Data Science, B.S.
The Data Science Major prepares students for a career in data analysis, combining foundational statistical concepts with computational principles from computer science. In the first two years of the program students will take core courses in both the Statistics and Computer Science Departments, providing a strong foundation in the principles of each field. In the 3rd and 4th years of the program, students will take more specialized courses, on topics such as design of algorithms, machine learning, information visualization, and Bayesian statistics. A major component of this degree is the final year capstone project course, a 2-quarter course that teaches students how to apply statistical and computational principles to solve large-scale real-world data analysis problems.
Freshman Applicants: See the Undergraduate Admissions section.
Transfer Applicants: See the Undergraduate Admissions section.
Bren School of ICS majors (including shared majors, BIM and CSE) pursuing minors within the Bren School of ICS may not count more than five courses toward both the major and minor. Some ICS majors and minors outside of the School are not permitted due to significant overlap. Visit the ICS Student Affairs Office website for Majors and Minors restrictions. All students should check the Double Major Restrictions Chart and view our information page on double majoring to see what degree programs are eligible for double majoring.
All students must meet the University Requirements.
Data Science Major Requirements
| Lower-division: | |
| A. Select one of the following series: | |
| Introduction to Programming and Programming with Software Libraries and Intermediate Programming | |
| or | |
| Python Programming and Libraries (Accelerated) and Intermediate Programming | |
| B. Complete: | |
| I&C SCI 45C | Programming in C/C++ as a Second Language |
| I&C SCI 46 | Data Structure Implementation and Analysis |
| I&C SCI 51 | Introductory Computer Organization |
| IN4MATX 43 | Introduction to Software Engineering |
| C. Complete: | |
| MATH 2A | Single-Variable Calculus I |
| MATH 2B | Single-Variable Calculus II |
| MATH 2D | Multivariable Calculus I |
| MATH 3A | Introduction to Linear Algebra |
| or I&C SCI 6N | Computational Linear Algebra |
| I&C SCI 6B | Boolean Logic and Discrete Structures |
| I&C SCI 6D | Discrete Mathematics for Computer Science |
| STATS 5 | Seminar in Data Science |
| STATS 7 | Basic Statistics |
| STATS 68 | Statistical Computing and Exploratory Data Analysis |
| Upper-division: | |
| A. Data Science core requirements: | |
| STATS 110 | Statistical Methods for Data Analysis I |
| STATS 111 | Statistical Methods for Data Analysis II |
| STATS 112 | Statistical Methods for Data Analysis III |
| STATS 115 | Introduction to Bayesian Data Analysis |
| STATS 120A | Introduction to Probability and Statistics I |
| STATS 120B | Introduction to Probability and Statistics II |
| STATS 120C | Introduction to Probability and Statistics III |
| I&C SCI 139W | Critical Writing on Information Technology |
| COMPSCI 122A | Introduction to Data Management |
| COMPSCI 161 | Design and Analysis of Algorithms |
| COMPSCI 178 | Machine Learning and Data-Mining |
| IN4MATX 143 | Information Visualization |
| B. Three elective courses from the list below: | |
| Probability II | |
| Stochastic Processes | |
| Multivariate Statistical Methods | |
| Principles in System Design | |
| Digital Image Processing | |
| Computer Simulation | |
| Information Retrieval | |
| Project in Databases and Web Applications | |
| Principles of Data Management | |
| Next Generation Search Systems | |
| Parallel and Distributed Computing | |
| Computer and Network Security | |
| Graph Algorithms | |
| Project in Algorithms and Data Structures | |
| Introduction to Optimization | |
| Introduction to Artificial Intelligence | |
| Neural Networks and Deep Learning | |
| Human Computer Interaction | |
| Information Retrieval | |
| Social Analysis of Computing | |
| C. Data Science capstone team-based project courses: STATS 170A and STATS 170B | |
| Freshman | ||
|---|---|---|
| Fall | Winter | Spring |
| I&C SCI 31 | I&C SCI 32 | I&C SCI 33 |
| MATH 2A | MATH 2B | MATH 2D |
| WRITING 40 | STATS 5 | STATS 7 |
| WRITING 50 | WRITING 60 | |
| Sophomore | ||
| Fall | Winter | Spring |
| I&C SCI 45C | I&C SCI 46 | I&C SCI 51 |
| I&C SCI 6B | I&C SCI 6D | STATS 68 |
| STATS 120A | MATH 3A | STATS 120C |
| General Education III | STATS 120B | General Education VI |
| Junior | ||
| Fall | Winter | Spring |
| COMPSCI 122A, 161, or 178 | COMPSCI 122A, 161, or 178 | COMPSCI 122A, 161, or 178 |
| IN4MATX 43 | I&C SCI 139W | IN4MATX 143 |
| STATS 110 | STATS 111 | STATS 112 |
| General Education IV/VIII | General Education III/VII | |
| Senior | ||
| Fall | Winter | Spring |
| Data Science Major Elective | STATS 115 | STATS 170B |
| Data Science Major Elective | STATS 170A | Data Science Major Elective |
| General Education III | General Education IV | General Education IV |
A wide variety of careers and graduate programs are open to graduates of the Data Science major. Demand for graduates with skills in both statistics and computer science currently outpaces supply - thus, students with these skills typically find employment quickly, across a wide variety of sectors, including internet companies, finance, engineering, business, medicine, and more. Data Science graduates are well-qualified for job titles such as “data scientist,” “data analyst,” or “statistician,” both in the public and private sectors. Graduate school in area such as Computer Science or Statistics is also a possible career path.