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Delivering Data-Driven Decisions with AWS: Applying Machine Learning, Data Engineering, and Generative AI

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AWS skills are in high demand as startups, consulting firms, and enterprises modernize their applications and transform data. Data analytics cannot scale without the help of cloud computing. In this course, instructor Wendy Wong teaches AWS skills with practical applications of machine learning, data engineering, and generative AI to help you make faster decisions for your organization and customers. This course guides you through the process of learning AWS skills with practical scenarios that complement agile projects and upskill in a no-code or low-code environment to deliver customer solutions that can be solved through machine learning, AI, data engineering, and data analytics at scale with cloud computing.


01 - Introduction
  • 01 - Deliver data-driven decisions with AWS

  • 02 - 1. Getting Started in Generative AI with Amazon CodeWhisperer
  • 01 - Overview of generative AI
  • 02 - Introduction to Amazon CodeWhisperer
  • 03 - Installing Amazon CodeWhisperer
  • 04 - Navigating Amazon CodeWhisperer for EDA and PCA

  • 03 - 2. Getting Started with Amazon Redshift Serverless
  • 01 - Overview of lakehouse architecture
  • 02 - Introduction to Amazon Redshift Serverless
  • 03 - Exploring common use cases
  • 04 - Navigating to Amazon Redshift Serverless

  • 04 - 3. No Code ETL on AWS Glue and AWS Glue Studio
  • 01 - Understanding AWS Glue and AWS Glue Studio
  • 02 - Transforming data with AWS Glue Studio and generative AI

  • 05 - 4. Making Predictions with Amazon SageMaker Canvas for No Code ML
  • 01 - Introduction to machine learning in the real world
  • 02 - Introduction to Amazon SageMaker Canvas
  • 03 - Linear regression with Jupyter Notebook
  • 04 - Linear regression with Amazon SageMaker Canvas

  • 06 - Conclusion
  • 01 - Learning more about AWS data services
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    تاریخ انتشار: 10 مرداد 1403
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