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3 Ways to Learn Data Science and Get a Job in 2024

Towards AI

How do you best learn Data Science and then get a Job? What is data science??? All the way back in 2012, Harvard Business Review said that Data Science was the sexiest job of the 21st century and recently followed up with an updated version of their article. Okay, let’s get started!

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Promote pipelines in a multi-environment setup using Amazon SageMaker Model Registry, HashiCorp Terraform, GitHub, and Jenkins CI/CD

AWS Machine Learning Blog

Building out a machine learning operations (MLOps) platform in the rapidly evolving landscape of artificial intelligence (AI) and machine learning (ML) for organizations is essential for seamlessly bridging the gap between data science experimentation and deployment while meeting the requirements around model performance, security, and compliance.

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Use Amazon SageMaker Studio with a custom file system in Amazon EFS

AWS Machine Learning Blog

Amazon SageMaker Studio is the latest web-based experience for running end-to-end machine learning (ML) workflows. This means that each user within the domain will have their own private space on the EFS file system, allowing them to store and access their own data and files. The following diagram illustrates this architecture.

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Four approaches to manage Python packages in Amazon SageMaker Studio notebooks

Flipboard

There are also limited options for ad hoc script customization by users, such as data scientists or ML engineers, due to permissions of the user profile execution role. Check that the SageMaker image selected is a Conda-supported first-party kernel image such as “Data Science.” Choose Open Launcher.

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Use Amazon SageMaker Model Card sharing to improve model governance

AWS Machine Learning Blog

Architecture overview The architecture is implemented as follows: Data Science Account – Data Scientists conduct their experiments in SageMaker Studio and build an MLOps setup to deploy models to staging/production environments using SageMaker Projects. For more information, refer to Configure the AWS CLI.

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Use Amazon SageMaker Model Cards sharing to improve model governance

AWS Machine Learning Blog

Architecture overview The architecture is implemented as follows: Data Science Account – Data Scientists conduct their experiments in SageMaker Studio and build an MLOps setup to deploy models to staging/production environments using SageMaker Projects. For more information, refer to Configure the AWS CLI.

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The 11 Top AI Influencers to Watch in 2024 (Guide)

Viso.ai

Each of these individuals serves as an inspiration for aspiring AI and ML engineers breaking into the field. Cassie Kozyrkov: A Top Voice in Data Science and Analytics Cassie Kozyrkov makes for one of the AI influencers of this decade. We ranked these individuals in reverse chronological order.