DHILIPKUMAR SIVAKUMAR
Member since 2025
Silver League
2957 points
Arcade Voyage: Google Sheets
Earned авг. 14, 2026 EDT
Arcade Trail: Cloud Delivery Systems
Earned авг. 14, 2026 EDT
Arcade Base Camp August 2026
Earned авг. 13, 2026 EDT
Arcade Adventure: Data Vault
Earned авг. 13, 2026 EDT
Arcade Base Camp July 2026
Earned июля 19, 2026 EDT
Arcade Trail: Google Workspace Administration
Earned июля 8, 2026 EDT
Introduction to Vertex AI Studio
Earned июля 7, 2026 EDT
Create Image Captioning Models
Earned июля 5, 2026 EDT
Transformer Models and BERT Model
Earned июля 2, 2026 EDT
Encoder-Decoder Architecture
Earned июля 2, 2026 EDT
Attention Mechanism
Earned июля 1, 2026 EDT
Introduction to Image Generation
Earned июля 1, 2026 EDT
Responsible AI: Applying AI Principles with Google Cloud
Earned окт. 21, 2025 EDT
Prompt Design in Agent Platform
Earned окт. 21, 2025 EDT
[DEPRECATED]Introduction to Responsible AI
Earned окт. 8, 2025 EDT
Introduction to Large Language Models
Earned окт. 7, 2025 EDT
Introduction to Generative AI
Earned окт. 7, 2025 EDT
Transforming raw spreadsheet data into structured business intelligence requires precise validation, efficient navigation, and dynamic visual reporting. This voyage path builds core analytical competencies using Google Sheets. You will begin by implementing strict data validation rules, configuring targeted search workflows, and ensuring data integrity across large datasets. You will then advance to building dynamic charts and executing complex analytical formulas to extract meaningful insights. Finalized with a comprehensive challenge lab, this voyage prepares you to build reliable, presentation-ready analytical workbooks.
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Accelerating software delivery while maintaining stability demands automated build, artifact, and release pipelines. This trail covers the core practices for implementing continuous integration and continuous delivery (CI/CD) on Google Cloud. You will begin by managing container images with Artifact Registry and building automated pipelines for Google Kubernetes Engine using Cloud Build. Next, you will configure continuous delivery workflows with Google Cloud Deploy to safely promote releases across environments. Concluding with a practical challenge lab, this trail prepares you to establish resilient, production-ready deployment pipelines.
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Welcome to Base Camp, where you’ll develop key Google Cloud skills (available in Spanish and Portuguese too!) and earn an exclusive credential that will open doors to the cloud for you. No prior experience is required!
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Who says sharing complex data across boundaries has to be a compliance nightmare? This adventure is your blueprint for delivering modern Analytics-as-a-Service on Google Data Cloud. You'll start by building secure, authorized views on BigQuery to safely expose data to partners without exposing underlying tables. Next, you'll learn to consume customer-specific datasets and streamline cross-organization data delivery. Packed with a hands-on challenge lab, this adventure gives you the practical skills to publish, share, and scale data seamlessly while keeping security tight.
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Welcome to Base Camp, where you’ll develop key Google Cloud skills (available in Spanish and Portuguese too!) and earn an exclusive credential that will open doors to the cloud for you. No prior experience is required!
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Managing an organization’s digital ecosystem isn't just about keeping the lights on—it's about building a secure launchpad for collaboration. In this trail, you'll step into the Google Workspace Admin Console to control user provisioning and application security from the ground up. Then, you'll switch gears to digital education, transforming standard environments into secure virtual classrooms using Google Meet and Google Classroom. Backed by a challenge lab, this trail is your fast track to running enterprise-grade cloud workspaces.
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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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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 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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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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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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Complete the introductory Prompt Design in Agent Platform skill badge to demonstrate skills in the following: prompt engineering, image analysis, and multimodal generative techniques, within Agent Platform. Discover how to craft effective prompts, guide generative AI output, and apply Gemini models to real-world marketing scenarios. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.
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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 Enterprise 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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