Machine Learning 2

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How you should study for this module?

  • View all video lessons and corresponding slide sets
  • Practice with the code samples from the lessons
  • Complete all topics assignments. (Mandatory) 
  • Undertake the case study
  • Study the exam practice questions before the exam
Recommended reading lists
Applied Unsupervised Learning with R, Alok Malik and Bradford Tuckfield, 1st Edition. (Packt Publishing, 2019). 322 pages.
Module overview
Machine learning algorithms are new generation algorithms and used in conjunction with classical predictive modelling methods. In the machine learning unit you will understand applications of various machine learning techniques including the Naïve Bayes Method, Support Vector Machine Algorithm, Decision Tree, Random Forest, Association Rules and Neural Networks.
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assessment requirments
In order to complete this module successfully you will need to 
  1. Attend the scheduled live classes (or view the recorded session)
  2. Watch all learning content on the platform
  3. Complete all topic assignments
  4. Submit case study answers
  5. Pass the module exam with a minimum grade of 50%

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Machine Learning 2 Certificate of Completion

Course Lessons

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