Academics
The University of ÃÛÌÇÖ±²¥ Boulder's Master of Science in Data Science (MS-DS) program prepares students to solve complex problems using data-driven approaches across industries. Through an interdisciplinary curriculum that integrates computer science, statistics and information science, students are introduced to core concepts in machine learning, AI tools, big data analytics and statistical modeling.Ìý
Graduates are equipped with the foundational knowledge and analytical skills needed to excel as data scientists, machine learning engineers, AI specialists, business analysts and more in fields like technology, healthcare, finance, government and consulting. Beyond academics, students benefit from Boulder's thriving tech ecosystem and access to world-class research facilities such as NCAR, NIST, and NOAA, with companies like Google, Apple, and Microsoft offering valuable networking and career opportunities.
Ìý
Masters of Science in Applied MathematicsÌý
Statistics & Data Sciences Track
Interdisciplinary, Residential program
Ìý
Masters of Science in Data Science on Campus
Interdisciplinary, Residential program
Ìý
Masters of Science in Data Science on Coursera
Asynchronous, Online program
Ìý
Masters in Business Analytics
Residential, Online program
Masters of Science in Applied Mathematics: Statistics and Data Sciences Track
ÃÛÌÇÖ±²¥ Boulder’s graduate program in applied mathematics offers students the opportunity to specialize in statistics and data science, or a customized track of their choice.
Admission
- Undergraduate degree with GPA of at least 3.0.
- Computing experience, such as R, Python, C, C++ or MATLAB. Experience with UNIX can be helpful.
- Completion of a rigorous calculus sequence and linear algebra are required. More advanced courses, such as Probability Theory, Introduction to Statistics, and Advanced Calculus (analysis), are strongly desired. Other advanced coursework in, for example, partial differential equations, complex analysis or numerical analysis would also be beneficial.
Key Courses
- Statistical Modeling for Data ScienceÌý
- Data AssimilationÌý
- Theory of Machine Learning
- Time Series
- Deep Learning I and II
- Computational Bayesian Statistics
- Randomized Algorithms
- Mathematical Statistics
Careers
- Data Scientist
- Data Analyst
- Machine Learning EngineerÌý
- Statistician
Masters of Science in Data Science on Campus
An interdisciplinary, residential program combining courses in computer science, statistics, and information science as well as application area courses.
Admission
- Undergraduate degree with GPA of at least 3.0Ìý
- Bridging courses are provided for those without a calculus or programming background.
Key Courses
- Statistical Methods 1 & 2
- Machine Learning
- Data Structures and Algorithms
- Data Mining
- Choose from many electives including Independent Studies and Internships
Careers
- Data Scientist
- Data Analyst
Masters of Science in Data Science on Coursera
Fully asynchronous, online program for students wanting a self-paced program. ÌýCourses offered in 6 Eight week sessions per year.
Admission
- Complete a pathway specialization (3 credit hours) with a B average or better
- Choose from Data Structures and Algorithms or Statistical Inference Pathway Specializations
Key Courses
- Statistical Methods 1 & 2
- Machine Learning
- Data Structures and Algorithms
- Data Mining
- Choose from many electives
Careers
- Data Scientist
- Data Analyst
Masters in Business Analytics
Leeds MS Business Analytics program (STEM-designated) teaches students the technical skills necessary to apply and manage modern data science to solve data-driven business problems. Leeds MS Business Analytics offers four specialized tracks: Marketing Analytics, Decision Science, Healthcare Analytics, and Security Analytics.
Key Courses
- Advanced Data Analytics
- Machine Learning in Python
- Structured & Unstructured Data Modeling & Analysis
- Modern Artificial Intelligence
- Track Specific courses
Careers
- Business Analyst
- Project Manager
- Data Scientist
- Consultant