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Roshan Kumar

Member since 2019

Create Embeddings, Vector Search, and RAG with BigQuery Earned марта 27, 2025 EDT
Google Security Operations - Fundamentals Earned окт. 18, 2024 EDT
Google Security Operations - SOAR Developer Earned авг. 8, 2024 EDT
Google Security Operations - SIEM Rules Earned авг. 1, 2024 EDT
Google Security Operations - SOAR Analyst Earned июля 24, 2024 EDT
Introduction to Responsible AI Earned июня 21, 2024 EDT
Responsible AI: Applying AI Principles with Google Cloud Earned июня 21, 2024 EDT
[DEPRECATED] SOAR Fundamentals Earned июня 21, 2024 EDT
Gemini for Cloud Architects Earned апр. 30, 2024 EDT
Gemini in Google Slides Earned апр. 30, 2024 EDT
Security Practices with Google Security Operations - SIEM Earned апр. 13, 2024 EDT
Gemini for Security Engineers Earned марта 7, 2024 EST
Introduction to Image Generation Earned дек. 13, 2023 EST

This course explores a Retrieval Augmented Generation (RAG) solution in BigQuery to mitigate AI hallucinations. It introduces a RAG workflow that encompasses creating embeddings, searching a vector space, and generating improved answers. The course explains the conceptual reasons behind these steps and their practical implementation with BigQuery. By the end of the course, learners will be able to build a RAG pipeline using BigQuery and generative AI models like Gemini and embedding models to address their own AI hallucination use cases.

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This course covers the baseline skills needed for the Google Security Operations Platform. The modules will cover specific actions and features that security engineers should become familiar with to start using the toolset.

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This course helps developers customize Chronicle and augment its abilities with third party integrations.

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Get hands-on experience applying and building rules for Chronicle. You learn what YARA-L is and how to customize & create event rules.

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This course helps you understand how to use Chronicle to properly handle security incidents.

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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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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 course will familiarize you with the core functionality of Chronicle, including the user interface, connections, and settings.

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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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Google Workspace with Gemini provides customers with generative AI features in Google Workspace. In this mini-course, you learn about the key features of Gemini and how they can be used to improve productivity and efficiency in Google Slides.

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Learn the technical aspects you need to know about Chronicle and how it can help you detect and action threats.

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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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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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