Purdue University - Department of Computer Science - Data Science Degree Requirements

Data Science Degree Requirements

The first computer science and math courses of the data science degree are almost identical to those of the computer science degree. They lay the foundation of basic principles and skills for the major. The first data science courses in the plan of study are taken in the sophomore year: CS 242, Introduction to Data Science, and STAT 355, Statistics for Data Science. In addition to the body of courses required of all College of Science students, data science majors will take courses in data mining and machine learning, data analytics, probability, and statistical theory. A capstone course or experience is also part of the data science major. Other computer science and statistics electives allow students to tailor the major to personal interests.

All beginning data science majors are required to take CS 19100, Freshman Resources Seminar and CS 19300, Tools. These are 1 credit courses that Computer Science students take in their first semester. Students are equally encouraged to take CS 29100, Sophomore Development Seminar, and CS 39100, Junior Resource Seminar.

CourseTitleCreditsSemester
CS 18000 Problem Solving and Object-Oriented Programming 4 1
CS 18200 Foundations of Computer Science 3 2
CS 38003 Python Programming 1 2
CS 24200 Introduction to Data Science 3 3
STAT 35500 Statistics for Data Science 3 3
CS 25100 Data Structures & Algorithms 3 4
STAT 41600 Probability 3 4
CS 37300 Data Mining and Machine Learning 3 5
STAT 41700 Statistical Theory 3 5
CS 49000 LSDA Large Scale Data Analytics 3 7

Detailed Data Science Description and Plan of Study from the University Catalog

Data Science Electives

The Data Science major requires two additional CS elective courses and one STAT elective course beyond the requirements in the table above.  Required electives must be selected from the following table.

CS Elective Group 1At least one elective is required from this group
CS 30700 Software Engineering I
CS 31400 Numerical Methods
CS 34800 Information Systems
CS 38100 Introduction to the Analysis of Algorithms
CS 47300 Web Information Search and Management
CS Elective Group 2At least one elective is required from this group
CS 35500 Introduction to Cryptography
CS 40800 Software Testing
CS 44800 Introduction to Relational Database Systems
CS 47100 Introduction to Artificial Intelligence
CS 48300 Introduction to Theory of Computation
STAT ElectivesAt least one elective is required from this group
STAT 42000 Introduction to Time Series
MA/STAT 49000 Elementary Stochastic Processes
STAT 40600 Statistical Programming and Data Management
STAT 51200 Applied Regression Analysis
STAT 51300 Statistical Quality Control
STAT 51400 Design of Experiments
STAT 52200 Sampling and Survey Techniques
STAT 52500 Intermediate Statistical Methodology

Unacceptable courses for credit for Data Science students in College of Science

Curriculum Resources

Visit the Curriculum Resource Site to find Sample Plans of Study. Courses do not need to be taken in sequential order as long as prerequisites and co-requisites are met.

Last Updated: Aug 28, 2017 1:08 PM

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