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Hernando Ivan Teddy

Member since 2021

Diamond League

56718 points
Automate Data Capture at Scale with Document AI Earned Sep 22, 2025 EDT
Vertex AI Search for Commerce Earned Sep 22, 2025 EDT
Workspace: Add-ons Earned Sep 21, 2025 EDT
Secure BigLake Data Earned Sep 19, 2025 EDT
Cloud Speech API: 3 Ways Earned Sep 18, 2025 EDT
The Basics of Google Cloud Compute Earned Sep 18, 2025 EDT
Google Developer Essentials Earned Sep 16, 2025 EDT
Get Started with Sensitive Data Protection Earned Sep 16, 2025 EDT
Boost Productivity with Gemini in BigQuery Earned Sep 15, 2025 EDT
Prompt Design in Vertex AI Earned Sep 6, 2025 EDT
Gemini for end-to-end SDLC Earned May 7, 2025 EDT
Create Image Captioning Models Earned May 7, 2025 EDT
Google Cloud: Prompt Engineering Guide Earned May 4, 2025 EDT
Introduction to Cloud Next Generation Firewall Earned May 4, 2025 EDT
Introduction to Google Workspace with Gemini Earned May 4, 2025 EDT
Introduction to Image Generation Earned May 4, 2025 EDT
Streamline App Development with Gemini Code Assist Earned May 4, 2025 EDT
Build Generative AI Agents with Vertex AI and Flutter Earned May 3, 2025 EDT
Create Generative AI Apps on Google Cloud Earned May 3, 2025 EDT
Machine Learning Operations (MLOps) for Generative AI Earned Apr 30, 2025 EDT
Gemini for Cloud Architects Earned Apr 30, 2025 EDT
Introduction to Responsible AI Earned Apr 30, 2025 EDT
Gemini for Application Developers Earned Apr 30, 2025 EDT
Introduction to Large Language Models Earned Apr 30, 2025 EDT
Introduction to Generative AI Earned Apr 30, 2025 EDT
Google Cloud Big Data and Machine Learning Fundamentals Earned May 23, 2024 EDT
Production Machine Learning Systems Earned May 23, 2024 EDT
Generative AI Explorer - Vertex AI Earned May 23, 2024 EDT
Build LookML Objects in Looker Earned May 23, 2024 EDT
Mitigating Security Vulnerabilities on Google Cloud Earned May 23, 2024 EDT
Perform Predictive Data Analysis in BigQuery Earned May 23, 2024 EDT
Analyze Sentiment with Natural Language API Earned May 23, 2024 EDT
Analyze Speech and Language with Google APIs Earned May 23, 2024 EDT
Analyze Images with the Cloud Vision API Earned May 23, 2024 EDT
Gemini for Data Scientists and Analysts Earned May 23, 2024 EDT
Baseline: Infrastructure Earned May 23, 2024 EDT
Build Infrastructure with Terraform on Google Cloud Earned May 23, 2024 EDT
Monitor and Manage Google Cloud Resources Earned May 21, 2024 EDT
Set Up an App Dev Environment on Google Cloud Earned May 21, 2024 EDT
DEPRECATED Detect Manufacturing Defects Using Visual Inspection AI Earned May 21, 2024 EDT
Develop Serverless Apps with Firebase Earned Apr 26, 2024 EDT
Integrating Applications with Gemini 1.0 Pro on Google Cloud Earned Apr 26, 2024 EDT
Deploy Kubernetes Applications on Google Cloud Earned Jul 23, 2023 EDT
NCAA® March Madness®: Bracketology with Google Cloud Earned Jul 22, 2023 EDT
Implement DevOps Workflows in Google Cloud Earned Jul 21, 2023 EDT
Set Up an App Dev Environment on Google Cloud Earned Jul 21, 2023 EDT
Develop Serverless Apps with Firebase Earned Jul 19, 2023 EDT
Build a Website on Google Cloud Earned Jul 19, 2023 EDT
Build Infrastructure with Terraform on Google Cloud Earned Jun 25, 2022 EDT
Automate Interactions with Contact Center AI Earned Jun 25, 2022 EDT
Google Cloud Solutions I: Scaling Your Infrastructure Earned Jun 25, 2022 EDT
Managing Cloud Infrastructure with Terraform Earned Jun 25, 2022 EDT
Security & Identity Fundamentals Earned Jun 24, 2022 EDT
Develop Serverless Applications on Cloud Run Earned Jun 22, 2022 EDT
Intermediate ML: TensorFlow on Google Cloud Earned Oct 31, 2021 EDT
Intro to ML: Image Processing Earned Oct 31, 2021 EDT
Intro to ML: Language Processing Earned Oct 30, 2021 EDT
DEPRECATED BigQuery for Data Warehousing Earned Oct 30, 2021 EDT
Data Science on Google Cloud Earned Oct 29, 2021 EDT
Derive Insights from BigQuery Data Earned Oct 28, 2021 EDT

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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This on-demand course provides partners the skills required to design, deploy, and monitor Vertail AI Search for Commerce solutions including retail search and recommendation AI for enterprise customers.

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

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Earn the Introductory skill badge by completing the Cloud Speech API: 3 Ways 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 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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This introductory-level quest shows application developers how the Google Cloud ecosystem could help them build secure, scalable, and intelligent cloud native applications. You learn how to develop and scale applications without setting up infrastructure, run data analytics, gain insights from data, and develop with pre-trained ML APIs to leverage machine learning even if you are not a Machine Learning expert. You will also experience seamless integration between various Google services and APIs to create intelligent apps.

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Complete the introductory Get Started with Sensitive Data Protection 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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This course explores Gemini in BigQuery, a suite of AI-driven features to assist data-to-AI workflow. These features include data exploration and preparation, code generation and troubleshooting, and workflow discovery and visualization. Through conceptual explanations, a practical use case, and hands-on labs, the course empowers data practitioners to boost their productivity and expedite the development pipeline.

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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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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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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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Google Cloud : Prompt Engineering Guide examines generative AI tools, how they work. We'll explore how to combine Google Cloud knowledge with prompt engineering to improve Gemini responses.

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This training course introduces Cloud NGFW. Topics include how Cloud NGFW provides centralized firewall management, centralized firewall visibility, advanced threat protection, and firewall insights.

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Google Workspace with Gemini provides customers with generative AI features in Google Workspace. In this learning path, you learn about the key features of Gemini and how they can be used to improve productivity and efficiency in Google Workspace.

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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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Designed for developers of all levels, this course introduces you to the core features and functionalities of Gemini Code Assist, an AI-powered app development collaborator for Google Cloud. From intelligent code suggestions and auto-completion to real-time error detection and refactoring assistance, you'll discover how Gemini Code Assist can significantly enhance your productivity and code quality, and save valuable time to focus on more productive and enjoyable tasks.

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In this course, you learn how to develop an app using Flutter, Google's portable UI toolkit, and integrate the app with Gemini, Google's family of generative AI models. You also use Vertex AI Agent Builder, Google's platform for building and managing AI Agents and applications.

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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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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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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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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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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 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.

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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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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 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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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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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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In this self-paced training course, participants learn mitigations for attacks at many points in a Google Cloud-based infrastructure, including Distributed Denial-of-Service attacks, phishing attacks, and threats involving content classification and use. They also learn about the Security Command Center, cloud logging and audit logging, and using Forseti to view overall compliance with your organization's security policies.

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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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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 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 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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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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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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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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Earn a skill badge by completing the Set Up an App Dev Environment on Google Cloud skill badge course, where you learn how to build and connect storage-centric cloud infrastructure using the basic capabilities of the following technologies: Cloud Storage, Identity and Access Management, Cloud Functions, and Pub/Sub.

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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 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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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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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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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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Complete the intermediate Implement DevOps Workflows in Google Cloud skill badge to demonstrate skills in the following: creating git repositories with Cloud Source 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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Earn a skill badge by completing the Set Up an App Dev Environment on Google Cloud skill badge course, where you learn how to build and connect storage-centric cloud infrastructure using the basic capabilities of the following technologies: Cloud Storage, Identity and Access Management, Cloud Functions, and Pub/Sub.

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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 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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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 a skill badge by completing the Automate Interactions with Contact Center AI quest, where you will learn about the features of Contact Center AI, including how to Build a virtual agent, Design conversation flows for your virtual agent; Add a phone gateway to your virtual agent; Use Dialogflow for troubleshooting; Review logs and debug your virtual agent. 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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In this course you will learn how you to harness serious Google Cloud power and infrastructure. The hands-on labs will give you use cases and you will be tasked with implementing scaling practices utilized by Google’s very own Solutions Architecture team. From developing enterprise grade load balancing and autoscaling, to building continuous delivery pipelines, Google Cloud Solutions I: Scaling your Infrastructure will teach you best practices for taking your Google Cloud projects to the next level.

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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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Security is an uncompromising feature of Google Cloud services, and Google Cloud has developed specific tools for ensuring safety and identity across your projects. In this fundamental-level quest, you will get hands-on practice with Google Cloud’s Identity and Access Management (IAM) service, which is the go-to for managing user and virtual machine accounts. You will get experience with network security by provisioning VPCs and VPNs, and learn what tools are available for security threat and data loss protections.

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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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TensorFlow is an open source software library for high performance numerical computation that's great for writing models that can train and run on platforms ranging from your laptop to a fleet of servers in the Cloud to an edge device. This quest takes you beyond the basics of using predefined models and teaches you how to build, train and deploy your own on Google Cloud.

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Using large scale computing power to recognize patterns and "read" images is one of the foundational technologies in AI, from self-driving cars to facial recognition. The Google Cloud Platform provides world class speed and accuracy via systems that can utilized by simply calling APIs. With these and a host of other APIs, GCP has a tool for just about any machine learning job. In this introductory quest, you will get hands-on practice with machine learning as it applies to image processing by taking labs that will enable you to label images, detect faces and landmarks, as well as extract, analyze, and translate text from within images.

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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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Looking to build or optimize your data warehouse? Learn best practices to Extract, Transform, and Load your data into Google Cloud with BigQuery. In this series of interactive labs you will create and optimize your own data warehouse using a variety of large-scale BigQuery public datasets. BigQuery is Google's fully managed, NoOps, low cost analytics database. With BigQuery you can query terabytes and terabytes of data without having any infrastructure to manage or needing a database administrator. BigQuery uses SQL and can take advantage of the pay-as-you-go model. BigQuery allows you to focus on analyzing data to find meaningful insights. Looking for a hands on challenge lab to demonstrate your skills and validate your knowledge? On completing this quest, 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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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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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 Looker Studio by connecting to BigQuery data.

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