Practical Statistics for Data Scientists

In this training you’ll learn:

  • Exploratory Data analysis in order to achieve Data quality which involves completeness, consistency of format, cleanliness and accuracy of individual data points.
  • Random sampling in order to reduce bias and yield a higher quality and representative dataset, even with big data
  • The principles of experimental design that yield definitive answers to questions
  • How to use regression to estimate outcomes and detect anomalies
  • Key classification techniques for predicting which categories a record belongs to
  • Statiscal machine learning methods that learn from data
  • Unsupervised learning methods for extracting meaning from unlabel data

Here you can consult the other trainings we offer.

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