Introduction to Data Science Statistical Methods

Course code: CDS84

This course gives an overview of the statistical methods used by data scientists, with an emphasis on the applicability to business problems. No software is shown in the course, and the mathematical details are kept to a minimum.

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Course dates

Starting date: Upon request

Type: Upon request

Course duration: 7 hours

Language: en

Price without VAT: 600 EUR


Type Course
Language Price without VAT
Upon request Upon request 7 hours en 600 EUR Register
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Target group

Business analysts who want an overview of the types of methods used in data science

Course structure

Introduction to Data Science

  • Introduction to data science.
  • Analytical life cycle.

Preparing the Data for Modeling

  • Analytical challenges to predictive modeling.
  • Feature engineering.

Supervised Models

  • Introduction to supervised machine learning models.
  • Regression.
  • Decision trees.
  • Neural networks.
  • Support vector machines.
  • Factorization machines.
  • Ensemble models.
  • Two-stage models.

Unsupervised Models

  • Introduction to unsupervised models.
  • Hierarchical clustering.
  • K-means clustering.
  • Self-organizing maps.
  • Market basket analysis.
  • Path analysis.
  • Network analysis.
  • Text analytics.

Model Assessment

  • Introduction to model assessment.


Before attending this course, you should have some exposure to model building and quantitative analyses.

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