Announcing New Graduate Certificate in Data Science
Editor's note: This article has been updated to reflect the program's new 2017 start date.
The Department of Computer Science at the University of Maryland is pleased to announce the creation of a Graduate Certificate of Professional Studies in Data Science starting in
Fall Semester 2016 Fall Semester 2017.
Called the “best job in America,” data scientists are in demand for their ability to create data-centric products, applications, or programs to address many scientific, socio-political, or business questions. In order to provide working professionals with the opportunity to become excellent practioners in this field, the University of Maryland’s highly-ranked Computer Science Department has created a brand-new Graduate Certificate of Professional Studies in Data Science. This 12-credit certificate evening program gives students the opportunity to learn the foundations of data science from our expert faculty, including computer science professors Amol Deshpande, Hal Daumé III, and Héctor Corrada Bravo. They will teach courses in Machine Learning, Statistics, Databases, and Visualization.
Students will receive a broad introduction to Data Science including how to extract and clean data, how to store and manage large quanties of data, as well as how to analyze that data and extract insights from it. Those who successfully complete the program will be able to understand different components of the data science pipeline. And after working with unstructured, messy data to create specific requirements for a data-centric application that addresses a specific problem or question, students will also be able to make important insights about that data. Students will also know the key steps to acquire and integrate data, and know how to do data cleaning, entity resolution, information extraction, and data integration. They will also be able to decide which machine learning techniques are applicable to a particular problem and implement those techniques without a pre-built library. Finally, students will not only learn to decide which algorithms are applicable to their big data applications, but they will be able to use a variety of statistical toolkits, software packages, and systems for processing and extracting insights from large volumes of data.
Please contact Professor Amol Deshpande for more information: amol [at] cs.umd.edu
The Department welcomes comments, suggestions and corrections. Send email to editor [at] cs [dot] umd [dot] edu.