Northwestern University(Data Science Program)
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QUICK FACTS
Degree Name | Master of Science in Analytics |
Duration | 15 months, full-time |
Start Date | Each Fall Quarter (September) |
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Class Size | Approximately 40 students per cohort |
Program Features |
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Location | Evanston campus |
Cost | Tuition and funding information |
Application opens | September 1 |
Application deadline | Scholarship Priority Deadline: December 1
Regular Decision Deadline: January 15 |
WHY MSIA AT NORTHWESTERN UNIVERSITY?
The Master of Science in Analytics program is housed within the department of Industrial Engineering and Management Sciences at the McCormick School of Engineering. We are a full-time, 15-month professional master's degree with an applied data science curriculum.
Many programs focus on just one aspect of analytics, producing graduates who are trained primarily in either modeling or data mining. Our program takes a broader, more comprehensive approach to analytics education. Coursework includes advanced machine learning and artificial intelligence techniques in addition to traditional applied statistical approaches. Students learn to think critically about matching techniques and programming solutions to business problems within an organizational context. To ground our curriculum in practical data science, our faculty use case studies of real-world analytics problems to foster discussion and refine mathematical, computing, and operational skills.
The Master of Science in Analytics program at Northwestern University features study in all three areas of analytics: predictive, prescriptive, and descriptive. Industry access, including a practicum project, capstone project, and a required data science internship, allow students to immediately implement their new skills. The full-time, small cohort helps to foster a tight-knit community where students are able to share their strengths and build meaningful connections. Our customized curriculum taught by tenured faculty from the McCormick School of Engineering, the Kellogg School of Management, and the Medill School of Journalism, Media, and Integrated Marketing Communications combines data engineering, machine learning, artificial intelligence, data science, and business.
DIVERSITY AND INCLUSION
The Master of Science in Analytics program strives to foster an environment that values diversity and inclusion of all people. For more information on Northwestern University's dedication to diversity and inclusion, please visit the Office of Institutional Diversity and Inclusion.
Discover Our Whole-brain Engineering Philosophy
We augment the analytical core of engineering with design, entrepreneurship, leadership, personal development, and unusual collaborations to imagine what's next and take the world in a whole new direction.
MSIA BLOG
Check out the MSiA research blog, featuring independent student and alumni research.
Data science is everywhere
Incredible amounts of data are generated every day, from apps on your phone to medical devices. And, every part of society connects with data: agriculture, engineering, finance and more.
Data science can give you the amazing power to . . .
Make a difference. Use data to solve global hunger or drive better business decisions. Maybe one day you could shape a hurricane disaster response plan, improve self-driving cars or define a military defense strategy.
Challenge yourself. Engage your quantitative and creative side. You’ll learn to apply the technical fundamentals of data science to data analysis pipelines and develop the knowledge and skills to transform data into insights. Learn about data visualization and how to communicate your findings to inform actions.
Create your future. Data scientists have the skills for a rewarding career in almost any industry!
Iowa State’s data science program offers . . .
- A bachelor of science undergraduate degree in data science
- A minor in data science
- A certificate in data science
- A variety of special tracks – choose your interest area from big data, engineering applications, optimization, security, software analytics, statistics and computational biology.
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