Fu Mr.
Member since 2024
Silver League
20275 points
DEPRECATED Detect Manufacturing Defects Using Visual Inspection AI
Earned מאי 23, 2024 EDT
Analyze Sentiment with Natural Language API
Earned מאי 23, 2024 EDT
Smart Analytics, Machine Learning, and AI on Google Cloud
Earned מאי 23, 2024 EDT
[DEPRECATED] Google Cloud Big Data and Machine Learning Fundamentals
Earned מאי 22, 2024 EDT
Introduction to AI and Machine Learning on Google Cloud
Earned מאי 22, 2024 EDT
Baseline: Infrastructure
Earned מאי 22, 2024 EDT
Generative AI Explorer - Agent Platform
Earned מאי 22, 2024 EDT
[Deprecated] Classify Images with TensorFlow on Google Cloud
Earned מאי 22, 2024 EDT
Build LookML Objects in Looker
Earned מאי 22, 2024 EDT
Analyze Images with the Cloud Vision API
Earned מאי 22, 2024 EDT
Analyze Speech and Language with Google APIs
Earned מאי 22, 2024 EDT
Create ML Models with BigQuery ML
Earned מאי 21, 2024 EDT
Perform Predictive Data Analysis in BigQuery
Earned מאי 21, 2024 EDT
Integrate Applications with Gemini on Google Cloud
Earned אפר 25, 2024 EDT
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 Analyze Sentiment with Natural Language API quest, where you learn how the API derives sentiment from text.
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Incorporating machine learning into data pipelines increases the ability to extract insights from data. This course covers ways machine learning can be included in data pipelines on Google Cloud. For little to no customization, this course covers AutoML. For more tailored machine learning capabilities, this course introduces Notebooks and BigQuery machine learning (BigQuery ML). Also, this course covers how to productionalize machine learning solutions by using Vertex AI.
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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 introduces Google Cloud's AI and machine learning (ML) capabilities, with a focus on developing both generative and predictive AI projects. It explores the various technologies, products, and tools available throughout the data-to-AI lifecycle, empowering data scientists, AI developers, and ML engineers to enhance their expertise through interactive exercises.
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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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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.
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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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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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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 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 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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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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This short course on integrating applications with Gemini on Google Cloud helps you discover the Gemini API and its generative AI models. The course teaches you how to access the Gemini 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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