Course Outline

The session is hands-on and will take the audience from the very basic steps of machine learning that is:

  • linear regression
  • logistic regression 

to more complex models such as: 

  • decision trees
  • neural networks.

During the session, participants will learn how to make supervised machine learning (classification and regression), when to use classification and when to use regression models and when to use classification models, all with hands on and real datasets.

Requirements

  • A basic understanding of python.
  • A basic awareness of the principals of machine learning.

Audience

  • If you are working in marketing, finance, supply chain or Business analytics, you will sure want to use machine learning to have a better understanding and insights from your data.
  • If you are interested in predictive analytics 
  • If you are interested in classification of cases based on the data that you have 
  4 Hours
 

Testimonials

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