MSc in Data ScienceMichigan State University - College of Natural Science
About this program
MSc in Data Science
Prepare for the data-driven decision-making requirements of any industry at a leading US public institution with Michigan State University's 4-semester M.S. degree in Data Science. This new cross-cutting professional degree program shared by the College of Engineering and the College of Natural Science prepares students in fundamentals and applied topics, taught by leading faculty in data science, statistics, computer science, and computational mathematics. You can be part of the inaugural cohort with Fall 2022 admissions.
The MS program in Data Science is recruiting students with strong undergraduate backgrounds in one of the core areas of statistics, computational mathematics, computer science, and information science, or closely related technical fields, and gives them advanced interdisciplinary training across the disciplines of statistics, mathematics, computer, and computational sciences, at levels appropriate for MS students in these respective disciplines.
Typical students come in with adequate programming competencies. These can include practical experience with languages from the mathematical sciences, such as MATLAB or R, or classical object-oriented programming.
Who we look for:
- You have a four-year technical degree and you need to learn more about data analysis methodologies to further your professional career.
- You enjoy the mathematical sciences and you can program, especially when you can see how the practical side can make a difference in real-life problems.
- You want to become proficient at explaining data science methods to your non-technical colleagues and help formulate data-driven team-based decisions.
- You see yourself as potentially capable of inventing new, principled data-science methods which are adapted to the needs of your professional environment.
For further information on admissions, please contact the university.
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The MS degree in Data Science is a 30-credit graduate degree, comprised of 18 required credits, 9 elective credits, and a 3-credit capstone course. Please visit the MSU Registrar course search page for MSU catalog course descriptions.
Six required courses (18 credits) for this program are balanced between the three units:
- Probability and Mathematical Statistics for Data Scientists, at MS level
- Applied Statistical Methodology for Data Scientists, at MS level
- Computer-Science course on Big Data Analysis which includes Collecting, Storing, Preprocessing and Analyzing Large Amounts of Data.
- Computer-Science course on Data Mining, at MS level.
- Foundational course on Algorithms and Methods in Data Science, at MS level
- Foundational course on Applied and Computational Optimization for Data Scientists, Including Implementation, at MS level.
9 credits of elective courses draw from a broad set of courses in the three units. Students with the 6 required courses above are well-prepared for taking electives. The list of electives includes the following, and may include other courses approved by the MS DS committee:
- Statistical Computation Using the Specialized Software R.
- Modern Statistical Data Analysis, Including Statistical Learning
- Statistical learning and data mining
- Bayesian Analysis
- R Programming for Statistics
- Pattern Recognition
- Design and Analysis of Algorithms
- Machine Learning
- Deep Learning
- Parallel computing
- Communication in Data Science.
Other elective courses which are being developed at MSU, some of which are topics courses that have already been taught in CSME, and could be taught jointly with other units. Plans exist for the following topics:
- Uncertainty Quantification (has been taught)
- Applied Topology (has been taught)
- Probabilistic Graphical Models (planned)
- Mathematical Image Processing (planned)
- Biomedical Science Data (planned)
- Applied Machine Learning for Biomedicine (planned)
- Computational Methods for Machine Learning (planned)
A 3-credit capstone course involves the completion of an applied, industrial, or governmental data-science project.
The program is building a portfolio of case studies by featuring capstone projects driven by industry, government, or academic clients.
Scholarships & funding
For information on scholarship and financial aid, please contact the university.
The program is spread over two academic years of instruction; as such, any dedicated two-year MS degree in any one of these disciplines would delve into further depth in that direction than the two-year MS degree in Data Science.
With their computational and analytical skills, the program's graduates can:
- Assimilate, process, and interpret data from rich and diverse sources, or from large and potentially distributed data sets.
- Build computational, mathematical and statistical models which infer meaningful relationships in data and can be used for interpretation and predictive analytics.
- Create visualizations to aid in the understanding of their data and models.
- Communicate their findings and insights to a variety of audiences so that decisions can be made, and action can be taken.
The MS degree in Data Science applies a flat fee per year of $19,000 for in-state, out-of-state, and international students, payable at the start of each of two academic years, for a total of $39,000 for this 30-credit degree program. Other payment options will be available for self-supported residents of Michigan, and for students wishing to complete the program in more than 2 years.
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About this institute
Michigan State University - College of Natural Science
Michigan State University has been advancing the common good with uncommon will for more than 160 years. A top global university, MSU pushes the boundaries of discovery to make a better world while providing students with life-changing opportunities. Students at...
Why study at Michigan State University - College of Natural Science
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Michigan State University - College of Natural Science
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