In this introductory-level course you will get hands-on practice with Workspace’s core applications from a user perspective. Although there are many more applications and tool components to Workspace than are covered here, you will get experience with the primary apps: Gmail, Calendar, Sheets and a handful of others. Each lab can be completed in 10-15 minutes, but extra time is provided to allow self-directed free exploration of the applications.
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In this advanced-level quest, you will learn the ins and outs of developing GCP applications in Python. The first labs will walk you through the basics of environment setup and application data storage with Cloud Datastore. Once you have a handle on the fundamentals, you will get hands-on practice deploying Python applications on Kubernetes and App Engine (the latter is the same framework that powers Snapchat!) With specialized bonus labs that teach user authentication and backend service development, this quest will give you practical experience so you can start developing robust Python applications straight away.
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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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Ukończ szkolenie wprowadzające Przygotowywanie danych do użycia z interfejsami ML w Google Cloud, aby zdobyć odznakę potwierdzającą zdobycie następujących umiejętności: czyszczenie danych przy użyciu usługi Dataprep firmy Trifacta, uruchamianie potoków danych w Dataflow, tworzenie klastrów i uruchamianie zadań Apache Spark w Dataproc, a także wywoływanie interfejsów API dotyczących uczenia maszynowego, w tym Cloud Natural Language API, Google Cloud Speech-to-Text API oraz Video Intelligence API.
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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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It's no secret that machine learning is one of the fastest growing fields in tech, and Google Cloud 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 APIs by taking labs like Detect Labels, Faces, and Landmarks in Images with the Cloud Vision API. Looking for a hands-on challenge lab to demonstrate your skills and validate your knowledge? 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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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 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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Ukończ szkolenie wprowadzające Uzyskiwanie statystyk z danych BigQuery, aby zdobyć odznakę potwierdzającą zdobycie następujących umiejętności: pisanie zapytań SQL, tworzenie zapytań dotyczących tabel publicznych, wczytywanie przykładowych danych w BigQuery, naprawianie typowych błędów składniowych przy użyciu walidatora zapytań w BigQuery oraz tworzenie raportów w Looker Studio przez tworzenie połączenia z danymi BigQuery.
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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 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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Aby zdobyć odznakę umiejętności, ukończ szkolenie Konfigurowanie środowiska programistycznego w Google Cloud, w trakcie którego dowiesz się, jak utworzyć i podłączyć infrastrukturę w chmurzę do przechowywania danych przy użyciu podstawowych funkcji technologii Cloud Storage, Identity and Access Management, Cloud Functions oraz Pub/Sub.
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Ukończ szkolenie wprowadzające Wdrażanie równoważenia obciążenia Cloud Load Balancing w Compute Engine, aby zdobyć odznakę potwierdzającą zdobycie następujących umiejętności: tworzenie i wdrażanie maszyn wirtualnych w Compute Engine oraz konfigurowanie sieciowych systemów równoważenia obciążenia i systemów równoważenia obciążenia aplikacji.
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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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Aby zdobyć odznakę umiejętności potwierdzającą opanowanie podstaw, ukończ kurs wprowadzający Tworzenie witryny w Google Cloud. Jest on oparty na serii materiałów wideo Get Cooking in Cloud i obejmuje te tematy: Wdrażanie witryny w Cloud RunHostowanie aplikacji internetowej w Compute EngineTworzenie, wdrażanie i skalowanie witryny w Google Kubernetes EngineMigracja z aplikacji monolitycznej do architektury mikroserwisów przy użyciu Cloud Build
Introduction to Security Principles in Cloud Computing
Earned gru 11, 2025 EST
Strategies for Cloud Security Risk Management
Earned gru 10, 2025 EST
The Basics of Google Cloud Compute
Earned kwi 5, 2025 EDT
Conversational AI on Vertex AI and Dialogflow CX
Earned lut 10, 2025 EST
DEPRECATED Cloud Operations and Service Mesh with Anthos
Earned lut 9, 2025 EST
Inspect Rich Documents with Gemini Multimodality and Multimodal RAG
Earned lut 7, 2025 EST
Explore Generative AI with the Gemini API in Vertex AI
Earned lut 7, 2025 EST
Build Real World AI Applications with Gemini and Imagen
Earned lut 6, 2025 EST
App Engine: 3 Ways
Earned sty 27, 2025 EST
Getting Started with Terraform for Google Cloud
Earned sty 24, 2025 EST
Get Started with Dataplex
Earned sty 24, 2025 EST
Strategies for Cloud Security Risk Management
Earned sty 16, 2025 EST
Get Started with Google Workspace Tools
Earned sty 15, 2025 EST
Observability in Google Cloud
Earned sty 7, 2025 EST
Manage Kubernetes in Google Cloud
Earned sty 7, 2025 EST
Level 2: Cloud Monitoring
Earned gru 19, 2024 EST
Level 1: Cloud Infrastructure and Data
Earned gru 16, 2024 EST
Vector Search and Embeddings
Earned gru 12, 2024 EST
Logging and Monitoring in Google Cloud
Earned gru 4, 2024 EST
Reliable Google Cloud Infrastructure: Design and Process
Earned lis 29, 2024 EST
Introduction to Security Principles in Cloud Computing
Earned lis 15, 2024 EST
Odpowiedzialna AI dla deweloperów: prywatność i bezpieczeństwo
Earned lis 15, 2024 EST
Odpowiedzialna AI dla deweloperów: interpretowalność i przejrzystość
Earned lis 15, 2024 EST
Odpowiedzialna AI dla deweloperów: obiektywność i uprzedzenia
Earned lis 14, 2024 EST
Create Generative AI Apps on Google Cloud
Earned lis 14, 2024 EST
ML Pipelines on Google Cloud
Earned lis 14, 2024 EST
Machine Learning Operations (MLOps) with Vertex AI: Model Evaluation
Earned lis 14, 2024 EST
Machine Learning Operations (MLOps) with Vertex AI: Manage Features
Earned lis 14, 2024 EST
Build a Certification Study Guide: PMLE
Earned lis 14, 2024 EST
Production Machine Learning Systems
Earned paź 15, 2024 EDT
Feature Engineering
Earned paź 15, 2024 EDT
Machine Learning Operations (MLOps): Getting Started
Earned paź 15, 2024 EDT
Developing a Google SRE Culture
Earned paź 14, 2024 EDT
Machine Learning Operations (MLOps) for Generative AI
Earned paź 14, 2024 EDT
Working with Notebooks in Vertex AI
Earned paź 14, 2024 EDT
Prompt Design in Vertex AI
Earned paź 14, 2024 EDT
Build, Train and Deploy ML Models with Keras on Google Cloud
Earned paź 14, 2024 EDT
Develop Gen AI Apps with Gemini and Streamlit
Earned paź 14, 2024 EDT
Gemini for end-to-end SDLC
Earned paź 12, 2024 EDT
Gemini for DevOps Engineers
Earned paź 12, 2024 EDT
Gemini for Security Engineers
Earned paź 12, 2024 EDT
Gemini for Network Engineers
Earned paź 12, 2024 EDT
Launching into Machine Learning
Earned paź 11, 2024 EDT
Gemini for Data Scientists and Analysts
Earned paź 10, 2024 EDT
Gemini for Cloud Architects
Earned paź 9, 2024 EDT
Gemini for Application Developers
Earned paź 9, 2024 EDT
Machine Learning in the Enterprise
Earned sty 9, 2024 EST
Enterprise Search on Generative AI App Builder
Earned sty 9, 2024 EST
Introduction to Data Analytics on Google Cloud
Earned sty 9, 2024 EST
Google Cloud Fundamentals for AWS Professionals
Earned gru 25, 2023 EST
Google Cloud Big Data and Machine Learning Fundamentals
Earned gru 25, 2023 EST
Responsible AI: Applying AI Principles with Google Cloud - Polski
Earned gru 25, 2023 EST
Introduction to Responsible AI - Polski
Earned gru 25, 2023 EST
Introduction to Large Language Models - Polski
Earned gru 25, 2023 EST
Create Image Captioning Models
Earned gru 24, 2023 EST
Transformer Models and BERT Model
Earned gru 24, 2023 EST
Encoder-Decoder Architecture
Earned gru 24, 2023 EST
Attention Mechanism
Earned gru 24, 2023 EST
Introduction to Image Generation
Earned gru 24, 2023 EST
Introduction to Generative AI - Polski
Earned gru 24, 2023 EST
Generative AI Explorer - Vertex AI
Earned gru 24, 2023 EST
Introduction to Vertex AI Studio
Earned gru 24, 2023 EST
Generative AI Fundamentals - Polski
Earned gru 22, 2023 EST
Introduction to AI and Machine Learning on Google Cloud
Earned gru 22, 2023 EST
Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud
Earned gru 20, 2023 EST
Google Cloud Computing Foundations: Networking & Security in Google Cloud
Earned gru 20, 2023 EST
[DEPRECATED] Google Cloud Computing Foundations: Infrastructure in Google Cloud - Locales
Earned gru 20, 2023 EST
[DEPRECATED]-Google Cloud Computing Foundations: Cloud Computing Fundamentals - Polski
Earned gru 12, 2023 EST
Cloud Hero: Kubernetes
Earned gru 29, 2022 EST
Intro to Infrastructure
Earned lis 23, 2022 EST
Intro to BigQuery: Analytics & Machine Learning
Earned paź 24, 2022 EDT
DEPRECATED Create Conversational AI Agents with Dialogflow CX
Earned paź 3, 2022 EDT
Getting Started with Go on Google Cloud
Earned paź 2, 2022 EDT
Cloud Hero Network Skills
Earned wrz 30, 2022 EDT
Cloud Hero IAM & Security Skills
Earned wrz 26, 2022 EDT
Create and Manage Cloud SQL for PostgreSQL Instances
Earned wrz 15, 2022 EDT
DEPRECATED Detect Manufacturing Defects Using Visual Inspection AI
Earned wrz 10, 2022 EDT
Engineer Data for Predictive Modeling with BigQuery ML
Earned wrz 9, 2022 EDT
Use Machine Learning APIs on Google Cloud
Earned wrz 8, 2022 EDT
Automate Data Capture at Scale with Document AI
Earned sie 30, 2022 EDT
DEPRECATED Applied Data: Blockchain
Earned sie 28, 2022 EDT
Perform Predictive Data Analysis in BigQuery
Earned sie 24, 2022 EDT
Cloud Hero Infra Skills
Earned sie 23, 2022 EDT
Inżynieria chmury
Earned sie 15, 2022 EDT
DEPRECATED Build and Deploy Machine Learning Solutions on Vertex AI
Earned sie 15, 2022 EDT
Migrate MySQL Data to Cloud SQL Using Database Migration Service
Earned lut 9, 2022 EST
Migrating MySQL data to Cloud SQL using Database Migration Service
Earned lut 9, 2022 EST
Budowanie bezpiecznej sieci Google Cloud
Earned lut 8, 2022 EST
Build Infrastructure with Terraform on Google Cloud
Earned lut 8, 2022 EST
Automate Deployment and Manage Traffic on a Google Cloud Network
Earned lut 7, 2022 EST
Budowanie sieci w Google Cloud
Earned lut 2, 2022 EST
DevOps Essentials
Earned lut 2, 2022 EST
Implement Cloud Security Fundamentals on Google Cloud
Earned lut 2, 2022 EST
Set Up a Google Cloud Network
Earned lut 1, 2022 EST
Prepare Data for Looker Dashboards and Reports
Earned sty 30, 2022 EST
Google Cloud Fundamentals: Core Infrastructure - Polski
Earned lis 3, 2021 EDT
Develop Serverless Applications on Cloud Run
Earned lip 20, 2021 EDT
Google Workspace Essentials
Earned lip 4, 2021 EDT
DEPRECATED Application Development - Python
Earned cze 30, 2021 EDT
DEPRECATED Explore Machine Learning Models with Explainable AI
Earned cze 30, 2021 EDT
Przygotowywanie danych do użycia z interfejsami ML w Google Cloud
Earned cze 27, 2021 EDT
Create ML Models with BigQuery ML
Earned cze 27, 2021 EDT
Machine Learning APIs
Earned cze 25, 2021 EDT
Develop Serverless Apps with Firebase
Earned cze 24, 2021 EDT
[DEPRECATED] Build Interactive Apps with Google Assistant
Earned cze 24, 2021 EDT
Uzyskiwanie statystyk z danych BigQuery
Earned cze 23, 2021 EDT
Monitor and Log with Google Cloud Observability
Earned cze 21, 2021 EDT
Deploy Kubernetes Applications on Google Cloud
Earned cze 20, 2021 EDT
Konfigurowanie środowiska programistycznego w Google Cloud
Earned cze 19, 2021 EDT
Wdrażanie równoważenia obciążenia Cloud Load Balancing w Compute Engine
Earned cze 16, 2021 EDT
Google Cloud Essentials
Earned cze 14, 2021 EDT
Tworzenie witryny w Google Cloud
Earned cze 13, 2021 EDT