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Master of Science in Data Science

University of Colorado Boulder via Coursera

Overview

An interdisciplinary, applied data science master’s degree with performance-based admissions and no application process.

Join the exciting and growing field of data science! The University of Colorado Boulder is developing a Master of Science in Data Science degree. This degree will draw on CU Boulder faculty expertise in statistics, data science, computer science, business analytics, natural language processing, and information science. You’ll learn cross-functional communication and teamwork as you master the skills that fuel creative problem-solving and drive today’s business innovations. Learn foundational skills and then apply them in elective specialties to achieve your personal career goals.

With short, 4-6 week courses, this rigorous degree matches the needs of today’s workforce. Performance-based admissions means there are no prerequisites or an application. Enroll right away into a series of three, 1-credit “pathway” courses with a focus on either statistics or computer science. Complete your pathway courses with a B or better to be admitted, all while making direct progress toward your degree.

Degree-seeking students will participate in practical, hands-on projects that utilize cloud-based programming environments and Jupyter Notebooks. Coursework includes access to real-world big data sets to prepare you for your future career.

We anticipate launching the degree in the first half of 2021. Sign up to receive the latest updates on this exciting new program!

Who this degree is for:

Anyone interested in the field of data science, no matter your academic background. With performance-based admissions, there is no application process –– simply prove you can do the work and you can earn the degree. Stackable courses, pay-as-you-go tuition, and a flexible path through the curriculum make this degree ideal for those with little or extensive experience in the field of data science.

Syllabus

Initial courses will cover theory and methods of data science, including data structures, programming fundamentals, and statistics. Learn both R and Python programming, the most commonly used languages in data science. Training will emphasize theory and methods as well as the tools of the modern workplace, including Amazon Web Services, the Hadoop file system, and tools like SQL and Apache Spark. Become proficient in Predictive Modeling, Risk Analysis, Data Visualization, Machine Learning, and AI.

Data scientists must also understand how to translate business and research problems into useful technical solutions, which requires communication, teamwork, and leadership skills. You’ll work in teams to learn and practice professional skills of leadership, communication, and collaboration — especially in how to communicate technical solutions to non-technical professionals. You’ll also interact with domain experts from academia, business, government, and nonprofits to apply your data science skills to real industry scenarios. There are also specialized courses in areas like natural language processing, geospatial analytics, and high-performance computing.

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