Data Analysis
Data gathering, manipulation, analysis, and visualization
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Fall 2020 – Winter 2021 | Data Analytics Opportunities
In SI 485: Information Analytics Project, advanced undergraduate students deliver data-oriented solutions through the development and analysis of data sets, building tools to extract useful information for clients through manipulation, analysis, and visualization.
Projects for SI 699: Big Data Analytics must be data-centric and revolve around large-scale datasets. Master’s-level students will work on problems of data manipulation, analysis, and visualization, and use enterprise-scale data to improve performance, outcomes, or understanding of a problem.
In SI 370: Data Exploration, undergraduate students get started with their own data acquisition and exploratory data analysis (EDA). Students in this course will learn basic concepts of information visualization and techniques of exploratory data analysis, using scripting, text parsing, structured query language, regular expressions, graphing, and clustering methods to explore data. Students will be able to make sense of and see patterns in otherwise intractable quantities of data.
In SI 670: Applied Machine Learning, graduate students learn basic machine learning concepts and methods, along with how to select and apply these methods correctly to solve supervised and unsupervised machine learning problems on real-world datasets. students will master basic concepts of supervised (classification) and unsupervised (clustering) techniques, identify which technique they need to apply for a particular dataset and problem.