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Wykorzystuj swoje umiejętności w konsoli Google Cloud

Chen Ming Teh

Jest członkiem od 2024

Liga złota

18525 pkt.
Podstawy: infrastruktura Earned maj 15, 2024 EDT
Manage Kubernetes in Google Cloud Earned maj 15, 2024 EDT
Google Cloud Big Data and Machine Learning Fundamentals Earned maj 15, 2024 EDT
Generative AI Explorer - Vertex AI Earned maj 15, 2024 EDT
Intro to ML: Language Processing Earned maj 14, 2024 EDT
Monitor and Manage Google Cloud Resources Earned maj 13, 2024 EDT
Build Infrastructure with Terraform on Google Cloud Earned maj 13, 2024 EDT
Perform Predictive Data Analysis in BigQuery Earned maj 13, 2024 EDT
Create ML Models with BigQuery ML Earned maj 13, 2024 EDT
Analyze Images with the Cloud Vision API Earned maj 13, 2024 EDT
Gemini for Data Scientists and Analysts Earned maj 12, 2024 EDT
Analyze Speech and Language with Google APIs Earned maj 12, 2024 EDT
Classify Images with TensorFlow on Google Cloud Earned maj 10, 2024 EDT
Analyze Sentiment with Natural Language API Earned maj 8, 2024 EDT
Integrating Applications with Gemini 1.0 Pro on Google Cloud Earned maj 7, 2024 EDT

Jeśli dopiero zaczynasz programować w chmurze i szukasz praktycznych ćwiczeń wykraczających poza treści z kursu „Podstawy Google Cloud”, ten kurs jest dla Ciebie. Zdobędziesz praktyczne doświadczenie dzięki modułom poświęconym Cloud Storage i innym kluczowym usługom aplikacji, takim jak Monitoring i Cloud Functions. Zdobędziesz cenne umiejętności, które przydadzą się w każdym przedsięwzięciu z zastosowaniem Google Cloud.

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Complete the intermediate Manage Kubernetes in Google Cloud skill badge to demonstrate skills in the following: managing deployments with kubectl, monitoring and debugging applications on Google Kubernetes Engine (GKE), and continuous delivery techniques. 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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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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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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It’s no secret that machine learning is one of the fastest growing fields in tech, and the Google Cloud Platform has been instrumental in furthering its development. With a host of APIs, GCP has a tool for just about any machine learning job. In this introductory course, you will get hands-on practice with machine learning as it applies to language processing by taking labs that will enable you to extract entities from text, and perform sentiment and syntactic analysis as well as use the Speech to Text API for transcription.

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This challenge lab tests your skills and knowledge from the labs in the Monitor and Manage Google Cloud Resources quest. You should be familiar with the content of labs before attempting this lab.

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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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Earn the intermediate skill badge by completing the Perform Predictive Data Analysis in BigQuery course, where you will gain practical experience on the fundamentals of sports data science using BigQuery, including how to create a soccer dataset in BigQuery by importing CSV and JSON files; harness the power of BigQuery with sophisticated SQL analytical concepts, including using BigQuery ML to train an expected goals model on the soccer event data, and evaluate the impressiveness of World Cup goals.

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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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Earn a skill badge by completing the Analyze Images with the Cloud Vision API quest, where you discover how to leverage the Cloud Vision API for various tasks, including extracting text from images.

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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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Earn a skill badge by completing the Analyze Speech and Language with Google APIs quest, where you learn how to use the Natural Language and Speech APIs in real-world settings.

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Earn the intermediate Skill Badge by completing the Classify Images with TensorFlow on Google Cloud skill badge course where you learn how to use TensorFlow and Vertex AI to create and train machine learning models. You primarily interact with Vertex AI Workbench user-managed notebooks.

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Earn a skill badge by completing the Analyze Sentiment with Natural Language API quest, where you learn how the API derives sentiment from text.

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This short course on integrating applications with Gemini 1.0 Pro models on Google Cloud helps you discover the Gemini API and its generative AI models. The course teaches you how to access the Gemini 1.0 Pro and Gemini 1.0 Pro Vision models from code. It lets you test the capabilities of the models with text, image, and video prompts from an app.

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