Statistics and data science
Master
In Maynard (USA)
Description
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Type
Master
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Location
Maynard (USA)
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Start date
Different dates available
Statistics, the science of making inferences and decisions under uncertainty, is becoming increasingly relevant in the modern world due to the widespread availability of and access to unprecedented amounts of data and computational resources. Unlike classical statistics, the need to process and manage massive amounts of data has become a key feature of modern statistics. This aspect of managing and processing data is popularly referred to as “data science.” Through six required subjects, the Minor in Statistics and Data Science provides students with a working knowledge base in statistics, probability, and computation, along with an ability to perform data analysis. Consult minor advisor about potential substitutions. Subject has prerequisites that are outside of the program. A minimum of four subjects taken for the Statistics and Data Science Minor cannot also count toward a major or another minor. See the Statistics and Data Science Minor webpage for additional information. Inquiries about the undergraduate program may be directed to the IDSS Academic Office.
Facilities
Location
Start date
Start date
Reviews
Subjects
- Probability
- Computational
- Engineering
- Statistics
- Data analysis
Course programme
6-12
Engineering Mathematics: Linear Algebra and ODEs
Introduction to Computer Science and Programming
Introduction to EECS via Robotics
Differential Equations
Linear Algebra
12
Introduction to Probability and Statistics in Engineering
Introduction to Probability I
and Introduction to Probability II
Statistics for Brain and Cognitive Science
Introduction to Statistical Methods in Economics
Introduction to Applied Probability
Statistics and Probability
Probability and Random Variables
12
Econometric Data Science
Statistical Thinking and Data Analysis
Fundamentals of Statistics
24
Engineering Computation and Data Science
Numerical Computation for Mechanical Engineers
Introduction to Inference
Introduction to Machine Learning
Foundations of Computational and Systems Biology 2
Advances in Computer Vision
Advanced Econometrics
Optimization Methods in Business Analytics
Computational Modeling and Data Analysis in Aerospace Engineering 2
Topics in Mathematics with Applications in Finance 2
Statistics, Computation and Applications
Consult minor advisor about potential substitutions.
Subject has prerequisites that are outside of the program.
Statistics and data science