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Naveen Rohith

Member since 2023

Gold League

42180 points
[DEPRECATED] Gemini for end-to-end SDLC Earned авг. 27, 2024 EDT
[DEPRECATED] Gemini for Security Engineers Earned авг. 27, 2024 EDT
[DEPRECATED] Gemini for Cloud Architects Earned авг. 27, 2024 EDT
Responsible AI: Applying AI Principles with Google Cloud Earned авг. 27, 2024 EDT
Introduction to Large Language Models Earned авг. 27, 2024 EDT
[DEPRECATED]Introduction to Responsible AI Earned авг. 27, 2024 EDT
Qwiklabs Trivia August 2023 Earned авг. 28, 2023 EDT
Create a Secure Data Lake on Cloud Storage Earned авг. 27, 2023 EDT
Manage Kubernetes in Google Cloud Earned авг. 27, 2023 EDT
Monitoring in Google Cloud Earned авг. 26, 2023 EDT
Implement Speech and Language Solutions with Pre-trained APIs Earned авг. 26, 2023 EDT
Using the Google Cloud Speech API Earned авг. 26, 2023 EDT
Analyze Sentiment with Natural Language API Earned авг. 26, 2023 EDT
Implement Cloud Storage and Data Protection Solutions Earned авг. 25, 2023 EDT
Use APIs to Work with Cloud Storage Earned авг. 25, 2023 EDT
Use Machine Learning APIs on Google Cloud Earned авг. 25, 2023 EDT
Analyze Speech and Language with Google APIs Earned авг. 25, 2023 EDT
Integrate BigQuery Data and Google Workspace using Apps Script Earned авг. 25, 2023 EDT
Build a Website on Google Cloud Earned авг. 24, 2023 EDT
Build a Secure Google Cloud Network Earned авг. 24, 2023 EDT
Level 2: Apps Script and Networks Earned авг. 21, 2023 EDT
Cloud Architecture: Design, Implement, and Manage Earned авг. 20, 2023 EDT
Implement DevOps Workflows in Google Cloud Earned авг. 20, 2023 EDT
Develop Serverless Apps with Firebase Earned авг. 19, 2023 EDT
Engineer Data for Predictive Modeling with BigQuery ML Earned авг. 19, 2023 EDT
Level 3: GenAI Earned авг. 19, 2023 EDT
Level 1: BigQuery ML, Cloud Architecture and Devops Skills Earned авг. 17, 2023 EDT
Exploring and Preparing your Data with BigQuery Earned авг. 17, 2023 EDT
Applying Advanced LookML Concepts in Looker Earned авг. 17, 2023 EDT
Google Cloud Fundamentals for AWS Professionals Earned авг. 10, 2023 EDT
Manage Data Models in Looker Earned авг. 9, 2023 EDT
Build LookML Objects in Looker Earned авг. 9, 2023 EDT
Create ML Models with BigQuery ML Earned авг. 9, 2023 EDT
Analyze Images with the Cloud Vision API Earned июля 29, 2023 EDT
Set Up a Google Cloud Network Earned июля 29, 2023 EDT
Enrich Metadata and Discovery of Lakehouse Data Earned июля 25, 2023 EDT
Secure Lakehouse Data Earned июля 25, 2023 EDT
Qwiklabs Trivia July 2023 Earned июля 25, 2023 EDT
Implement Sensitive Data Protection on Google Cloud Earned июля 25, 2023 EDT
Level 2: Data Deep Dive Earned июля 25, 2023 EDT
Data Catalog Fundamentals Earned июля 24, 2023 EDT
Derive Insights from BigQuery Data Earned июля 24, 2023 EDT
Prepare Data for ML APIs on Google Cloud Earned июля 24, 2023 EDT
Prepare Data for Looker Dashboards and Reports Earned июля 22, 2023 EDT
Creating New BigQuery Datasets and Visualizing Insights Earned июля 20, 2023 EDT
DEPRECATED Networking Fundamentals on Google Cloud Earned июля 19, 2023 EDT
Level 1: AppDev and Infrastructure Earned июля 19, 2023 EDT
The Basics of Google Cloud Compute Earned июля 19, 2023 EDT
Getting Started with Go on Google Cloud Earned июля 18, 2023 EDT
Deploy and Manage Applications on Google App Engine Earned июля 18, 2023 EDT
Achieving Advanced Insights with BigQuery Earned июля 17, 2023 EDT
Applying Machine Learning to your Data with Google Cloud Earned июля 17, 2023 EDT
Developing Data Models with LookML Earned июля 17, 2023 EDT
Analyzing and Visualizing Data in Looker Earned июля 17, 2023 EDT
[DEPRECATED] Google Cloud Big Data and Machine Learning Fundamentals Earned июля 12, 2023 EDT
Introduction to Generative AI Earned июля 10, 2023 EDT

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 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 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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As the use of enterprise Artificial Intelligence and Machine Learning continues to grow, so too does the importance of building it responsibly. A challenge for many is that talking about responsible AI can be easier than putting it into practice. If you’re interested in learning how to operationalize responsible AI in your organization, this course is for you. In this course, you will learn how Google Cloud does this today, together with best practices and lessons learned, to serve as a framework for you to build your own responsible AI approach.

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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 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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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. Give your career a boost with hands-on experience on GCP and partner services and earn the August badge.

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Complete the introductory Create a Secure Data Lake on Cloud Storage skill badge course to demonstrate skills in the following: securing and configuring a Cloud Storage bucket, using Gemini for text generation, managing IAM access control, and establishing a Knowledge Catalog lake for data governance.

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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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Complete the introductory Monitoring in Google Cloud skill badge course to demonstrate skills in the following: using Cloud Monitoring tools to monitor resources on Google Cloud.

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Earn the Introductory Skill Badge by completing the Implement Speech and Language Solutions with Pre-trained APIs course, where you learn how to use speech related API tools to synthesise and transcribe speech.

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Earn a skill badge by completing the Using the Google Cloud Speech API skill badge course, where you learn how create a Speech-to-Text API request, transcribe audio speech to text, and transcribe speech.

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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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Earn a Skill Badge by completing the Implement Cloud Storage and Data Protection Solutions course. Learn to create a Cloud Storage bucket, use the command line, and protect objects with Bucket Lock.

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Complete the introductory Use APIs to Work with Cloud Storage skill badge to demonstrate skills in the following: using APIs to work with Cloud Storage resources, including the Cloud Storage API.

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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 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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Complete the introductory Integrate BigQuery Data and Google Workspace using Apps Script skill badge course to demonstrate skills in connecting Workspace products with BigQuery via AppSheet.

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Earn the introductory skill badge by completing the Build a Website on Google Cloud skill badge course. This course is based on the Get Cooking in Cloud series and covers`:`Deploying a website on Cloud RunHosting a web app on Compute EngineCreating, deploying, and scaling your website on Google Kubernetes EngineMigrating from a monolithic application to a microservices architecture using Cloud Build

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Earn a skill badge by completing the Build a Secure Google Cloud Network skill badge course, where you will learn about multiple networking-related resources to build, scale, and secure your applications on Google Cloud.

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For organisations to thrive in the digital world, it is important for them to have secured networks to protect sensitive data, prevent cyber threats and maintain customer trust. Learn the principles of network design, security and management and integrating BigQuery Data and Google Workspace using Apps Script. Gain hands-on experience with labs carefully designed to nurture and assess your tech skills and set you on a course to earn your first Google Cloud credential.

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Earn a skill badge by completing the Cloud Architecture: Design, Implement, and Manage to demonstrate skills in the following: deploy a publicly accessible website using Apache web servers, configure a Compute Engine VM using startup scripts, configure secure RDP using a Windows Bastion host and firewall rules, build and deploy a Docker image to a Kubernetes cluster and then update it, and create a CloudSQL instance and import a MySQL database. This skill badge is a great resource for understanding topics that will appear in the Google Cloud Certified Professional Cloud Architect certification exam.

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Complete the intermediate Implement DevOps Workflows in Google Cloud skill badge to demonstrate skills in the following: creating and managing Git repositories, launching, managing, and scaling deployments on Google Kubernetes Engine (GKE), and architecting CI/CD pipelines that automate container image builds and deployments to GKE.

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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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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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Recently, a McKinsey report found that Generative AI could add up to $4.4 trillion a year to the global economy, signaling an imminent surge in the demand for GenAI professionals. Now is the perfect time to get a head start and gain hands-on experience with Google Cloud's powerful GenAI tools and techniques, carefully designed to enhance your tech skills and set you on a promising course. Play now to be at the forefront of innovation, shaping the future with GenAI and earning your first Google Cloud GenAI game badge!

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The world around us is changing and mastering future-driven technologies is the key to success. We want you to get started by learning a little of everything! Discover machine learning in data analysis, build scalable cloud solutions and accelerate software development that will shape the future. The possibilities in the Arcade are endless and all of those will lead you towards earning your first Google Cloud Credential. No prior experience required.

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In this course, we see what the common challenges faced by data analysts are and how to solve them with the big data tools on Google Cloud. You’ll pick up some SQL along the way and become very familiar with using BigQuery and Dataprep to analyze and transform your datasets. This is the first course of the From Data to Insights with Google Cloud series. After completing this course, enroll in the Creating New BigQuery Datasets and Visualizing Insights course.

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In this course, you will get hands-on experience applying advanced LookML concepts in Looker. You will learn how to use Liquid to customize and create dynamic dimensions and measures, create dynamic SQL derived tables and customized native derived tables, and use extends to modularize your LookML code.

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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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Complete the intermediate Manage Data Models in Looker skill badge course to demonstrate skills in the following: maintaining LookML project health; utilizing SQL runner for data validation; employing LookML best practices; optimizing queries and reports for performance; and implementing persistent derived tables and caching policies.

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Complete the introductory Build LookML Objects in Looker skill badge course to demonstrate skills in the following: building new dimensions and measures, views, and derived tables; setting measure filters and types based on requirements; updating dimensions and measures; building and refining Explores; joining views to existing Explores; and deciding which LookML objects to create based on business requirements.

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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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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 Enrich Metadata and Discovery of Lakehouse Data skill badge course to demonstrate skills in BigQuery, Lakehouse, and Knowledge Catalog. You create Lakehouse tables and enrich metadata management and discovery of the table data.

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Complete the introductory Secure Lakehouse Data skill badge course to demonstrate skills with IAM, BigQuery, Lakehouse, and Knowledge Catalog to create and secure Lakehouse tables.

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Welcome to Qwiklabs Trivia for July! 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 July badge.

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Complete the Implement Sensitive Data Protection on Google Cloud Skill Badge course to demonstrate skills in the following: using Sensitive Data Protection services (including the Cloud Data Loss Prevention API) to inspect, redact, and de-identify sensitive data in Google Cloud.

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The demand for data skills is growing rapidly, and we want you to get ahead! According to a report by the McKinsey Global Institute, the demand for data scientists and analysts is expected to grow by 150% by 2025. There are a lot of different aspects to any data role, so it's important to start with the basics - and we’ve got you covered. Learn how to tap into ML APIs, dive into your first data lake, and learn how the experts think about securing data. No experience required.

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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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Complete the introductory Derive Insights from BigQuery Data skill badge course to demonstrate skills in the following: Write SQL queries.Query public tables.Load sample data into BigQuery.Troubleshoot common syntax errors with the query validator in BigQuery.Create reports in Data Studio by connecting to BigQuery data.

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Complete the introductory Prepare Data for ML APIs on Google Cloud skill badge to demonstrate skills in the following: cleaning data with Dataprep by Trifacta, running data pipelines in Dataflow, creating clusters and running Apache Spark jobs in Managed Service for Apache Spark, and calling ML APIs including the Cloud Natural Language API, Google Cloud Speech-to-Text API, and Video Intelligence API.

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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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This is the second course in the Data to Insights course series. Here we will cover how to ingest new external datasets into BigQuery and visualize them with Looker Studio. We will also cover intermediate SQL concepts like multi-table JOINs and UNIONs which will allow you to analyze data across multiple data sources. Note: Even if you have a background in SQL, there are BigQuery specifics (like handling query cache and table wildcards) that may be new to you. After completing this course, enroll in the Achieving Advanced Insights with BigQuery course.

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Earn a skill badge by completing the Networking Fundamentals on Google Cloud quest, where you learn how to work with VPC networks and load balancers on Google Cloud. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete 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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Demand for cloud-skilled workers is rising. According to a report by Indeed, cloud computing jobs are expected to grow by 22% over the next five years, much faster than the average for all occupations. Play now to get hands-on experience building with Google Cloud's powerful coding and infrastructure management tools. Each lab teaches and tests your growing tech skills, and sets you on the path to your first Google Cloud credential.

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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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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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Earn a Skill Badge by completing the Deploy and Manage Applications on Google App Engine course, where you learn how to use App Engine with Python, Go, and PHP.

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The third course in this course series is Achieving Advanced Insights with BigQuery. Here we will build on your growing knowledge of SQL as we dive into advanced functions and how to break apart a complex query into manageable steps. We will cover the internal architecture of BigQuery (column-based sharded storage) and advanced SQL topics like nested and repeated fields through the use of Arrays and Structs. Lastly we will dive into optimizing your queries for performance and how you can secure your data through authorized views. After completing this course, enroll in the Applying Machine Learning to your Data with Google Cloud course.

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In this course, we define what machine learning is and how it can benefit your business. You'll see a few demos of ML in action and learn key ML terms like instances, features, and labels. In the interactive labs, you will practice invoking the pretrained ML APIs available as well as build your own Machine Learning models using just SQL with BigQuery ML.

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This course empowers you to develop scalable, performant LookML (Looker Modeling Language) models that provide your business users with the standardized, ready-to-use data that they need to answer their questions. Upon completing this course, you will be able to start building and maintaining LookML models to curate and manage data in your organization’s Looker instance.

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In this course, you learn how to do the kind of data exploration and analysis in Looker that would formerly be done primarily by SQL developers or analysts. Upon completion of this course, you will be able to leverage Looker's modern analytics platform to find and explore relevant content in your organization’s Looker instance, ask questions of your data, create new metrics as needed, and build and share visualizations and dashboards to facilitate data-driven decision making.

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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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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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