Our Practical Data Analysis using Machine Learning course explores several methods and algorithms used to perform regression, classification and clustering tasks. Study such powerful methods as support vector machines, decision trees, random forests, naïve Bayes classifiers and the k-nearest neighbours algorithm. Get an introduction to neural networks, how they work and what they can do, and practice building several artificial neural network models. This data analysis course also gives you the opportunity practice different evaluation techniques for the statistical models you develop since evaluating statistical models is one of the most important and crucial steps in any data analysis task. Develop your understanding of data analysis fundamentals by working with real work problems and data, including your own.
Course Delivery Method:
This course is delivered through a blended model that combines online and on campus environments, rotating on a weekly basis. The first class will be held on campus.
You must have completed our COMP 9721 Introduction to Machine Learning course.
Hours and Fees
- Contact Information
- Technology Department