Use state-of-the-art software tools to perform data mining and analysis on large structured and unstructured data sets, and transform such data into knowledge.
Design and implement new algorithms for data mining and analysis, and study their time-, space-, and energy-efficiency.
Perform data acquisition and management for extremely large and dynamic databases.
Present and communicate knowledge derived from data in an unambiguous and convincing manner.
Courses
Credit Hours
CAP 5610-Machine Learning
Origin/evaluation of machine intelligence; machine learning concepts and their applications in problem solving, planning and “expert systems” symbolic role of human and computers.
3
CNT 5805-Network Science
Undergraduate degree in CS, EE, or CpE. The emerging science of complex networks and their applications. Focus will be on algorithms, mathematical theories, and computational methods that analyze complex networks and predict their behavior.
3
COP 5711-Parallel and Distributed Database Systems
The course introduces students to parallel computing across the hardware-software stack. Special emphasis is placed on parallel programming using emerging architectures and technologies.
3
STA 5206-Statistical Analysis
Data analysis; statistical models; estimation; tests or hypotheses; analysis of variance, covariance, and multiple comparisons; regression and nonparametric methods.
3
STA 5703-Data Mining Methodology I
Supervised data mining tools including boosting trees, SV machine, regression, and neural network will be covered. The Enterprise Miner (R or Python) will be used.
3
STA 6704-Data Mining Methodology II
Unsupervised learning methods such as cluster analysis, association analysis and newly developed tools will be covered. The Enterprise Miner (R or Python) will be used.
3
CAP 6942-Project in Data Analytics
A project-focused course that demonstrates mastery of data analytics through development of novel algorithms or innovative application of existing techniques for data mining applications.
3
Electives
Credit Hours
CAP 6307-Text Mining I
Extracting knowledge from unstructured text collections. Document indexing, similarity and summarization, clustering, classification, named entity recognition and relation extraction, text stream processing. Several programming assignments.
3
CAP 6315-Social Media and Network Analysis
Techniques developed by the computer science research community for analyzing social networks and social media datasets.
3
CAP 6318-Computational Analysis of Social Complexity
Computational concepts, principles, modeling and simulation approaches used to analyze complex social and economic phenomena, leveraging the availability of large amounts of data, and elements of complexity theory.
3
CAP 6545-Machine Learning Methods for Biomedical Data
Summarize computational techniques for bridging two fields: machine learning and biomedical science to illustrate successful data mining and knowledge discovery in an interdisciplinary context.
3
CAP 6737-Interactive Data Visualization
Principles and techniques for interactive data visualization that are useful for analyzing, presenting and exploring information are covered. The emphasis will be on algorithmic aspects of developing interactive visualization. The students will receive practical experience of building interactive visualization systems.
3
STA 6714-Data Preparation
Variable selections, missing value imputation, text, time series, and new data preparation method will be covered. The Enterprise Miner (R or Python) will be used.