This course introduces data mining and machine learning by exploring the process of extracting patterns and insights from large datasets to support business decision-making. Students will examine techniques such as data cleansing, transformation, classification, predictive analytics, clustering, and association rules, and apply them to real-world applications, including market basket analysis. Through hands-on experience, students will develop proficiency in fundamental tools, algorithms, and programming techniques for supervised and unsupervised learning, enabling them to create effective models for business applications..
Prerequisites: ISM 3011C and STA 2023.
Terms Typically Offered:Fall, Spring, Summer
Credits:3.00
Textbook information will be available online for each term's courses 45 days prior to the first day of classes
for the term.
The courses in this catalog are identified by prefixes and numbers that were assigned by Florida's Statewide
Course Numbering System, a system used by all public postsecondary institutions in Florida and 32 non-public
institutions. Seminole State controls the description, credit and content of its own courses.
