Big Data analytics and systems

• Genomic data analysis
• Data mining
• Machine learning
• Data management

Big Data usually includes data sets with sizes beyond the abilities of common software tools to capture, manage, and process within a tolerable elapsed time. Big Data study can include fundamental techniques, theories, methodologies, and technologies for broad applications. These techniques, methodologies, and technologies can be computational, statistical, or mathematical in nature. The study of Big Data is an evolving topic, and one that overlaps with work in communications. One example is computational genomics, at the crux of computer engineering and genomics. The field’s goal is to store, organize, and analyze a large amount of genomic information. Another example is data mining, which involves the computational process of discovering patterns in large data sets. Its goal is to extract information from a data set and transform it into an understandable structure for further use.

To specialize in Big Data analytics and systems, you’ll want to take:

And to work in computation genomics, you’ll also want to take:

To specialize in data mining, you might consider taking: