One of the highlights of the Master of Science in Informatics and Analytics program at UNC Greensboro is the opportunity for students to select a concentration of interest. Students may choose one of the following five concentrations.
The Advanced Analytics concentration provides students with the skills required to pursue a career as a data analyst in the world of big data. In addition to providing students with a solid foundation in applied statistical methods and their practical applications, the program offers specialized training to help students handle complex big data.
Software: R, SAS, Python, SQL and Tableau
Potential Projects: credit card approval data analysis (categorical data analysis project), categorical data analysis for Wisconsin breast cancer database, permutation tests for least absolute deviation regression (for statistical computing), survival analysis of Primary Biliary Cirrhosis (PBC) disease, assessing disclosure risk in opioid overdose reporting, statistical analysis on water quality data and Epidemiological studies of potential radon exposure on lung cancer.
Possible Careers: Data Scientist, Statistician, Data Analyst and Statistical Consultant.
Required Courses (6):
IAA 621: Applied Computational Statistics (3)
IAA 622: Complex Data Analysis (3)
One course from the following (3)
IAA 623 Discrete Data Analysis (3)
IAA 624: Multivariate Analysis (3)
IAA 625: Survey Sampling (3)
Required Capstone (3):
IAA 689 Capstone Project in Advanced Data Analysis (3)
The Bioinformatics concentration is an interdisciplinary field that develops and applies computational methods to analyze large biological datasets, including, but not limited to, gene sequences, protein-protein interactions and ontology annotations to answer complex biological questions. The advent of next generation sequencing technologies has led to the creation of large datasets that can be utilized for knowledge discovery. Such data comprise of clinical reports, genome sequences, gene expression profiles, biomedical literature reports and medical images.
The analysis and exploration of these datasets requires scalable and efficient data analytics. Applications of predictive techniques such as Machine Learning and network analysis have found use in healthcare, preventive medicine and drug discovery.
Software: Python, R, and machine learning technologies
Potential Projects: microarray data analysis, gene-gene network analysis, protein-protein interaction networks analysis, sequence analysis, disease network analysis, text mining of scientific literature and analysis of ontology annotation data
Possible Careers: Bioinformatics Research Scientist, Bioinformatic Analyst, Bioinformatics Software Engineer, Research Scientist, Computational Biology/Bioinformatics, Bioinformatics Data Scientist and Genomic Data Scientist
IAB 620 Introduction to Bioinformatics (3)
IAB 621 Big Data in Bioinformatics (3)
IAB 622 Applied Data Mining and Hypothesis Testing for Bioinformatics (3)
IAB 689 Capstone Project in Bioinformatics (3)
The Computational Analytics concentration provides students with knowledge in the areas of big data and data science. Within the following courses, students will learn theories, algorithms and technologies towards the development of analytical systems and models for disparate, complex and small/large scale datasets. The learning objectives of the program enable students to tackle a wide variety of data-focused scientific, social and environmental challenges.
Software: Python, Java, R, Hadoop, Spark, and machine learning technologies.
Potential Projects: health care analytics, social media analytics, text analytics (authorship annotation, supervised learning), image processing and anomaly detection (financial, cyber security).
Possible Careers: Data Scientist, Big Data Engineer, Data and Analytics Manager, Data Architect and Data Analyst.
Required Courses (9)
IAC 620 Algorithm Analysis and Design (3)
IAC 621 Data Science (3)
IAC 622 Big Data and Machine Learning (3)
Required Capstone (3)
IAC 689 Capstone Project in Computational Analytics (3)
The Cultural Analytics concentration studies cultural trends and the circulation of digital artifacts using text mining methods and exploratory data analysis.
Software: R language, R Studio, R Notebooks, Pandoc, and GitHub software
Possible Careers: social media management, news/feed aggregation, data journalism, software documentation, mobile application development, research software development and technical writing
IAL 620 Web Scraping and Online Data Collection (3)
IAL 621 Content Analysis for Social Network Data (3)
IAL 622 The Internet of Things and “Wearable” Analytics (3)
IAL 689 Capstone Project in Computational Analytics (3)
The Geospatial Analysis concentration involves the creation and analysis of geographic data to examine economic, environmental, physical and social phenomena. Students of the program acquire an in-depth knowledge of methods and principles, and gain expertise with leading software packages to prepare for work in the Geographic Information Science research community and industry.
Software: Python, geographic information systems,image processing software, and database management software.
Potential Projects: radiowave propagation modeling, suitability modeling, network analysis, geographic analysis of human and natural phenomena, site selection and location analysis.
Possible Careers: National Geospatial-Intelligence Agency, United States Census Bureau, Environmental Systems Research Institute, Apple Inc. and Alphabet Inc.
Required Course (3)
IAG 620 Understanding Geographic Information Systems (3)
Two courses from the following (6)
IAG 621 Advanced Cartography (3)
IAG 622 GIS Applications in Urban Planning (3)
IAG 623 Advanced Geographic Information Systems (3)
IAG 624 Advanced Remote Sensing (3)
IAG 625 Spatial Analysis (3)
IAG 626 GIS Programming and Design Application (3:3)
Required Capstone (3)
IAC 689 Capstone Project in Geospatial Analysis (3)
- Sports Analytics
- Health Informatics