Feature Engineering for Data Science

Feature Engineering for Data Science (2 days)

This course provides a unique and comprehensive approach for the process of feature engineering for advanced analytics algorithms. The course tackles the whole data preparation process, from data acquisition, data cleansing, data transformation, and feature engineering. You will learn the essentials to model analytical data marts and design elastic processes for both model training and model prediction processes.

Course Outline

  • Introduction to Feature Engineering
  • Data Origin, Data Models & Analytical Data Marts
  • Data Acquisition and Data Integration
  • Data Transformations
  • Binning and Dimensional Reduction
  • Missing Value Treatment
  • Outlier Treatment
  • Data Sampling and Partitioning
  • One-row-per-subject Features
  • Data Preparation Essentials for Predictive Modeling

Who should attend

Data Scientists, statisticians, business analysts, market researchers, and information technology professionals who need to get started with data-driven analytics and want to make better use of their data.

Did not find the training you are looking for? Please feel free to ask for any other Advanced Analytics training.

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