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	<title>Amazon SageMaker Unified Studio &#8211; Noise</title>
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		<title>Accelerate AI development using Amazon SageMaker AI with serverless MLflow</title>
		<link>https://noise.getoto.net/2025/12/02/accelerate-ai-development-using-amazon-sagemaker-ai-with-serverless-mlflow/</link>
		
		<dc:creator><![CDATA[Donnie Prakoso]]></dc:creator>
		<pubDate>Tue, 02 Dec 2025 16:02:56 +0000</pubDate>
				<category><![CDATA[Amazon Sagemaker]]></category>
		<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[AWS re:Invent]]></category>
		<category><![CDATA[launch]]></category>
		<category><![CDATA[news]]></category>
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					<description><![CDATA[Simplify AI experimentation with zero-infrastructure MLflow that launches in minutes, scales automatically, and seamlessly integrates with SageMaker's model customization and pipeline capabilities.]]></description>
		
		
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		<item>
		<title>Orchestrating data processing tasks with a serverless visual workflow in Amazon SageMaker Unified Studio</title>
		<link>https://noise.getoto.net/2025/11/26/orchestrating-data-processing-tasks-with-a-serverless-visual-workflow-in-amazon-sagemaker-unified-studio/</link>
		
		<dc:creator><![CDATA[Suba Palanisamy]]></dc:creator>
		<pubDate>Tue, 25 Nov 2025 23:08:05 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[In this post, we show how to use the new visual workflow experience in SageMaker Unified Studio IAM-based domains to orchestrate an end-to-end machine learning workflow. The workflow ingests weather data, applies transformations, and generates predictions—all through a single, intuitive interface, without writing any orchestration code.]]></description>
		
		
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		<item>
		<title>New one-click onboarding and notebooks with a built-in AI agent in Amazon SageMaker Unified Studio</title>
		<link>https://noise.getoto.net/2025/11/22/new-one-click-onboarding-and-notebooks-with-a-built-in-ai-agent-in-amazon-sagemaker-unified-studio/</link>
		
		<dc:creator><![CDATA[Channy Yun (윤석찬)]]></dc:creator>
		<pubDate>Sat, 22 Nov 2025 01:23:12 +0000</pubDate>
				<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[launch]]></category>
		<category><![CDATA[news]]></category>
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					<description><![CDATA[Amazon SageMaker Unified Studio introduces new one-click onboarding experiences and serverless notebooks with a built-in AI agent without any manual set up or provisioning of your domain or compute resources. You can launch SageMaker Unified Studio directly from Amazon SageMaker, Amazon Athena, Amazon Redshift, and Amazon S3 Tables console pages, giving a fast path to analytics and AI workloads.]]></description>
		
		
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		<title>Getting started with Amazon S3 Tables in Amazon SageMaker Unified Studio</title>
		<link>https://noise.getoto.net/2025/11/20/getting-started-with-amazon-s3-tables-in-amazon-sagemaker-unified-studio/</link>
		
		<dc:creator><![CDATA[David Pasha]]></dc:creator>
		<pubDate>Wed, 19 Nov 2025 23:26:57 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon S3 Tables]]></category>
		<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[In this post, you learn how to integrate SageMaker Unified Studio with S3 Tables and query your data using Amazon Athena, Amazon Redshift, or Apache Spark in EMR and AWS Glue.]]></description>
		
		
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		<title>New business metadata features in Amazon SageMaker Catalog to improve discoverability across organizations</title>
		<link>https://noise.getoto.net/2025/11/19/new-business-metadata-features-in-amazon-sagemaker-catalog-to-improve-discoverability-across-organizations/</link>
		
		<dc:creator><![CDATA[Channy Yun (윤석찬)]]></dc:creator>
		<pubDate>Wed, 19 Nov 2025 19:09:27 +0000</pubDate>
				<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[launch]]></category>
		<category><![CDATA[news]]></category>
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					<description><![CDATA[Amazon SageMaker Catalog now offers column-level metadata forms and enforced glossary requirements, enabling organizations to improve data classification, discoverability, and governance through standardized business metadata.]]></description>
		
		
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		<item>
		<title>Cross-account lakehouse governance with Amazon S3 Tables and SageMaker Catalog</title>
		<link>https://noise.getoto.net/2025/11/19/cross-account-lakehouse-governance-with-amazon-s3-tables-and-sagemaker-catalog/</link>
		
		<dc:creator><![CDATA[Sneha Rao]]></dc:creator>
		<pubDate>Tue, 18 Nov 2025 23:01:03 +0000</pubDate>
				<category><![CDATA[Amazon S3 Tables]]></category>
		<category><![CDATA[Amazon Sagemaker]]></category>
		<category><![CDATA[Amazon SageMaker Data & AI Governance]]></category>
		<category><![CDATA[Amazon SageMaker Lakehouse]]></category>
		<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[Expert (400)]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[In this post, we walk you through a practical solution for secure, efficient cross-account data sharing and analysis. You’ll learn how to set up cross-account access to S3 Tables using federated catalogs in Amazon SageMaker, perform unified queries across accounts with Amazon Athena in Amazon SageMaker Unified Studio, and implement fine-grained access controls at the column level using AWS Lake Formation.]]></description>
		
		
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		<item>
		<title>Enhanced search with match highlights and explanations in Amazon SageMaker</title>
		<link>https://noise.getoto.net/2025/11/05/enhanced-search-with-match-highlights-and-explanations-in-amazon-sagemaker/</link>
		
		<dc:creator><![CDATA[Ramesh H Singh]]></dc:creator>
		<pubDate>Tue, 04 Nov 2025 22:57:29 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[Amazon SageMaker now enhances search results in Amazon SageMaker Unified Studio with additional context that improves transparency and interpretability. The capability introduces inline highlighting for matched terms and an explanation panel that details where and how each match occurred across metadata fields such as name, description, glossary, and schema. In this post, we demonstrate how to use enhanced search in Amazon SageMaker.]]></description>
		
		
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			</item>
		<item>
		<title>Use trusted identity propagation for Apache Spark interactive sessions in Amazon SageMaker Unified Studio</title>
		<link>https://noise.getoto.net/2025/10/31/use-trusted-identity-propagation-for-apache-spark-interactive-sessions-in-amazon-sagemaker-unified-studio/</link>
		
		<dc:creator><![CDATA[Aarthi Srinivasan]]></dc:creator>
		<pubDate>Fri, 31 Oct 2025 20:55:40 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[In this post, we provide step-by-step instructions to set up Amazon EMR on EC2, EMR Serverless, and AWS Glue within SageMaker Unified Studio, enabled with trusted identity propagation. We use the setup to illustrate how different IAM Identity Center users can run their Spark sessions, using each compute setup, within the same project in SageMaker Unified Studio. We show how each user will see only tables or part of tables that they’re granted access to in Lake Formation.]]></description>
		
		
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			</item>
		<item>
		<title>Federate access to SageMaker Unified Studio with AWS IAM Identity Center and Okta</title>
		<link>https://noise.getoto.net/2025/10/27/federate-access-to-sagemaker-unified-studio-with-aws-iam-identity-center-and-okta/</link>
		
		<dc:creator><![CDATA[Raghavarao Sodabathina]]></dc:creator>
		<pubDate>Mon, 27 Oct 2025 21:11:07 +0000</pubDate>
				<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[AWS IAM Identity Center]]></category>
		<category><![CDATA[Expert (400)]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[This post shows step-by-step guidance to setup workforce access to Amazon SageMaker Unified Studio using Okta as an external Identity provider with AWS IAM Identity Center.]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>Accelerate data governance with custom subscription workflows in Amazon SageMaker</title>
		<link>https://noise.getoto.net/2025/10/24/accelerate-data-governance-with-custom-subscription-workflows-in-amazon-sagemaker/</link>
		
		<dc:creator><![CDATA[Nira Jaiswal]]></dc:creator>
		<pubDate>Fri, 24 Oct 2025 20:41:19 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon SageMaker Data & AI Governance]]></category>
		<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[Technical How-to]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=fc436357edd70bdb9d7ab4bbb4782a85</guid>

					<description><![CDATA[Organizations need to efficiently manage data assets while maintaining governance controls in their data marketplaces. Although manual approval workflows remain important for sensitive datasets and production systems, there’s an increasing need for automated approval processes with less sensitive datasets. In this post, we show you how to automate subscription request approvals within SageMaker, accelerating data access for data consumers.]]></description>
		
		
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			</item>
		<item>
		<title>Automate email notifications for governance teams working with Amazon SageMaker Catalog</title>
		<link>https://noise.getoto.net/2025/10/21/automate-email-notifications-for-governance-teams-working-with-amazon-sagemaker-catalog/</link>
		
		<dc:creator><![CDATA[Himanshu Sahni]]></dc:creator>
		<pubDate>Tue, 21 Oct 2025 20:59:53 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon DataZone]]></category>
		<category><![CDATA[Amazon SageMaker Data & AI Governance]]></category>
		<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[In this post, we show you how to create custom notifications for events occurring in SageMaker Catalog using Amazon EventBridge, AWS Lambda, and Amazon SNS. You can expand this solution to automatically integrate SageMaker Catalog with in-house enterprise workflow tools like ServiceNow and Helix.]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>Configure seamless single sign-on with SQL analytics in Amazon SageMaker Unified Studio</title>
		<link>https://noise.getoto.net/2025/10/18/configure-seamless-single-sign-on-with-sql-analytics-in-amazon-sagemaker-unified-studio/</link>
		
		<dc:creator><![CDATA[Arun A K]]></dc:creator>
		<pubDate>Fri, 17 Oct 2025 23:20:34 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[Technical How-to]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=cd1fb3252c6bc368cba6fba158521dc3</guid>

					<description><![CDATA[This post demonstrates how to configure SageMaker Unified Studio with SSO, set up projects and user onboarding, and access data securely using integrated analytics tools.]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>Visualize data lineage using Amazon SageMaker Catalog for Amazon EMR, AWS Glue, and Amazon Redshift</title>
		<link>https://noise.getoto.net/2025/10/13/visualize-data-lineage-using-amazon-sagemaker-catalog-for-amazon-emr-aws-glue-and-amazon-redshift/</link>
		
		<dc:creator><![CDATA[Shubham Purwar]]></dc:creator>
		<pubDate>Mon, 13 Oct 2025 19:08:49 +0000</pubDate>
				<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[Amazon EMR]]></category>
		<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[Amazon SageMaker Data & AI Governance]]></category>
		<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[AWS Glue]]></category>
		<category><![CDATA[Expert (400)]]></category>
		<category><![CDATA[Technical How-to]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=89e754efcbf447ec16867fdb98ac995b</guid>

					<description><![CDATA[Amazon SageMaker offers a comprehensive hub that integrates data, analytics, and AI capabilities, providing a unified experience for users to access and work with their data. Through Amazon SageMaker Unified Studio, a single and unified environment, you can use a wide range of tools and features to support your data and AI development needs, including […]]]></description>
		
		
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			</item>
		<item>
		<title>Use Apache Airflow workflows to orchestrate data processing on Amazon SageMaker Unified Studio</title>
		<link>https://noise.getoto.net/2025/09/22/use-apache-airflow-workflows-to-orchestrate-data-processing-on-amazon-sagemaker-unified-studio/</link>
		
		<dc:creator><![CDATA[Vinod Jayendra]]></dc:creator>
		<pubDate>Mon, 22 Sep 2025 16:56:56 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon Managed Workflows for Apache Airflow (Amazon MWAA)]]></category>
		<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[Application Integration]]></category>
		<category><![CDATA[Technical How-to]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=bec102efbc4f1b89d06ae17669841592</guid>

					<description><![CDATA[Orchestrating machine learning pipelines is complex, especially when data processing, training, and deployment span multiple services and tools. In this post, we walk through a hands-on, end-to-end example of developing, testing, and running a machine learning (ML) pipeline using workflow capabilities in Amazon SageMaker, accessed through the Amazon SageMaker Unified Studio experience. These workflows are powered by Amazon Managed Workflows for Apache Airflow.]]></description>
		
		
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		<item>
		<title>Tailor Amazon SageMaker Unified Studio project environments to your needs using custom blueprints</title>
		<link>https://noise.getoto.net/2025/09/18/tailor-amazon-sagemaker-unified-studio-project-environments-to-your-needs-using-custom-blueprints/</link>
		
		<dc:creator><![CDATA[Aditya Challa]]></dc:creator>
		<pubDate>Wed, 17 Sep 2025 22:49:58 +0000</pubDate>
				<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[Intermediate (200)]]></category>
		<category><![CDATA[Technical How-to]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=99ca1ac029307d379ba482b708ad7b3d</guid>

					<description><![CDATA[Amazon SageMaker Unified Studio is a single data and AI development environment that brings together data preparation, analytics, machine learning (ML), and generative AI development in one place. By unifying these workflows, it saves teams from managing multiple tools and makes it straightforward for data scientists, analysts, and developers to build, train, and deploy ML […]]]></description>
		
		
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		<title>Amazon SageMaker introduces Amazon S3 based shared storage for enhanced project collaboration</title>
		<link>https://noise.getoto.net/2025/09/16/amazon-sagemaker-introduces-amazon-s3-based-shared-storage-for-enhanced-project-collaboration/</link>
		
		<dc:creator><![CDATA[Hari Ramesh]]></dc:creator>
		<pubDate>Tue, 16 Sep 2025 20:23:44 +0000</pubDate>
				<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[Amazon Simple Storage Service (S3)]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[Intermediate (200)]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[AWS recently announced that Amazon SageMaker now offers Amazon Simple Storage Service (Amazon S3) based shared storage as the default project file storage option for new Amazon SageMaker Unified Studio projects. This feature addresses the deprecation of AWS CodeCommit while providing teams with a straightforward and consistent way to collaborate on project files across the […]]]></description>
		
		
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		<item>
		<title>Accelerate your data and AI workflows by connecting to Amazon SageMaker Unified Studio from Visual Studio Code</title>
		<link>https://noise.getoto.net/2025/09/12/accelerate-your-data-and-ai-workflows-by-connecting-to-amazon-sagemaker-unified-studio-from-visual-studio-code/</link>
		
		<dc:creator><![CDATA[Lauren Mullennex]]></dc:creator>
		<pubDate>Fri, 12 Sep 2025 15:59:57 +0000</pubDate>
				<category><![CDATA[Amazon SageMaker AI]]></category>
		<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[Intermediate (200)]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[In this post, we demonstrate how to connect your local VS Code to SageMaker Unified Studio so you can build complete end-to-end data and AI workflows while working in your preferred development environment.]]></description>
		
		
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		<item>
		<title>Use the Amazon DataZone upgrade domain to Amazon SageMaker and expand to new SQL analytics, data processing, and AI uses cases</title>
		<link>https://noise.getoto.net/2025/09/11/use-the-amazon-datazone-upgrade-domain-to-amazon-sagemaker-and-expand-to-new-sql-analytics-data-processing-and-ai-uses-cases/</link>
		
		<dc:creator><![CDATA[David Victoria]]></dc:creator>
		<pubDate>Thu, 11 Sep 2025 20:37:38 +0000</pubDate>
				<category><![CDATA[Amazon DataZone]]></category>
		<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[Intermediate (200)]]></category>
		<category><![CDATA[Technical How-to]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=900a4050813cfa07d4dc84154023781b</guid>

					<description><![CDATA[Amazon DataZone and Amazon SageMaker announced a new feature that allows an Amazon DataZone domain to be upgraded to the next generation of SageMaker, making the investment customers put into developing Amazon DataZone transferable to SageMaker. All content created and curated through Amazon DataZone such as assets, metadata forms, glossaries, subscriptions, and so on are […]]]></description>
		
		
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		<title>Introducing enhanced AI assistance in Amazon SageMaker Unified Studio: Agentic chat, Amazon Q Developer CLI, and MCP integration</title>
		<link>https://noise.getoto.net/2025/09/09/introducing-enhanced-ai-assistance-in-amazon-sagemaker-unified-studio-agentic-chat-amazon-q-developer-cli-and-mcp-integration/</link>
		
		<dc:creator><![CDATA[Lauren Mullennex]]></dc:creator>
		<pubDate>Mon, 08 Sep 2025 21:32:24 +0000</pubDate>
				<category><![CDATA[Amazon Q Developer]]></category>
		<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[In this post, we will walk through how you can use the improved Amazon Q Developer chat and the new built-in Amazon Q Developer CLI in SageMaker Unified Studio for coding ETL tasks, to fix code errors, and generate ML development workflows. Both interfaces use MCP to read files, run commands, and interact with AWS services directly from the IDE. You can also configure additional MCP servers to extend Amazon Q Developer’s capabilities with custom tools and integrations specific to your workflow.]]></description>
		
		
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		<title>Announcing SageMaker Unified Studio Workshops for Financial Services</title>
		<link>https://noise.getoto.net/2025/09/08/announcing-sagemaker-unified-studio-workshops-for-financial-services/</link>
		
		<dc:creator><![CDATA[Sanjay Ohri]]></dc:creator>
		<pubDate>Mon, 08 Sep 2025 18:31:44 +0000</pubDate>
				<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[Financial Services]]></category>
		<category><![CDATA[Intermediate (200)]]></category>
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					<description><![CDATA[In this post, we’re excited to announce the release of four Amazon SageMaker Unified Studio publicly available workshops that are specific to each FSI segment: insurance, banking, capital markets, and payments. These workshops can help you learn how to deploy Amazon SageMaker Unified Studio effectively for business use cases.]]></description>
		
		
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