Anshuman Mishra
Учасник із 2019
Срібна ліга
Кількість балів: 10930
DEPRECATED Create Conversational AI Agents with Dialogflow CX
Earned лип. 3, 2023 EDT
Introduction to Responsible AI - Українська
Earned черв. 26, 2023 EDT
Generative AI Explorer - Agent Platform
Earned черв. 24, 2023 EDT
Introduction to Large Language Models - Українська
Earned черв. 24, 2023 EDT
Introduction to Generative AI - Українська
Earned черв. 10, 2023 EDT
Organize and Govern Data with Knowledge Catalog
Earned черв. 3, 2023 EDT
Machine Learning APIs
Earned трав. 24, 2023 EDT
App Building with AppSheet
Earned трав. 21, 2023 EDT
Store, Process, and Manage Data on Google Cloud - Command Line
Earned квіт. 19, 2023 EDT
Store, Process, and Manage Data on Google Cloud - Console
Earned квіт. 19, 2023 EDT
Level 1: Managing Resources and Data in the Cloud
Earned квіт. 19, 2023 EDT
Monitor and Manage Google Cloud Resources
Earned квіт. 17, 2023 EDT
Managing Cloud Infrastructure with Terraform
Earned бер. 28, 2023 EDT
Qwiklabs Trivia March 2023
Earned бер. 22, 2023 EDT
Workspace: Add-ons
Earned бер. 6, 2023 EST
Data Catalog Fundamentals
Earned лют. 2, 2023 EST
New Year, New Skills: Red Challenge (A)
Earned січ. 18, 2023 EST
New Year, New Skills: Green Challenge (A)
Earned січ. 5, 2023 EST
Cloud Hero: Kubernetes
Earned груд. 31, 2022 EST
Розробка хмарних технологій
Earned груд. 31, 2022 EST
Qwiklabs Trivia August 2022
Earned груд. 31, 2022 EST
Qwiklabs Trivia December 2022
Earned груд. 23, 2022 EST
No code november 2022
Earned лист. 4, 2022 EDT
Qwiklabs Trivia October 2022
Earned жовт. 28, 2022 EDT
Cloud Healthcare API
Earned жовт. 27, 2022 EDT
Sports Analytics: Pitch Perfect BigQuery
Earned черв. 6, 2022 EDT
Qwiklabs Trivia May 2022
Earned трав. 29, 2022 EDT
Qwiklabs Trivia Game
Earned квіт. 5, 2022 EDT
Tipoff! Sports data analysis with GCP
Earned бер. 17, 2022 EDT
DEPRECATED Applying BigQuery ML's Classification, Regression, and Demand Forecasting for Retail Applications
Earned лют. 18, 2022 EST
NCAA® March Madness®: Bracketology with Google Cloud
Earned лют. 18, 2022 EST
Data Science on Google Cloud
Earned лют. 18, 2022 EST
DEPRECATED Language, Speech, Text, & Translation with Google Cloud APIs
Earned лют. 7, 2022 EST
Початок роботи з інфраструктурою
Earned жовт. 28, 2021 EDT
Початок роботи з даними, машинним навчанням і штучним інтелектом
Earned вер. 21, 2021 EDT
Learn to Earn Cloud Challenge: Architecture
Earned вер. 17, 2021 EDT
Understanding LookML in Looker
Earned вер. 9, 2021 EDT
BigQuery for Machine Learning
Earned черв. 18, 2021 EDT
DEPRECATED Google Cloud Solutions II: Data and Machine Learning
Earned черв. 1, 2021 EDT
Основи Google Cloud
Earned вер. 17, 2020 EDT
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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Це ознайомлювальний курс мікронавчання, який має пояснити, що таке відповідальне використання штучного інтелекту, чому воно важливе і як компанія Google реалізує його у своїх продуктах. Крім того, у цьому курсі викладено 7 принципів Google щодо штучного інтелекту.
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The Generative AI Explorer - Agent Platform course 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 Gemini models in Agent Platform. 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 custom training in Agent Platform and deploy it to an endpoint in Agent Platform.
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У цьому ознайомлювальному курсі мікронавчання ви дізнаєтеся, що таке великі мовні моделі, де вони використовуються і як підвищити їх ефективність коригуванням запитів. Він також охоплює інструменти Google, які допоможуть вам створювати власні додатки на основі генеративного штучного інтелекту.
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Це ознайомлювальний курс мікронавчання, який має пояснити, що таке генеративний штучний інтелект, як він використовується й чим відрізняється від традиційних методів машинного навчання. Він також охоплює інструменти Google, які допоможуть вам створювати власні додатки на основі генеративного штучногоінтелекту.
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Complete the introductory Organize and Govern Data with Knowledge Catalog skill badge to demonstrate skills in the following: creating Knowledge Catalog assets, creating aspect types, and applying aspects to entries in Knowledge Catalog.
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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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Earn a skill badge by completing the App Building with AppSheet course, where you learn how to build, configure, and publish apps using AppSheet.
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Cloud Storage, Cloud Functions, and Cloud Pub/Sub are all Google Cloud Platform services that can be used to store, process, and manage data. All three services can be used together to create a variety of data-driven applications. In this skill badge you use Cloud Storage to store images, Cloud Functions to process the images, and Cloud Pub/Sub to send the images to another application.
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Cloud Storage, Cloud Functions, and Cloud Pub/Sub are all Google Cloud Platform services that can be used to store, process, and manage data. All three services can be used together to create a variety of data-driven applications. In this skill badge you use Cloud Storage to store images, Cloud Functions to process the images, and Cloud Pub/Sub to send the images to another application.
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More than 90% of IT leaders say they're looking to grow their cloud environments in the next several years, yet more than 80% of those same leaders identified a lack of skills as a barrier to growth. This means that tech skills (particularly cloud skills!) are in high demand. Want to grow your skills and take advantage of the opportunity? Play now to get hands-on experience with Google Cloud. Each lab teaches and tests your growing tech skills, and sets you on the path to your first Google Cloud credential. No experience required.
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Complete the introductory Monitor and Manage Google Cloud Resources skill badge to demonstrate skills in the following: granting and revoking IAM permissions; installing monitoring and logging agents; creating, deploying, and testing an event-driven Cloud Run function.
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In this Quest, the experienced user of Google Cloud will learn how to describe and launch cloud resources with Terraform, an open source tool that codifies APIs into declarative configuration files that can be shared amongst team members, treated as code, edited, reviewed, and versioned. In these nine hands-on labs, you will work with example templates and understand how to launch a range of configurations, from simple servers, through full load-balanced applications.
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Welcome to Qwiklabs Trivia for March! Each week, we will release a new set of questions to test your knowledge. You will have opportunities to play throughout the month. Give your career a boost with hands on experience on GCP and partner services and earn the March badge.
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This course demonstrates the power of integrating Google Cloud services and tools with Workspace applications - like using Node.js to build a survey bot, the Natural Language API to recognize sentiment in a Google Doc, and building a chat bot with Apps Script.
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Data Catalog is deprecated and will be discontinued on January 30, 2026. You can still complete this course if you want to. For steps to transition your Data Catalog users, workloads, and content to Dataplex Catalog, see Transition from Data Catalog to Dataplex Catalog (https://cloud.google.com/dataplex/docs/transition-to-dataplex-catalog). Data Catalog is a fully managed and scalable metadata management service that empowers organizations to quickly discover, understand, and manage all of their data. In this quest you will start small by learning how to search and tag data assets and metadata with Data Catalog. After learning how to build your own tag templates that map to BigQuery table data, you will learn how to build MySQL, PostgreSQL, and SQLServer to Data Catalog Connectors.
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New year, new skills! Add 23 (or so) new skills and techniques to your toolkit, while sampling certification-based learning paths. Whether you're thinking about Google Cloud's Data, DevOps or Networking certifications, or just exploring, this is the challenge to help you start your year strong.
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New year, new skills! Add 23 (or so) new skills and techniques to your toolkit, while sampling certification-based learning paths. Whether you're thinking about Google Cloud's Data, DevOps or Networking certifications, or just exploring, this is the challenge to help you start your year strong.
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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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Цей вступний курс унікальний серед інших курсів. Практичні заняття розроблено так, щоб ІТ-фахівці могли опрацювати теми й сервіси, які ввійдуть до сертифікації Google Cloud Certified Associate Cloud Engineer. У цей курс входять спеціально розроблені практичні заняття, зокрема присвячені керуванню ідентифікацією і доступом, організації мереж і розгортанню Kubernetes Engine, щоб ви могли перевірити свої знання про Google Cloud. Майте на увазі, що хоча виконання цих практичних занять покращить ваші навички й уміння, радимо також переглянути посібник із підготовки до іспиту й інші доступні ресурси.
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Welcome to Qwiklabs Trivia for August! Each week, we will release a new set of questions to test your knowledge. You will have opportunities to play throughout the month. Prepare for ACE and test your knowledge to earn the August badge.
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Welcome to Qwiklabs Trivia for December! Each week, we will release a new set of questions to test your knowledge. You will have opportunities to play throughout the month. Give your career a boost with hands on experience on GCP and partner services and earn the December badge.
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No-code development platforms allow programmers and non-programmers alike to build beautiful, useful apps. Complete labs to learn new skills and earn the badge. No experience needed!
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Welcome to Qwiklabs Trivia for October! Each week, we will release a new set of questions to test your knowledge. You will have opportunities to play throughout the month. Give your career a boost with hands on experience on GCP and partner services and earn the October badge.
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Cloud Healthcare API bridges the gap between care systems and applications built on Google Cloud. By supporting standards-based data formats and protocols of existing healthcare technologies, Cloud Healthcare API connects your data to advanced Google Cloud capabilities, including streaming data processing with Cloud Dataflow, scalable analytics with BigQuery, and machine learning with Cloud Machine Learning Engine. In this Quest you will use the Cloud Healthcare API to ingest and process data in the industry standard FHIR, HL7v2 and DICOM formats, train a TensorFlow model for prediction with FHIR data, and also gain practice with de-identification of datasets.
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In this introductory level Quest you will gain practical experience on the fundamentals of sports data science using BigQuery. Start your journey by creating 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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Welcome to Qwiklabs Trivia for May! Each week, we will release a new set of questions to test your knowledge. You will have opportunities to play throughout the month. Build your Data and BigQuery skills and test your knowledge to earn the May badge.
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Ready for this week's Trivia? Complete all the labs and add this premium badge to your profile. Get credits worth $25 to continue your cloud learning journey. Hurry and join today as the game closes soon. Access code: 1q-trivia-422.
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Are you ready for #MarchMadness? (Learn more about this high-intensity competition: bitly of https://medium.com/analyzing-ncaa-college-basketball-with-gcp.) No matter what sport you follow, they all have one thing in common: data. Learn how Google Cloud can help you step your game up, both on and off the court (field, track, pitch, you get the idea…) Complete this badge and win 25$ worth Cloud Skills Boost credits! Access code:- 1q-tipoff-418
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In this course you will learn how to use several BigQuery ML features to improve retail use cases. Predict the demand for bike rentals in NYC with demand forecasting, and see how to use BigQuery ML for a classification task that predicts the likelihood of a website visitor making a purchase.
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In this series of labs you will learn how to use BigQuery to analyze NCAA basketball data with SQL. Build a Machine Learning Model to predict the outcomes of NCAA March Madness basketball tournament games.
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This is the first of two Quests of hands-on labs is derived from the exercises from the book Data Science on Google Cloud Platform, 2nd Edition by Valliappa Lakshmanan, published by O'Reilly Media, Inc. In this first Quest, covering up through chapter 8, you are given the opportunity to practice all aspects of ingestion, preparation, processing, querying, exploring and visualizing data sets using Google Cloud tools and services.
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In this quest you will use a collection of Google APIs that are all related to language, and speech. You will use the Speech-to-Text API to transcribe an audio file into a text file, the Cloud Translation API to translate from one language to another, the Cloud Translation API to detect what language is being used and translate to a different language, the Natural Language API to classify text and analyze sentiment, and create synthetic speech.
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Якщо ви лише пробуєте розробляти хмарні рішення й шукаєте практичні заняття на додаток до кваліфікаційного курсу "Знайомство з Google Cloud", тоді цей курс саме для вас. Ви отримаєте прикладний досвід завдяки практичним заняттям, присвяченим Cloud Storage і іншим ключовим сервісам додатків, як-от Monitoring і Cloud Functions. Ви отримаєте цінні навички, які можна застосовувати в будь-яких проєктах Google Cloud.
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Зараз усі говорять про масиви даних, машинне навчання й штучний інтелект, але це досить вузькоспеціалізовані теми, про які важко знайти матеріали, зрозумілі не лише спеціалістам. На щастя, Google Cloud пропонує зручні сервіси в цих галузях, а завдяки цьому вступному курсу ви зможете ознайомитися з такими інструментами, як BigQuery, Cloud Speech API і Video Intelligence.
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Welcome to the Learn To Earn Cloud Challenge architecture track! These eight labs give you a blueprint of GCP's building blocks. At the end of each lab, you'll have hands-on experience with another tool or service to add to your resume. Complete this game to earn the Architecture game badge, and you'll be one step closer to collecting all four Learn to Earn Cloud Challenge badges (see "what's next" below for more information). Race the clock to increase your score and watch your name rise on the leaderboard. Good luck!
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In this course, you will get hands-on experience with LookML in Looker. You will learn how to write LookML code to create new dimensions and measures, create derived tables and join them to Explores, filter Explores, and define caching policies in LookML.
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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.
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In this advanced-level quest, you will learn how to harness serious Google Cloud computing power to run big data and machine learning jobs. The hands-on labs will give you use cases, and you will be tasked with implementing big data and machine learning practices utilized by Google’s very own Solutions Architecture team. From running Big Query analytics on tens of thousands of basketball games, to training TensorFlow image classifiers, you will quickly see why Google Cloud is the go-to platform for running big data and machine learning jobs.
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На цьому вступному курсі ви отримаєте практичний досвід роботи з основними інструментами й сервісами Google Cloud. Також вам доступні додаткові відео, які допоможуть краще зрозуміти контекст і закріпити знання щодо тем, розглянутих у практичних заняттях. Google Cloud "Основи" – це рекомендований початковий курс для тих, хто починає вивчати Google Cloud. Ви можете розпочати навчання, маючи мінімальні знання про хмарні технології або взагалі не маючи їх, і отримати практичний досвід, який зможете застосувати у своєму першому хмарному проєкті Google Cloud. "Основи Google Cloud" дають вичерпне уявленні про ключові функції платформи – від написання команд у Cloud Shell і розгортання першої віртуальної машини до запуску додатків на Kubernetes Engine і використання розподілу навантаження.
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