Our curriculum prepares students to design tools that collect, evaluate and interpret data to inform critical decisions. Through rigorous, mathematically based coursework, learners master advanced concepts for a strong foundation for professional success and self-direction.
Hear From Our Students
"In my final semester, I built a neural network - a predictive model for heart disease. I was able to go through a start to finish project. Going forward…it’s invaluable."
In this advanced Python programming course, you will design custom classes to accomplish data science tasks. You will also develop facilities with Python's standard library as well as important data processing packages.
In this set of courses, you will develop and refine your knowledge of calculus, linear algebra, basic probability, and discrete math to master computational processes and problems in machine learning and statistics.
This course will enable you to design, diagram, and query relational and non-relational database management systems. Particular focus will be given to SQL scripting and embedded programming.
In this course, you will acquire industry-ready skills for predictive modeling and data mining based contemporary machine learning algorithms and techniques.
In this set of courses, you will use the R programming language to apply inferential concepts and applications. Linking theory and practice, you will deepen your understanding of parametric and nonparametric statistics for data analysis as well as key steps in model selection, testing and evaluation. You will also apply these skills to complete an independent project based on real world data.
In this course you will design, analyze, and code algorithms for computational efficiency and problem-solving. Including the processing of large data sets.
This course allows you to receive credit toward graduation for participating in a paid data science internship. You will also receive mentoring from an an academic advisor of your choice.
In this course you will learn how to design, train, and evaluate complex multi-layer neural networks in Python. You will also add to your data science portfolio by completing a culminating project of your own design.
This course will enable you to work with machine learning algorithms and big data at scale. Along the way, you will learn industry practices for implementing these techniques as well as insight into the architectures that support them.
These courses are designed to strengthen your coding and data acquisition skills as well as familiarize you with a broad range of data science methods. You will also refine skills for data-centric project development and collaboration that are prerequisites to professional practice.
In this course, you will learn to design, develop, test, and present 'full-cycle' data science products or services. And assess their value in relation to real world situations and needs.
Go to the graduate admission application to submit your information. For information on admission requirements, visit the graduate academic programs page and locate your program of interest.
