Anshuman Mishra
Date d'abonnement : 2019
Ligue d'Argent
10930 points
DEPRECATED Create Conversational AI Agents with Dialogflow CX
Earned juil. 3, 2023 EDT
[DEPRECATED]Introduction to Responsible AI
Earned juin 26, 2023 EDT
Generative AI Explorer - Agent Platform
Earned juin 24, 2023 EDT
Introduction to Large Language Models
Earned juin 24, 2023 EDT
Introduction to Generative AI
Earned juin 10, 2023 EDT
Organize and Govern Data with Knowledge Catalog
Earned juin 3, 2023 EDT
Machine Learning APIs
Earned mai 24, 2023 EDT
App Building with AppSheet
Earned mai 21, 2023 EDT
Store, Process, and Manage Data on Google Cloud - Command Line
Earned avr. 19, 2023 EDT
Store, Process, and Manage Data on Google Cloud - Console
Earned avr. 19, 2023 EDT
Level 1: Managing Resources and Data in the Cloud
Earned avr. 19, 2023 EDT
Monitor and Manage Google Cloud Resources
Earned avr. 17, 2023 EDT
Managing Cloud Infrastructure with Terraform
Earned mars 28, 2023 EDT
Qwiklabs Trivia March 2023
Earned mars 22, 2023 EDT
Workspace: Add-ons
Earned mars 6, 2023 EST
Data Catalog Fundamentals
Earned fév. 2, 2023 EST
New Year, New Skills: Red Challenge (A)
Earned jan. 18, 2023 EST
New Year, New Skills: Green Challenge (A)
Earned jan. 5, 2023 EST
Cloud Hero: Kubernetes
Earned déc. 31, 2022 EST
Cloud Engineering
Earned déc. 31, 2022 EST
Qwiklabs Trivia August 2022
Earned déc. 31, 2022 EST
Qwiklabs Trivia December 2022
Earned déc. 23, 2022 EST
No code november 2022
Earned nov. 4, 2022 EDT
Qwiklabs Trivia October 2022
Earned oct. 28, 2022 EDT
Cloud Healthcare API
Earned oct. 27, 2022 EDT
Sports Analytics: Pitch Perfect BigQuery
Earned juin 6, 2022 EDT
Qwiklabs Trivia May 2022
Earned mai 29, 2022 EDT
Qwiklabs Trivia Game
Earned avr. 5, 2022 EDT
Tipoff! Sports data analysis with GCP
Earned mars 17, 2022 EDT
DEPRECATED Applying BigQuery ML's Classification, Regression, and Demand Forecasting for Retail Applications
Earned fév. 18, 2022 EST
NCAA® March Madness®: Bracketology with Google Cloud
Earned fév. 18, 2022 EST
Data Science on Google Cloud
Earned fév. 18, 2022 EST
DEPRECATED Language, Speech, Text, & Translation with Google Cloud APIs
Earned fév. 7, 2022 EST
Baseline: Infrastructure
Earned oct. 28, 2021 EDT
Baseline: Data, ML, AI
Earned sept. 21, 2021 EDT
Learn to Earn Cloud Challenge: Architecture
Earned sept. 17, 2021 EDT
Understanding LookML in Looker
Earned sept. 9, 2021 EDT
BigQuery for Machine Learning
Earned juin 18, 2021 EDT
DEPRECATED Google Cloud Solutions II: Data and Machine Learning
Earned juin 1, 2021 EDT
Google Cloud Essentials
Earned sept. 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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This is an introductory-level microlearning course aimed at explaining what responsible AI is, why it's important, and how Google implements responsible AI in their products. It also introduces Google's 3 AI principles.
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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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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. Explore other content in the Gemini Agent Ready (GEAR) program.
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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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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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This fundamental-level quest is unique amongst the other quest offerings. The labs have been curated to give IT professionals hands-on practice with topics and services that appear in the Google Cloud Certified Associate Cloud Engineer Certification. From IAM, to networking, to Kubernetes engine deployment, this quest is composed of specific labs that will put your Google Cloud knowledge to the test. Be aware that while practice with these labs will increase your skills and abilities, we recommend that you also review the exam guide and other available preparation resources.
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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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If you are a novice cloud developer looking for hands-on practice beyond Google Cloud Essentials, this course is for you. You will get practical experience through labs that dive into Cloud Storage and other key application services like Monitoring and Cloud Functions. You will develop valuable skills that are applicable to any Google Cloud initiative. 1-minute videos walk you through key concepts for these labs.
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Big data, machine learning, and artificial intelligence are today’s hot computing topics, but these fields are quite specialized and introductory material is hard to come by. Fortunately, Google Cloud provides user-friendly services in these areas, and with this introductory-level quest, so you can take your first steps with tools like BigQuery, Cloud Speech API and Video Intelligence. Want extra help? 1-minute videos walk you through key concepts for each lab.
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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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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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