ISM 422

Data Modelling

Academic Year Semester Location Online
2018-2019 Fall, Spring Main campus No

Level: Undergraduate

Credits: 3

Lab Fee: None

Pre-requisites: ISM 331, ISM 420, Senior Standing

In this course, students will design statistical experiments and analyze the results using modern statistical methods and software packages. Students will also explore the pitfalls of interpreting statistical arguements and conclusions, especially those involving big data and large data sets. This course will internalize the core set of practical and effective modelling techniques, machine learning algorithms, and sources of data to solve real world problems. Additionally, this course is designed as both a capstone senior project course and a preparation for data modelling competitions such as those presented on Kaggle.com Prerequisites: ISM 331, ISM 420 and senior standing