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9 Careers You Could Go into With a Data Science Degree

Smart Data Collective

You would need to have the skills to analyze large amounts of complex data and find patterns that would benefit the business or organization you work for. Data Engineer. In this role, you would perform batch processing or real-time processing on data that has been collected and stored. Applications Architect.

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Real value, real time: Production AI with Amazon SageMaker and Tecton

AWS Machine Learning Blog

The following graphic shows how Amazon Bedrock is incorporated to support generative AI capabilities in the fraud detection system architecture.

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Build an Amazon SageMaker Model Registry approval and promotion workflow with human intervention

AWS Machine Learning Blog

Specialist Data Engineering at Merck, and Prabakaran Mathaiyan, Sr. ML Engineer at Tiger Analytics. He has extensive experience in enterprise systems architecture and operations across several industries – particularly in Health Care and Life Science. This post is co-written with Jayadeep Pabbisetty, Sr.

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Accelerate machine learning time to value with Amazon SageMaker JumpStart and PwC’s MLOps accelerator

AWS Machine Learning Blog

With a comprehensive suite of technical artifacts, including infrastructure as code (IaC) scripts, data processing workflows, service integration code, and pipeline configuration templates, PwC’s MLOps accelerator simplifies the process of developing and operating production-class prediction systems.

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Data Intelligence empowers informed decisions

Pickl AI

Data Engineer Builds and manages the infrastructure for collecting, storing, and analysing large volumes of data. Java, Scala), data warehousing Build a strong foundation in databases, gain programming skills, and engage in hands-on projects and internships. . . ₹ 10,00000 Deep learning, programming (e.g.,

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Innovating at speed: BMW’s generative AI solution for cloud incident analysis

AWS Machine Learning Blog

It requires checking many systems and teams, many of which might be failing, because theyre interdependent. Developers need to reason about the system architecture, form hypotheses, and follow the chain of components until they have located the one that is the culprit.

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