Що більше штучний інтелект і машинне навчання використовуються в корпоративних середовищах, то нагальнішою стає потреба розробити принципи відповідального ставлення до них. Однак говорити про принципи відповідального використання штучного інтелекту легше, ніж застосовувати їх на практиці. Цей курс допоможе вам дізнатись, як запровадити відповідальну роботу зі штучним інтелектом у вашій організації. У цьому курсі ви дізнаєтеся про підхід Google Cloud до відповідального використання ШІ, а також отримаєте практичні поради й набудете досвіду, який допоможе вам розробити власний підхід до цього завдання.
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.
Earn a skill badge by completing the Analyze Sentiment with Natural Language API quest, where you learn how the API derives sentiment from text.
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.
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.
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!
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.
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.
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.
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
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.
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.
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.
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.
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.
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.
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.
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.
This course introduces Vertex AI Studio, a tool to interact with generative AI models, prototype business ideas, and launch them into production. Through an immersive use case, engaging lessons, and a hands-on lab, you’ll explore the prompt-to-product lifecycle and learn how to leverage Vertex AI Studio for Gemini multimodal applications, prompt design, prompt engineering, and model tuning. The aim is to enable you to unlock the potential of gen AI in your projects with Vertex AI Studio.
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
This course introduces you to the Transformer architecture and the Bidirectional Encoder Representations from Transformers (BERT) model. You learn about the main components of the Transformer architecture, such as the self-attention mechanism, and how it is used to build the BERT model. You also learn about the different tasks that BERT can be used for, such as text classification, question answering, and natural language inference.This course is estimated to take approximately 45 minutes to complete.
This course will introduce you to the attention mechanism, a powerful technique that allows neural networks to focus on specific parts of an input sequence. You will learn how attention works, and how it can be used to improve the performance of a variety of machine learning tasks, including machine translation, text summarization, and question answering. This course is estimated to take approximately 45 minutes to complete.
This course gives you a synopsis of the encoder-decoder architecture, which is a powerful and prevalent machine learning architecture for sequence-to-sequence tasks such as machine translation, text summarization, and question answering. You learn about the main components of the encoder-decoder architecture and how to train and serve these models. In the corresponding lab walkthrough, you’ll code in TensorFlow a simple implementation of the encoder-decoder architecture for poetry generation from the beginning.
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 Gemini Enterprise Agent Platform.
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.
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.
Щоб отримати кваліфікаційний значок, пройдіть курси "Introduction to Generative AI", "Introduction to Large Language Models" й "Introduction to Responsible AI". Пройшовши завершальний тест, ви підтвердите, що засвоїли основні поняття, які стосуються генеративного штучного інтелекту. Кваліфікаційний значок – це цифровий значок від платформи Google Cloud, який свідчить, що ви знаєтеся на продуктах і сервісах Google Cloud. Щоб опублікувати кваліфікаційний значок, зробіть свій профіль загальнодоступним, а також додайте значок у профіль у соціальних мережах.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.