Machine Learning for Business Applications

Catalog description

Machine learning, a subset of artificial intelligence, gives computers the capability to learn from data, identify patterns, and make decisions without being explicitly programmed. This course will cover different supervised and unsupervised machine learning algorithms, and their applications to structured and unstructured data including financial, marketing, health care, social media, entertainment, and socio-economic data. Four main problem domains will be covered (i) regression, (ii) classification, (iii) clustering, and (iv) association. Using machine learning to transform data into business decisions and communication of the results and insights from the analysis will be emphasized throughout the course. This course does not assume any prior exposure to machine learning theory or practice. Prerequisite(s): ANL 301 and STA 202, or permission of department chair.