This course Introduces basic data mining concepts and techniques for discovering interesting patterns hidden in large-scale data sets, focusing on issues relating to effectiveness and efficiency.

Clustering data is the process of grouping items so that items in a group (cluster) are similar and items in different groups are dissimilar. After data has been clustered, the results can be analyzed ...

Anomaly detection can be used to determine when something is noticeably different from the regular pattern. BYU professor Christophe Giraud-Carrier, director of the BYU Data Mining Lab, gave the ...

Think of data mining as digging for digital gold. It’s the technique of studying big data to reveal insights, trends, and links that aren't instantly apparent. In simple terms, it takes unprocessed ...

Predictive analytics enables you to develop mathematical models to help you better understand the variables driving success. Predictive analytics relies on formulas that compare past successes and ...

*Note: This course description is only applicable for the Computer Science Post-Baccalaureate program. Additionally, students must always refer to course syllabus for the most up to date information.