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Course Description

Female IT engineer standing in front of a data center

This course will equip you with the knowledge and skills on the use of algorithms and their application in different domains. Participants will discover how to visualize the results of data analysis and present the results in a way that tells a story and explains concepts using non-technical language. The course will be delivered using a variety of hands-on learning activities that provides participants with practice scenarios in data mining and machine learning.

This course is designed for professionals working with data from various sectors in healthcare, finance, insurance and marketing, data science and data analytics professionals.

If you have previous experience coding in R, you may be eligible for advanced standing and could begin working towards your certificate this fall. For additional information about completing a prior learning assessment, please contact the program manager

Learning Outcomes

Upon successful completion of the course, students will be able to:

  • Examine cases of descriptive and predictive problems.
  • Apply clustering approaches such as K-means and hierarchical clustering.
  • Investigate data classification using statistical methods such as logistic regression, naïve Bayes.
  • Demonstrate machine learning with Support Vector Machines, decision trees and random forest.
  • Explain the Deep Learning concept and methodologies and apply Neural Network methods to data sets.
  • Describe model evaluation methods.
  • Discover how to visualize the results of data analysis and present results in non-technical language.
  • Program using advanced R language.

Additional Requirements

Admission to the program requires an Undergraduate degree or College Diploma plus the completion of a Basic Statistics course.

Applies Towards the Following Certificates

*Course details are subject to change.

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Section Title
Data Mining and Machine Learning
Type
Online
Dates
January 20, 2020 to March 15, 2020
Contact Hours
40.0
Delivery Options
Online  
Course Fee(s)
Early Bird $995.00
Potential Discount(s)
Instructors
Section Notes
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