Data Science
In a world of fast-evolving technology, science and business, data science is an essential tool for organizations looking to stay ahead of the curve. If you are fascinated by analysis and you have a mind for numbers, the data science program may be perfect for you. Our MS in data science provides students with a broad course of study in programming, algorithms, statistics and data management, as well as a depth of understanding in specific fields such as data mining, machine learning and parallel systems.
Graduates of the data science program go on to work in a wide variety of careers, including business, government, education and the natural sciences. Whether you're interested in research or want to bring your data expertise to the entrepreneurial realm, you will be prepared to reach across disciplines, making sense of the past and present to improve the future.
With technology existing in a state of constant evolution, the ability to access, understand and analyze data is essential for any organization or company looking to stay ahead of the curve. In our MS in Data Science program, you’ll learn and develop comprehensive data science skills, including programming, algorithms, machine learning, data mining, parallel and distributed systems, and data management.
In addition to learning how to use existing statistical and analytical tools for evaluating and interpreting data, you'll also learn how to build new tools that facilitate the use of data in making research, policy and business decisions. Your learning will be reinforced with practical, hands-on team projects, where you'll apply your skills to real-world problems.
Graduates of the Data Science program go on to work in a wide variety of careers, including business, government, education and the natural sciences. Whether you're interested in going into research or want to bring your data expertise to the entrepreneurial realm, you will be prepared to reach across disciplines, making sense of the past and present to improve the future.
Featured Courses
COMP 3432
Machine Learning
About this Course
This course will give an overview of machine learning techniques, their strengths and weaknesses, and the problems they are designed to solve. This will include the broad differences between supervised, unsupervised and reinforcement learning and associated learning problems such as classification and regression. Techniques covered, at the discretion of the instructor, may include approaches such as linear and logistic regression, neural networks, support vector machines, kNN, decision trees, random forests, Naive Bayes, EM, k-Means, and PCA. After taking the course, students will have a working knowledge of these approaches and experience applying them to learning problems. Enforced Prerequisites: COMP 2370 and COMP 2355.
COMP 4441
Introduction to Probability and Statistics for Data Science
About this Course
The course introduces fundamentals of probability for data science. Students survey data visualization methods and summary statistics, develop models for data, and apply statistical techniques to assess the validity of the models. The techniques will include parametric and nonparametric methods for parameter estimation and hypothesis testing for a single sample mean and two sample means, for proportions, and for simple linear regression. Students will acquire sound theoretical footing for the methods where practical, and will apply them to real-world data, primarily using R. Enforced Prerequisites and Restrictions: COMP 1671, MATH 1951, MATH 1952, or Data Science Bridge Courses I-IV, or equivalent experience
COMP 4333
Parallel and Distributed Computing
About this Course
Current techniques for effective use of parallel processing and large scale distributed systems. Programming assignments will give students experience in the use of these techniques. Specific topics will vary from year to year to incorporate recent developments. This course qualifies for the Computer Science "Advanced Programming" requirement. Prerequisites: COMP2370 and COMP2355, or equivalent.
Application Information
Take the first step toward your academic career at the Ritchie School and start your application today.
Fall 2023 Final Deadline
