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Charan Raj B H
Member since 2023
Gold League
14310 points
Responsible AI: Applying AI Principles with Google Cloud
Earned мая 2, 2024 EDT
[DEPRECATED]Introduction to Responsible AI
Earned мая 1, 2024 EDT
Introduction to Large Language Models
Earned апр. 29, 2024 EDT
Introduction to Generative AI
Earned апр. 29, 2024 EDT
Derive Insights from BigQuery Data
Earned авг. 29, 2023 EDT
Level 3: GenAI
Earned авг. 29, 2023 EDT
Analyze Images with the Cloud Vision API
Earned авг. 29, 2023 EDT
Qwiklabs Trivia August 2023
Earned авг. 29, 2023 EDT
Integrate BigQuery Data and Google Workspace using Apps Script
Earned авг. 25, 2023 EDT
Level 2: Apps Script and Networks
Earned авг. 22, 2023 EDT
Build a Secure Google Cloud Network
Earned авг. 17, 2023 EDT
Engineer Data for Predictive Modeling with BigQuery ML
Earned авг. 15, 2023 EDT
Cloud Architecture: Design, Implement, and Manage
Earned авг. 14, 2023 EDT
Level 1: BigQuery ML, Cloud Architecture and Devops Skills
Earned авг. 13, 2023 EDT
Implement DevOps Workflows in Google Cloud
Earned авг. 13, 2023 EDT
Develop Serverless Apps with Firebase
Earned авг. 12, 2023 EDT
Create ML Models with BigQuery ML
Earned авг. 10, 2023 EDT
Deploy and Manage Applications on Google App Engine
Earned июля 23, 2023 EDT
[DEPRECATED] Google Cloud Big Data and Machine Learning Fundamentals
Earned июля 17, 2023 EDT
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 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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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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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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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!
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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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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.
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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.
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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.
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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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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.
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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.
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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.
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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.
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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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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 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.
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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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