Key Skills: Machine learning, R programming, generalized linear models, problem-solving for business, detecting outliers and missing values, scoring data, predictive analytics techniques, preparing data sets, regression, classification
Description: The Machine Learning course is included in the Online MSBA core, teaching predictive analytics techniques in a largely hands-on course working with data sets. Working predominantly in R, topics include preparing data, building models and analyzing the results. Many concepts and skills can also be applied to working in Python as well. This course prepares the future data scientist’s toolkit with a deep understanding of the theory and practice of regression and classification.
The focus will be on data preparation in the initial stages of the course before progressing to building models and performing analysis from prepared data. By the end of the course, students will have learned how to determine the appropriate generalized linear model or models for a given data set, how to detect and handle outliers and missing values in prepared data and how to score data, which involves applying algorithmic models, built from one data set, to another data set in order to solve a business problem.
By clicking "Submit" and submitting this form, I agree to receive text messages, emails and other communication regarding educational programs and opportunities, and to be contacted by William & Mary and Everspring, its authorized representative. Message and data rates may apply. Message frequency varies. Reply HELP for help and STOP to cancel. View our privacy policy and disclosures.
William & Mary has engaged Everspring, a leading provider of education and technology services, to support select aspects of program delivery.
