# GET YOUR DEGREE IN

## DATA THEORY

Develop knowledge and skills

in the mathematical and statistical foundations of data science

Develop knowledge and skills

in the mathematical and statistical foundations of data science

UCLA's Data Theory major joins the strength of the university’s Mathematics department with the innovation of its Statistics department to offer students a world-class education in the foundations of Data Science. At UCLA, all Statistics faculty are data scientists with a wide range of application fields. In Mathematics, data science is well-represented by six faculty members of its Applied Mathematics group.

The Data Theory major focuses on the fundamental concepts needed to model data and to make sense of data. It is this foundation that allows for the fullest and best application of data science. Graduates will come away prepared to be leaders in industry or academia.

Over the last three decades, the interdisciplinary ﬁeld of Data Science has emerged. The ﬁeld employs advanced mathematics, statistics, and computer science, in concert with the remarkable growth in the capacity of computers, to achieve insights, to make predictions, and to make decisions in ways that would have been science fiction in 1985.

Sources and types of data are increasing rapidly, driven by the ubiquitous use of computing in science and commerce, as well as the routine use of automatic measuring and electronic recording devices. This data revolution is transforming the sciences, engineering, and even the humanities.

Examples include biologists working on gene expression, solving problems concerning the ethics of data use and storage; speech, image, and other pattern recognition; banking, ﬁnance, investments, insurance of all types, and their government regulation; digital health records; epidemiological prediction; surveillance; self-driving cars; advertising; Internet searches; logistics; robots; weather, climate; earthquakes; and predictive policing and legal decision-making.

The world is awash in the sea of data, creating an urgent demand for scientists who are able to understand data collection, storage, integration, and analysis.

At UCLA, it is critical to offer a track that produces students well equipped to understand current data science and develop the data science of the future. Using tools based in mathematics, especially the theory of probability, Statistics has become the language of data. However, the deluge of new types and magnitudes of data has outstripped traditional statistical methods and has led to the rapid development of methods outside of Statistics and Applied Mathematics, including what has become known as Machine Learning. Most Data Science programs focus on teaching students the methods of data modeling, analysis and engineering.

What is missing is a rigorous understanding of the statistical and mathematical foundational concepts that underlie these methods. Without these, data scientists lack the understanding to deal with the plethora of problems they will face. UCLA's Data Theory major fills this need.

This capstone major is the first in the world, both in name and content. One key academic difference from the Data Science majors proposed by peer universities is the presence in our major of substantial upper division proof-based mathematics. The major is strong, perhaps stronger than some Masters degrees, in Machine Learning, which is at the core of Data Science.

Altogether, graduates of the Data Theory program at UCLA will have encountered the key programming tools of the field and be strong in programming skills which are acquired via completion of class projects and homework.

Courses offered as part of the major include:

- The basic math and science requirements expected of all science majors, including calculus, introductory physics, and introductory chemistry, in addition to one course each in statistics and computer programming.
- Societal Impacts of Data
- Data Technologies for Data Scientists
- Experience of Data Science (students will solve real data science problems for community-based or campus-based clients)
- Introduction to Data-Driven Mathematical Modeling: Life, The Universe, and Everything
- Mathematical Methods of Data Theory

The fields that the graduates will enter are evolving quickly in response to the type and scale of data that are becoming available. Major corporations have research groups devoted to projects in data science and numerous more recent entrants, including start-ups, are dedicated to particular problem areas.

During their studies, students will have multiple opportunities for encounters with employers. They can take advantage of a planned internship opportunity for summer of the Junior year and other undergraduate research experiences. It is a capstone major, providing the opportunity for students to collaborate in groups solving real data science problems. Students work in small groups with a faculty member and client, with an emphasis on communication, team work, and understanding the scientific question in data science terms.

Committed support of professionals from industries being transformed by data science will assist in internships placement, obtaining data contexts for projects, and keeping UCLA students and faculty connected to developments in industry.

Graduates of UCLA's Data Theory major will be much better prepared to immediately join and contribute. The degree signals to employers and graduate program admissions officers that a strong graduate is a potential leader in data science.