F
Fundamentals of Predictive Modelling

Solutions to many business problems are related to

successfully predicting future outcomes. This course

introduces predictive modelling and provides a foundation

for more advanced methods and machine learning. Therefore the overall modelloing process is discussed in detail.



Students will gain an understanding of the general approach to predictive modelling and then build simple and multiple linear regression models in Python and R and apply these in a range of contexts.



Core Reading List:

Mastering Predictive Analytics with R - Second Edition

James D. Miller, Rui Miguel Forte

Publisher Packt

Publication date: August 2017



Predictive Analytics with Python, 1st Edition

Alvaro Fuentes

Publisher Packt

    Application requirements

    Candidates who apply for this course must have a recognised undergraduate degree or equivalent. Candidates without a degree but with other relevant qualifications and/or work experience can also be considered.

    

    English language competency at an IELTS 6.5 (or equivalent) is required of all applicants whose first language is not English. Where students can demonstrate previous substantial studies or work experience in English, this requirement can be waived.

    

  • Accreditation: Unaccredited
  • Total workload: 150 hours
  • Requires extra purchases (outside texts, etc.): Yes, purchases required
  • ID verification: Required
  • Admission requirements: Application required
  • Minimum education requirement for students: Undergraduate