Dmytro Kostenko
Date d'abonnement : 2024
Ligue d'Argent
32080 points
Introduction to Vertex AI Studio
Earned mars 19, 2024 EDT
Transformer Models and BERT Model
Earned mars 19, 2024 EDT
Introduction to Image Generation
Earned mars 19, 2024 EDT
[DEPRECATED]Introduction to Responsible AI
Earned mars 19, 2024 EDT
Encoder-Decoder Architecture
Earned mars 19, 2024 EDT
Create Image Captioning Models
Earned mars 19, 2024 EDT
Attention Mechanism
Earned mars 19, 2024 EDT
The Arcade Trivia March 2024 Week 1
Earned mars 17, 2024 EDT
Analyze Sentiment with Natural Language API
Earned mars 14, 2024 EDT
Implement Speech and Language Solutions with Pre-trained APIs
Earned mars 14, 2024 EDT
[Deprecated] Get Started with Looker
Earned mars 14, 2024 EDT
Analyze Speech and Language with Google APIs
Earned mars 12, 2024 EDT
Automate Data Capture at Scale with Document AI
Earned mars 12, 2024 EDT
DEPRECATED Detect Manufacturing Defects Using Visual Inspection AI
Earned mars 11, 2024 EDT
Share Data Using Google Data Cloud
Earned mars 10, 2024 EDT
Build a Data Warehouse with BigQuery
Earned mars 8, 2024 EST
Derive Insights from BigQuery Data
Earned mars 7, 2024 EST
Perform Predictive Data Analysis in BigQuery
Earned mars 7, 2024 EST
Create ML Models with BigQuery ML
Earned mars 5, 2024 EST
[Deprecated] Classify Images with TensorFlow on Google Cloud
Earned mars 2, 2024 EST
Responsible AI: Applying AI Principles with Google Cloud
Earned mars 2, 2024 EST
Generative AI Fundamentals
Earned mars 2, 2024 EST
Introduction to Generative AI
Earned fév. 25, 2024 EST
Google Cloud Fundamentals: Core Infrastructure
Earned fév. 25, 2024 EST
Introduction to Large Language Models
Earned fév. 16, 2024 EST
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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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 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.
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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 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 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 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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Hey there! You're invited to game on with the Arcade Trivia for March Week 1! Play throughout the month and boost your cloud learning journey. Every week, we'll release a new set of questions to test your knowledge of Google Cloud Platform. Get started now and earn the March Trivia Week 1 badge!
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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 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 Get Started with Looker skill badge course, where you learn how to analyze, visualize, and curate data using Looker Studio and Looker.
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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 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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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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Earn a skill badge by completing the Share Data Using Google Data Cloud skill badge course, where you will gain practical experience with Google Cloud Data Sharing Partners, which have proprietary datasets that customers can use for their analytics use cases. Customers subscribe to this data, query it within their own platform, then augment it with their own datasets and use their visualization tools for their customer facing dashboards.
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Complete the intermediate Build a Data Warehouse with BigQuery skill badge course to demonstrate skills in the following: joining data to create new tables, troubleshooting joins, appending data with unions, creating date-partitioned tables, and working with JSON, arrays, and structs in BigQuery.
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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 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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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 the intermediate Skill Badge by completing the Classify Images with TensorFlow on Google Cloud skill badge course where you learn how to use TensorFlow and Vertex AI to create and train machine learning models. You primarily interact with Vertex AI Workbench user-managed notebooks.
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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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Earn a skill badge by completing the Introduction to Generative AI, Introduction to Large Language Models and Introduction to Responsible AI courses. By passing the final quiz, you'll demonstrate your understanding of foundational concepts in generative AI.
A skill badge is a digital badge issued by Google Cloud in recognition of your knowledge of Google Cloud products and services. Share your skill badge by making your profile public and adding it to your social media profile.
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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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Google Cloud Fundamentals: Core Infrastructure 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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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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