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This course focuses on the fundamentals of preparing data for machine learning using Databricks. Participants will learn essential skills for exploring, cleaning, and organizing data tailored for traditional machine learning applications. Key topics include data visualization, feature engineering, and optimal feature storage strategies. Through practical exercises, participants will gain hands-on experience in efficiently preparing data sets for machine learning within the Databricks. This course is designed for associate-level data scientists and machine learning practitioners. and individuals seeking to enhance their proficiency in data preparation, ensuring a solid foundation for successful machine learning model deployment.

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What You'll Learn

  • N/A

Who Should Attend

  • N/A
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Prerequisites

  • Familiarity with Databricks workspace and notebooks
  • Familiarity with Delta Lake and Lakehouse
  • Intermediate-level knowledge of Python

Learning Journey

Coming Soon...

  • Fundamentals of Data Preparation and Feature Engineering
  • Data Imputation
  • Data Encoding
  • Data Standardization
  • Feature Engineering Pipelines
  • Introduction to Feature Store
  • Feature Engineering with Feature Store

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Frequently Asked Questions (FAQs)

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Course Curriculum

Course Curriculum

Training Schedule

Training Schedule

Exam & Certification

Exam & Certification

FAQs

Frequently Asked Questions

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