APPLIED DATA
SCIENCE CLARKSON UNIVERSITY
Master of Science in Applied Data Science
Data analytics and big data
Corporations, governments, startups and small businesses crave the insights buried beneath mountains of big data. But they are realizing they need specially trained and highly skilled people who can turn these endless streams of data into useful insight and actionable intelligence. Clarkson will make you a master of data analytics, and the demand for your knowledge and ability will make your career opportunities almost limitless.
This is the degree that changes everything
Big data is everywhere. Making sense of it all demands a multidimensional, crossdisciplinary approach. Clarkson’s customdeveloped program blends business, mathematics and computer science to deliver an unmatched comprehensive, industry-ready data analytics skillset. • Gain a competitive advantage. • Turn big data into smart data. • Improve operations efficiency. • Reduce fraud, waste and abuse. • Understand the factors that turn consumers into customers. No matter your academic or professional background, you can gain the analytical skills and learn the critical methodology needed to make the most of big data. (If you need or want to take prerequisite courses, Clarkson offers them online at no cost.) Use knowledge-discovery skills and information visualization to mine data, formulate predictive models, interpret findings and articulate the value of data.
Fast and flexible
The MS degree program can be completed in a single school year as a full-time residential student or online at your own pace. The program consists of six 3-credit core courses, four 3-credit elective courses and a 6-credit capstone project. The core courses are as follows: Database Modeling, Design & Implementation Probability & Statistics for Analytics Information Visualization Data Mining Applied Machine Learning Data Warehousing
Course list
Elective courses are offered in a variety of areas, and they include, but are not limited to, the following: Big Data Architecture* Big Data Processing and Cloud Services* Optimization Methods for Analytics* Modeling for Insight* Strategic Project Management* Marketing Research Methods* Cost Management and Financial Analysis Introduction to Artificial Intelligence: Principles and Techniques* Geospatial Systems
Computational/Machine Learning Human-Computer Interaction Econometrics Advanced Topics in Supply Chain Management: Simulation and Analysis Deep Learning Image Understanding Software Design and Development Pattern Recognition *Currently offered online
Make data meaningful
Career outlook
For your capstone project (IA690), you’ll work on a sponsored project that puts your skills to use on initiatives for partner companies or data-driven projects for nonprofits.
Demand for data science and analytics professionals in the U.S. is quickly outgrowing the supply of such talent. The number of data science and analytics job listings is expected to increase from 364,000 to 2,720,000 by 2020, according to a 2017 report published by IBM.
The data analytics program is an interdisciplinary program available across schools, which are accredited by the Middle States Commission on Higher Education. Two such programs that it works closely with are the one-year residential MBA program and the online MBA program, both of which are housed in Clarkson’s David D. Reh School of Business. To learn more, please visit: clarkson.edu/graduate/mba clarkson.edu/graduate/online-mba
Go where the data leads
Pharma Entertainment Industries Marketing Technology Industries Engineering Firms Fortune 500s Fast-Growing Startups With Clarkson’s MS in data analytics, you’ll have highly valuable knowledge at the intersection of science, business and engineering. You’ll be prepared for virtually any industry.
LEARN MORE AND APPLY ONLINE AT
clarkson.edu/data-analytics
RC .5M 7/2020 QMC
Office of Graduate Admissions Capital Region Campus 80 Nott Terrace Schenectady, NY 12308 518-631-9831 graduate@clarkson.edu
clarkson.edu/graduate Clarkson University does not discriminate on the basis of race, gender, color, creed, religion, national origin, age, disability, sexual orientation, veteran or marital status in provision of educational opportunity or employment opportunities.