Online Master of Science in Data Science Online Master of Science in Data Science Online Master of Science in Data Science
From the University of DenverFrom the University of DenverFrom the University of Denver
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A Curriculum for Data Professionals
Months to Complete
The online MS in Data Science curriculum comprises of 15 courses that provide students with knowledge and skills in critical competencies such as programming, data mining, machine learning, database management, and data visualization.
Upon graduation, students will be able to build tools to collect, evaluate, and interpret data to solve complex challenges across a variety of industries. The curriculum can be completed in 18 to 24 months depending on student schedules.
Because the online MS in Data Science program is available to students from all academic and professional backgrounds, we offer three bridge courses that provide students with a solid foundation in programming to help them succeed in their data science coursework.
Each course is worth 4 credits and does not count toward the 48-credit requirement to complete the data science master’s program.
The three bridge courses are:
Computer Science Programming Basics
This accelerated course covers the basics of Python programming. By the end of the course students will be able to develop, design, and implement Python programs, appreciate the difference between data types, learn to read from and write to files, understand and use data structures, understand and use recursion.
Data Science Mathematics I
This course presents the elements of calculus essential for work in data science. Students will study differentiation and integration in the context of probability density and of optimization.
Data Science Mathematics II
This course presents the basics of linear algebra and discrete math essential for subsequent coursework in data science.
The Datascience@Denver curriculum prepares students to collect, evaluate, and interpret data to inform critical decisions. From the start of the program, students are challenged by rigorous coursework as they learn to tackle the world’s most crucial big-data challenges.
Below are a few examples of featured courses:
Algorithms for Data Science
Students learn the algorithmic strategies and techniques that data scientists use to understand complex data science challenges like dynamic programming, randomization and order statistics.
Students are given an overview of machine learning techniques, the strengths and weaknesses of those techniques, and the problems they are designed to solve. Topics covered include linear and logistic regression, neural networks, and decision trees.
Parallel and Distributed Computing for Data Science
Students implement parallel and distributed computing methods like threaded applications and GPU parallel programming to solve large problems by breaking them down into smaller ones.
DataScience@Denver, the online MS in Data Science program from the University of Denver’s Daniel Felix Ritchie School of Engineering and Computer Science, prepares students at any stage of their careers to use data to help their organizations make more informed strategic decisions.
You will connect with peers from various locations, cultures, and areas of expertise as you learn to harness the power of data. Our students have gone on to work at major international companies as key players in the data science industry, valued for their diverse perspectives and proactive methods of problem solving.
“The DataScience@Denver program is distinguished by its rigor—students coming from many disciplines develop essential skills like probability and statistics, programming, and problem solving. The curriculum was designed to produce graduates who are prepared to enter the exciting and demanding field of data science.”
– Bruce Harmon, Professor of the Practice of Computer Science and Faculty Director for DataScience@Denver
Gain the Data Skills You Need to Solve Complex Challenges
Explore the online MS in Data Science program today
Applicants must hold a bachelor’s degree from a regionally accredited college or university or the recognized equivalent from an international institution. Although applicants must demonstrate strong analytical skills, technical and/or programming experience is not required.
GRE scores are not required for admission to the program. In addition to the online application, students must submit the following:
Application Fee or Waiver
Letters of Recommendation
The online data science master’s program has four start dates throughout the year. Applications are reviewed and accepted on a rolling basis.
The data science field continues to grow as more companies rely on the benefits of data collection and evaluation. According to the U.S. Bureau of Labor Statistics, the number of jobs for data analyst professionals will increase by 25% from 2019 to 2029.1