Gemini for end-to-end SDLC
Earned sept. 6, 2024 EDT
Gemini for DevOps Engineers
Earned sept. 6, 2024 EDT
Gemini for Security Engineers
Earned sept. 5, 2024 EDT
Gemini for Network Engineers
Earned sept. 5, 2024 EDT
Gemini for Data Scientists and Analysts
Earned sept. 5, 2024 EDT
Gemini for Cloud Architects
Earned sept. 3, 2024 EDT
Responsible AI: Applying AI Principles with Google Cloud
Earned sept. 2, 2024 EDT
Introduction to Responsible AI
Earned sept. 2, 2024 EDT
Introduction to Generative AI
Earned sept. 2, 2024 EDT
Gemini for Application Developers
Earned sept. 2, 2024 EDT
Derive Insights from BigQuery Data
Earned juil. 6, 2024 EDT
Building No-Code Apps with AppSheet: Foundations
Earned juil. 6, 2024 EDT
Analyzing and Visualizing Data in Looker
Earned juil. 6, 2024 EDT
Introduction to Large Language Models
Earned juin 21, 2024 EDT
DEPRECATED Language, Speech, Text, & Translation with Google Cloud APIs
Earned juin 17, 2024 EDT
Introduction to Data Analytics on Google Cloud
Earned juin 15, 2024 EDT
Build a Secure Google Cloud Network
Earned juin 6, 2024 EDT
Set Up an App Dev Environment on Google Cloud
Earned mai 16, 2024 EDT
Implementing Cloud Load Balancing for Compute Engine
Earned mai 11, 2024 EDT
This is the first of five courses in the Google Cloud Data Analytics Certificate. In this course, you’ll define the field of cloud data analysis and describe roles and responsibilities of a cloud data analyst as they relate to data acquisition, storage, processing, and visualization. You’ll explore the architecture of Google Cloud-based tools, like BigQuery and Cloud Storage, and how they are used to effectively structure, present, and report data.
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This course introduces important topics of AI privacy and safety. It explores practical methods and tools to implement AI privacy and safety recommended practices through the use of Google Cloud products and open-source tools.
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Explore AI-powered search technologies, tools, and applications in this course. Learn semantic search utilizing vector embeddings, hybrid search combining semantic and keyword approaches, and retrieval-augmented generation (RAG) minimizing AI hallucinations as a grounded AI agent. Gain practical experience with Vertex AI Vector Search to build your intelligent search engine.
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This course introduces concepts of AI interpretability and transparency. It discusses the importance of AI transparency for developers and engineers. It explores practical methods and tools to help achieve interpretability and transparency in both data and AI models.
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This course introduces concepts of responsible AI and AI principles. It covers techniques to practically identify fairness and bias and mitigate bias in AI/ML practices. It explores practical methods and tools to implement Responsible AI best practices using Google Cloud products and open source tools.
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Complete the intermediate Inspect Rich Documents with Gemini Multimodality and Multimodal RAG skill badge to demonstrate skills in the following: using multimodal prompts to extract information from text and visual data, generating a video description, and retrieving extra information beyond the video using multimodality with Gemini; building metadata of documents containing text and images, getting all relevant text chunks, and printing citations by using Multimodal Retrieval Augmented Generation (RAG) with Gemini. 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 course and the final assessment challenge lab to receive a skill badge that you can share with your network.
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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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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.
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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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Complete the intermediate Develop Gen AI Apps with Gemini and Streamlit skill badge course to demonstrate skills in text generation, applying function calls with the Python SDK and Gemini API, and deploying a Streamlit application with Cloud Run. In this course, you learn Gemini prompting, test Streamlit apps in Cloud Shell, and deploy them as Docker containers in Cloud Run.
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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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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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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.
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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.
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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.
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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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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps engineers manage infrastructure. You learn how to prompt Gemini to find and understand application logs, create a GKE cluster, and investigate how to create a build environment. Using a hands-on lab, you experience how Gemini improves the DevOps workflow.
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 network engineers create, update, and maintain VPC networks. You learn how to prompt Gemini to provide specific guidance for your networking tasks, beyond what you would receive from a search engine. Using a hands-on lab, you experience how Gemini makes it easier for you to work with Google Cloud VPC networks.
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 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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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 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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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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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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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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In this course you will learn the fundamentals of no-code app development and recognize use cases for no-code apps. The course provides an overview of the AppSheet no-code app development platform and its capabilities. You learn how to create an app with data from spreadsheets, create the app’s user experience using AppSheet views and publish the app to end users.
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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 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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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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In this beginner-level course, you will learn about the Data Analytics workflow on Google Cloud and the tools you can use to explore, analyze, and visualize data and share your findings with stakeholders. Using a case study along with hands-on labs, lectures, and quizzes/demos, the course will demonstrate how to go from raw datasets to clean data to impactful visualizations and dashboards. Whether you already work with data and want to learn how to be successful on Google Cloud, or you’re looking to progress in your career, this course will help you get started. Almost anyone who performs or uses data analysis in their work can benefit from this course.
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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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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 introductory Implementing Cloud Load Balancing for Compute Engine skill badge to demonstrate skills in the following: creating and deploying virtual machines in Compute Engine and configuring network and application load balancers.
Introduction to Data Analytics in Google Cloud
Earned nov. 20, 2024 EST
Responsible AI for Developers: Privacy & Safety
Earned sept. 12, 2024 EDT
Vector Search and Embeddings
Earned sept. 12, 2024 EDT
Responsible AI for Developers: Interpretability & Transparency
Earned sept. 11, 2024 EDT
Responsible AI for Developers: Fairness & Bias
Earned sept. 11, 2024 EDT
Inspect Rich Documents with Gemini Multimodality and Multimodal RAG
Earned sept. 11, 2024 EDT
Machine Learning Operations (MLOps) for Generative AI
Earned sept. 10, 2024 EDT
Introduction to Vertex AI Studio
Earned sept. 10, 2024 EDT
Prompt Design in Vertex AI
Earned sept. 10, 2024 EDT
Develop Gen AI Apps with Gemini and Streamlit
Earned sept. 9, 2024 EDT
Create Image Captioning Models
Earned sept. 9, 2024 EDT
Introduction to Image Generation
Earned sept. 9, 2024 EDT
Transformer Models and BERT Model
Earned sept. 9, 2024 EDT
Encoder-Decoder Architecture
Earned sept. 9, 2024 EDT
Attention Mechanism
Earned sept. 6, 2024 EDT
Gemini for end-to-end SDLC
Earned sept. 6, 2024 EDT
Gemini for DevOps Engineers
Earned sept. 6, 2024 EDT
Gemini for Security Engineers
Earned sept. 5, 2024 EDT
Gemini for Network Engineers
Earned sept. 5, 2024 EDT
Gemini for Data Scientists and Analysts
Earned sept. 5, 2024 EDT
Gemini for Cloud Architects
Earned sept. 3, 2024 EDT
Responsible AI: Applying AI Principles with Google Cloud
Earned sept. 2, 2024 EDT
Introduction to Responsible AI
Earned sept. 2, 2024 EDT
Introduction to Generative AI
Earned sept. 2, 2024 EDT
Gemini for Application Developers
Earned sept. 2, 2024 EDT
Derive Insights from BigQuery Data
Earned juil. 6, 2024 EDT
Building No-Code Apps with AppSheet: Foundations
Earned juil. 6, 2024 EDT
Analyzing and Visualizing Data in Looker
Earned juil. 6, 2024 EDT
Introduction to Large Language Models
Earned juin 21, 2024 EDT
DEPRECATED Language, Speech, Text, & Translation with Google Cloud APIs
Earned juin 17, 2024 EDT
Introduction to Data Analytics on Google Cloud
Earned juin 15, 2024 EDT
Build a Secure Google Cloud Network
Earned juin 6, 2024 EDT
Set Up an App Dev Environment on Google Cloud
Earned mai 16, 2024 EDT
Implementing Cloud Load Balancing for Compute Engine
Earned mai 11, 2024 EDT