MS In Data Science
Pursue your degree full or part-time and gain the tools that will help companies, government and non-profits make better decisions.
- Who Should Apply: Analytically-minded individuals at any career stage. No computer science background required!
- Enrollment Options: Full or Part-Time
- Location: On-Campus
- Class Schedule: Evening Classes
- Program Length: 9-24 months depending on academic background and full or part-time enrollment
- Next Start: September 2019 (Fall Quarter Start Only)
- Priority Deadline: January 15th, 2019
- Final Application Deadline: August 15th, 2019*
*Due to faculty schedules and availability during interterms, holidays and school breaks, applications completed after the final deadline may not be considered or receive an admissions decision in time to register for the upcoming term. Applicants are thus STRONGLY encouraged to ensure applications requirements are met prior to the August 15th deadline. This includes ensuring references have been submitted by recommenders and transcripts and test scores have been received by DU’s Office of Graduate Education.
As organizations increasingly turn to data to inform decision-making, they are looking for professionals who can build the tools that extract, analyze, interpret and manage massive amounts data from a wide variety of sources. Data scientists uniquely blend technical and creative skills to create solutions that help a range of organizations – corporate, nonprofit, government – thrive and be more successful.
With the University of Denver’s MS in Data Science, you’ll be ready for a successful career as a data scientist. With an explosion of job openings in data science —up 108% since 2013—you’ll be well positioned to pursue the “sexiest job” of the 21st century, as coined by Harvard Business Review.
You’ll learn and develop comprehensive data science skills and knowledge, including programming, algorithms, machine learning, data mining, parallel and distributed systems, and data management. Not only will you learn how to use existing statistical and analytical tools necessary for evaluating and interpreting data, you will also learn how to build new tools that facilitate the use of data in making critical research, policy, and business decisions.
Your learning will be reinforced with practical, hands-on team projects, giving you several opportunities to apply your skills to real world problems.
A previous background in computer science is not required to apply.
If you have previous coursework in Java programming, data structures, calculus, linear algebra and computer science theory, it will take you ~9-18 months to complete your degree depending on whether you’re enrolled full or part-time. Once admitted, you will take a placement exam to ensure you have mastery of the foundational concepts to ensure success in the program.
12 Courses (48 Credits)
- COMP 3421: Introduction to Database Management Systems
- COMP 4333: Parallel and Distributed Computing
- COMP 4431: Data Mining
- COMP 4432: Machine Learning
- COMP 4441: Introduction to Probability and Statistics for Data Science
- COMP 4442: Advanced Probability and Statistics for Data Science
- COMP 4447: Data Science Co-op 1
- COMP 4448: Data Science Co-op 2
- COMP 4449: Capstone Project in Data Science
- COMP 4581: Algorithms for Data Science
- Data Science Elective 1
- Data Science Elective 2
Choose from a variety of electives, including Computer Forensics, Bayesian Analysis, Introduction to Artificial Intelligence, and Programming Languages.
If you do not have previous coursework in these subjects, you’ll take four bridge courses that will serve as a foundation for your data science courses, and you can complete the program in 12-24 months depending on whether you’re enrolled full or part-time. Passing the bridge courses with a 3.0 GPA is required to continue on in the program.
Bridge courses (16 credits if required)
- COMP 3001: Computer Science Theory Basics
- COMP 3005: Computer Science Programming Basics – Java
- COMP 3006: Computer Science Advanced Programming – Advanced Java and Data Structures
- COMP 3007: Data Science Theory Fundamentals – Calculus and Linear Algebra
With an impressive mix of full-time university faculty, you’ll learn from instructors who are on the front lines of data science.
“Data science is behind the scenes of not only executive decision making, but also in how groups influence other people’s actions. For example, to create it’s purchase recommender system Amazon uses a sophisticated prediction algorithm that utilizes a customer’s wish list, items the customer has reviewed, and the purchases and wish lists of other customers who have reviewed the same items. These recommendations have an impact on the actual purchasing decisions and hence the bottom line of the companies that make the products. Further, using data science to influence others is not limited to business, but also occurs in politics. The Obama/Biden campaign in 2012 used data science to predict ad placement and even ad content. In part due to its potential to influence others, data science promises to be one of the most important emerging fields for the future.” —Scott Leutenegger, Data Science Faculty and Chair of the Computer Science Department
“Our ability to collect, store, retrieve, analyze, and act on unprecedented amounts of data in new ways opens up vast opportunities for data science-informed invention. Data scientists are positioned to build transformative innovations in areas such as medicine, energy, education, and the sciences at levels from collection of data to extraction of actionable information.” —Cathy Durso, Data Science Faculty and Research Statistician
As organizations seek to build new tools that capture and make sense of tremendous amounts of data, data scientists are in high demand across all sectors and industries of the economy, commanding an average starting salary of $86,000 with an average overall salary of $129,000.
With an MS in Data Science from the University of Denver, you’ll be ready to assume roles such as Data Scientist, Business Analyst, Software Engineer, or Business Intelligence Director. Your work will include data mining, processing, data visualization, programming, and technical work that contributes to decision-making.
We’re looking for analytical, creative and solution-focused individuals from a variety of backgrounds.
The admission requirements to be considered for the MS in Data Science are:
- Bachelor’s Degree from a regionally accredited college or university (or the recognized equivalent from an international institution)
- Competitive Applicants Typically Earn a Quantitative GRE Score of 156 or higher
- Minimum GPA of 2.5
To apply, submit the following materials:
- Application Form and $65 Fee
- GRE or GMAT Score
- Two Letters of Recommendation
- Personal Statement
- Professional Resume
Additional Requirements for International Applications
Tuition and Financial Aid
Tuition for all students in the MS in Data Science degree is reduced from full tuition rates and is calculated on a per credit hour basis.
For the 2019-2020 academic year, the cost per credit hour for the MS in Data Science will be $1071.
At this rate, tuition for the full MS in Data Science degree in 2019-2020 is roughly $51,408-$68,544 depending on the number of bridge classes needed as determined by the admitted student’s performance on a pre-assessment prior to enrollment.
The MS in Data Science degree is not simultaneously eligible for DU’s flat tuition rate for students taking 12-18 credit hours a quarter.
Federal student loans are available for domestic students.
As tuition is already reduced on a per credit hour basis for all admitted students, we do not provide additional scholarships, assistantships or financial assistance.
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Kickstart Your Career in Data Science with the Ritchie School