Major in Data Science, Mathematics Concentration

Program Overview

The Data Science program combines computer science, mathematics, and statistics to analyze vast and complex data, fostering knowledge and insight. It prepares students for careers in diverse fields by equipping them with foundational skills in data wrangling, optimization, inferential reasoning, and machine learning, empowering them to revolutionize industries through data-driven decision-making.

Program Outline

Degree Overview:

Data Science is the discovery of knowledge and insight through the analysis of data. As such, it draws on the study of algorithms and their implementation from computer science, the power of abstraction and of geometric and topological formalism from mathematics, and the modeling and analysis of data from statistics. It has emerged as a separate field in response to the avalanche of data from web enabled sensors and instrumentation, mobile devices, web logs and transactions, and the availability of computing power for data storage and analysis. Modern data is challenging not only due to its large scale, but also because it is increasingly heterogeneous and unstructured.

Outline:

The program is structured over four semesters, with a total of 120 credits required for graduation. The program is divided into four years: Freshman, Sophomore, Junior, and Senior. Each year has two semesters. The program includes a variety of courses in computer science, mathematics, and statistics. The program also includes a capstone project in data science.

Freshman Year:

• Semester 1:
• CO 150 College Composition (GT-CO2) - 3 credits
• CS 150B Culture and Coding: Python (GT-AH3) - 3 credits
• DSCI 100 First Year Seminar in Data Science - 1 credit
• MATH 156 Mathematics for Computational Science I (GT-MA1) - 4 credits
• Diversity, Equity, and Inclusion - 3 credits
• Total Credits:
14 credits
• Semester 2:
• CS 164 CS1--Computational Thinking with Java - 4 credits
• DSCI 369 Linear Algebra for Data Science - 4 credits
• STAT 158 Introduction to R Programming - 1 credit
• STAT 315 Intro to Theory and Practice of Statistics - 3 credits
• Biological and Physical Sciences - 4 credits
• Total Credits:
16 credits

Sophomore Year:

• Semester 3:
• CS 165 CS2--Data Structures - 4 credits
• STAT 341 Statistical Data Analysis I - 3 credits
• Historical Perspectives - 3 credits
• Social and Behavioral Sciences - 3 credits
• Total Credits:
13 credits
• Semester 4:
• CS 220 Discrete Structures and their Applications - 4 credits
• DSCI 235 Data Wrangling - 2 credits
• MATH 151 Mathematical Algorithms in Matlab I - 1 credit
• MATH 256 Mathematics for Computational Science II - 4 credits
• STAT 342 Statistical Data Analysis II - 3 credits
• Biological and Physical Sciences - 3 credits
• Total Credits:
17 credits

Junior Year:

• Semester 5:
• DSCI 320 Optimization Methods in Data Science - 3 credits
• Data Science Elective (See List on Concentration Requirements Tab) - 3-4 credits
• Math Elective (See List on Concentration Requirements Tab) - 3 credits
• Select one course from the following:
• CO 300 Writing Arguments (GT-CO3) - 2 credits
• CO 301B Writing in the Disciplines: Sciences (GT-CO3) - 2 credits
• CO 302 Writing in Digital Environments (GT-CO3) - 2 credits
• JTC 300 Strategic Writing and Communication (GT-CO3) - 2 credits
• Elective - 3 credits
• Total Credits:
15-16 credits
• Semester 6:
• CS 201/PHIL 201 Ethical Computing Systems (GT-AH3) - 3 credits
• DSCI 335 Inferential Reasoning in Data Analysis - 3 credits
• DSCI 336 Data Graphics and Visualization - 1 credit
• Data Science Elective (See List on Concentration Requirements Tab) - 3-5 credits
• Math Elective (See List on Concentration Requirements Tab) - 3 credits
• Total Credits:
13-15 credits

Senior Year:

• Semester 7:
• DSCI 445 Statistical Machine Learning - 4 credits
• Data Science Elective (See List on Concentration Requirements Tab) - 3-4 credits
• Math Elective (See List on Concentration Requirements Tab) - 3 credits
• Electives - 6 credits
• Total Credits:
15-16 credits
• Semester 8:
• DSCI 478 Capstone Group Project in Data Science - 4 credits
• Data Science Elective (See List on Concentration Requirements Tab) - 3-5 credits
• Math Elective (See List on Concentration Requirements Tab) - 3 credits
• Electives - 4 credits
• Total Credits:
14-16 credits

Data Science Electives List:

• CS 214 Software Development - 3 credits
• CS 250 Computer Systems Foundations - 4 credits
• CS 270 Computer Organization - 4 credits
• CS 314 Software Engineering - 3 credits
• CS 320 Algorithms--Theory and Practice - 3 credits
• CS 370 Operating Systems - 3 credits
• CS 435 Introduction to Big Data - 4 credits
• CS 440 Introduction to Artificial Intelligence - 4 credits
• CT 301 C++ Fundamentals - 2 credits
• DSCI 473 Introduction to Geometric Data Analysis - 2 credits
• DSCI 475 Topological Data Analysis - 2 credits
• ECON 202 Principles of Microeconomics (GT-SS1) - 3 credits
• ECON 204 Principles of Macroeconomics (GT-SS1) - 3 credits
• ECON 304 Intermediate Macroeconomics - 3 credits
• ECON 306 Intermediate Microeconomics - 3 credits
• ECON 435 Intermediate Econometrics - 3 credits
• STAT 400 Statistical Computing - 3 credits
• STAT 420 Probability and Mathematical Statistics I - 3 credits
• STAT 421 Introduction to Stochastic Processes - 3 credits
• STAT 430 Probability and Mathematical Statistics II - 3 credits
• STAT 440 Bayesian Data Analysis - 3 credits
• STAT 460 Applied Multivariate Analysis - 3 credits

Math Electives List:

• MATH 301 Introduction to Combinatorial Theory - 3 credits
• MATH 317 Advanced Calculus of One Variable - 3 credits
• MATH 331 Introduction to Mathematical Modeling - 3 credits
• MATH 332 Partial Differential Equations - 3 credits
• MATH 345 Differential Equations - 4 credits
• MATH 360 Mathematics of Information Security - 3 credits
• MATH 417 Advanced Calculus I - 3 credits
• MATH 430/ECE 430 Fourier and Wavelet Analysis with Apps - 3 credits
• MATH 455 Mathematics in Biology and Medicine - 3 credits

Other:

• The calculus requirement for the major may alternatively be satisfied by completion of MATH 160, MATH 161, and MATH 261.
• A minimum of 15 total credits must be selected from the Data Science Electives in the Junior and Senior years.
• Select enough elective credits to bring the program total to a minimum of 120 credits, of which at least 42 must be upper-division (300- to 400-level).