Program Overview

Introduction to the Master of Data Science Program

The Master of Data Science program at Rice University is designed to prepare professionals for careers in data science, business analytics, data engineering, and machine learning/AI. The program features a flexible, yet rigorous, curriculum that includes instruction by data science experts and a best-in-class online teaching methodology.

Program Curriculum

The online Master of Data Science curriculum requires the completion of a minimum of 31 credit hours, including five core courses designed to help students gain an understanding of the computational and statistical foundations of data science.

Core Required Courses

• COMP 614 - Programming for Data Science (3 credit hours): An introduction to computer programming designed to give an overview of programming and algorithmic topics commonly seen in Data Science.
• COMP 642 - Machine Learning (3 credit hours): Machine learning is the automation of the inductive learning process that humans do so well.
• COMP 643 - Big Data (3 credit hours): This class will cover the theory and practice of Big Data.
• COMP 665 - Data Visualization (3 credit hours): Data is being generated by humans and algorithms at an astounding rate.
• COMP 680 - Statistics for Computing and Data Science (3 credit hours): Probability and statistics are essential tools in data science and central to fields like bioinformatics, social informatics, and machine learning.

Specialization

Rice's online MDS students will select one 9-credit hour specialization. At this time, online students can take:

• Machine Learning (9 credit hours): Understand the basis for machine learning and how a machine can learn without being programmed.
• Business Analytics (9 credit hours): Build business acumen and transform data into actionable business insights.

Electives

The electives below are representative and may be subject-to-change based on Faculty availability.

• COMP 628 - Cybersecurity (3 credit hours): This introductory cybersecurity course includes topics relevant to core components of cybersecurity technologies, processes, and practices designed to protect networks, computers, and data from attack, damage, and unauthorized access.
• COMP 630 - Databases (3 credit hours): This course includes five learning objectives.
• COMP 682 - Principles of Algorithms and Software Area (3 credit hours): This course covers the fundamental algorithms and data structures that all masters of computer science students should know.
• RCEL 504 - Ethical-Technical Leadership (3 credit hours): Technology-based companies are powered by teams of engineers who create products and services that create value and competitive advantages for organizations that can turn into profits.

Capstone Project

• DSCI 535 - Applied Machine Learning and Data Science Projects (4 credit hours): In this project-based course, you'll have the opportunity to put your new knowledge into practice.

Professional Development Requirement

• Professional Development Requirement (0-3 credit hours): As the Master of Data Science program is a professional master's degree, an important part of the program is a student's professional development.

Program Highlights

• Academic Rigor: Intellectual challenge met with unquestioning support.
• Holistic Approach: Obtain comprehensive knowledge in how to apply core methods of data science to areas of specialization.
• Same Degree as In-Person: The same curriculum offered on-campus with the added flexibility of an online program.
• Leading Faculty: World-class faculty that provide hands-on education and thoughtful interactions with students.
• Real-World Application: Coursework designed to enable students to solve real-world problems with data science theory and techniques.
• Customizable Program: The flexible format prepares students to launch or advance their careers in data science and technology industries.

Program Outcomes and Experience

• Data Science Skill Attainment: Quickly acquire computational and statistical foundations in data science, specialized knowledge in subjects of your choice and hands-on experience managing raw data to solve real-world problems.
• New Confidence in Business Communications: Gain professional confidence in communicating to lay audiences orally and in writing about data science methods and results.
• Professional Preparation: Experience a collaborative and engaging format and a rigorous curriculum taught by faculty recognized for their teaching, research and practice — all designed to prepare you to meet the demands of employers.

Online Bridge Course

Rice University's online bridge course is designed to provide you with the necessary refresh in math and programming that will help you succeed in the online Master of Data Science program. The six-week-long session will give you a head start on mastering technical skills that will ease your transition into the data science master's degree curriculum.