Data Sciences, B.S. (Science)

Program Code: DTSCS_BS

Entrance to Major

To be eligible for entrance into the Data Sciences major, a degree candidate must satisfy requirements for entrance to the major.

Specific entrance requirements include:

  1. The degree candidate must be taking, or have taken, a program appropriate for entry to the major as shown in the bulletin.
  2. The degree candidate must complete the following entrance-to-major requirements: CMPSC 121* or CMPSC 131*, CMPSC 122* or CMPSC 132*, MATH 140*, MATH 141*, STAT 200* or DS 200*. These courses must be completed by the end of the semester during which the entrance to major process is carried out.

Degree Requirements

For the Bachelor of Science degree in Data Sciences, a minimum of 125 credits is required (at least 18 credits must be taken at the 400 level):

Requirement Credits
General Education 45
Electives 5-14
Requirements for the Major 72-81

6 of the 45 credits for General Education are included in the Requirements for the Major. This includes: 6 credits of GQ courses.

General Education

Connecting career and curiosity, the General Education curriculum provides the opportunity for students to acquire transferable skills necessary to be successful in the future and to thrive while living in interconnected contexts. General Education aids students in developing intellectual curiosity, a strengthened ability to think, and a deeper sense of aesthetic appreciation. These are requirements for all baccalaureate students and are often partially incorporated into the requirements of a program. For additional information, see the General Education Requirements section of the Bulletin and consult your academic adviser.

The keystone symbol Keystone/General Education Course appears next to the title of any course that is designated as a General Education course. Program requirements may also satisfy General Education requirements and vary for each program.

Foundations (grade of C or better is required.)

  • Quantification (GQ): 6 credits
  • Writing and Speaking (GWS): 9 credits

Knowledge Domains

  • Arts (GA): 6 credits
  • Health and Wellness (GHW): 3 credits
  • Humanities (GH): 6 credits
  • Social and Behavioral Sciences (GS): 6 credits
  • Natural Sciences (GN): 9 credits

Integrative Studies (may also complete a Knowledge Domain requirement)

  • Inter-Domain or Approved Linked Courses: 6 credits

University Degree Requirements

First Year Engagement

All students enrolled in a college or the Division of Undergraduate Studies at University Park, and the World Campus are required to take 1 to 3 credits of the First-Year Seminar, as specified by their college First-Year Engagement Plan.

Other Penn State colleges and campuses may require the First-Year Seminar; colleges and campuses that do not require a First-Year Seminar provide students with a first-year engagement experience.

First-year baccalaureate students entering Penn State should consult their academic adviser for these requirements.

Cultures Requirement    

6 credits are required and may satisfy other requirements

  • United States Cultures: 3 credits
  • International Cultures: 3 credits

Writing Across the Curriculum

3 credits required from the college of graduation and likely prescribed as part of major requirements.

Total Minimum Credits

A minimum of 120 degree credits must be earned for a baccalaureate degree. The requirements for some programs may exceed 120 credits. Students should consult with their college or department adviser for information on specific credit requirements.

Quality of Work

Candidates must complete the degree requirements for their major and earn at least a 2.00 grade-point average for all courses completed within their degree program.

Limitations on Source and Time for Credit Acquisition

The college dean or campus chancellor and program faculty may require up to 24 credits of course work in the major to be taken at the location or in the college or program where the degree is earned. Credit used toward degree programs may need to be earned from a particular source or within time constraints (see Senate Policy 83-80). For more information, check the Suggested Academic Plan for your intended program.

Requirements for the Major

To graduate, a student enrolled in the major must earn a grade of C or better in each course designated by the major as a C-required course, as specified by Senate Policy 82-44.

Common Requirements for the Major (All Options)

Prescribed Courses
Prescribed Courses: Require a grade of C or better
DS 220Data Management for Data Sciences3
DS 300Privacy and Security for Data Sciences3
DS 340WApplied Data Sciences3
DS 440Data Sciences Capstone Course3
MATH 140Calculus With Analytic Geometry I Keystone/General Education Course4
MATH 141Calculus with Analytic Geometry II Keystone/General Education Course4
MATH 220Matrices Keystone/General Education Course2
STAT 184Introduction to R2
STAT 380Data Science Through Statistical Reasoning and Computation3
Additional Courses
1 credit of First-Year Seminar1
Additional Courses: Require a grade of C or better
CMPSC 121Introduction to Programming Techniques Keystone/General Education Course3
or CMPSC 131 Programming and Computation I: Fundamentals
CMPSC 122Intermediate Programming3
or CMPSC 132 Programming and Computation II: Data Structures
STAT/MATH 318Elementary Probability3
or STAT/MATH 414 Introduction to Probability Theory
Requirements for the Option
Select an option35-44

Requirements for the Option

Statistical Modeling Data Sciences (DTSCS_BS): 35 credits
Only Available through the Eberly College of Science
Prescribed Courses
Prescribed Courses: Require a grade of C or better
MATH 230Calculus and Vector Analysis4
STAT 415Introduction to Mathematical Statistics3
STAT 440Computational Statistics3
STAT 462Applied Regression Analysis3
Additional Courses
Additional Courses: Require a grade of C or better
DS 200Introduction to Data Sciences4
or STAT 200 Elementary Statistics Keystone/General Education Course
DS 310Machine Learning for Data Analytics3
or CMPSC 448 Machine Learning and Algorithmic AI
MATH 311WConcepts of Discrete Mathematics3
or CMPSC 360 Discrete Mathematics for Computer Science
Supporting Courses and Related Areas 1
Select 6 credits from Quantitative Modeling Option List A courses, see Appendix D6
Select 6 credits from Quantitative Modeling Option List B courses, see Appendix D6

LIST OF STATISTICAL MODELING DATA SCIENCES COURSES

Applied Data Sciences (DATSC_BS): 38 credits
Only Available through the College of Information Sciences and Technology
Prescribed Courses
Prescribed Courses: Require a grade of C or better
DS 200Introduction to Data Sciences4
DS 310Machine Learning for Data Analytics3
DS 320Data Integration3
DS 330Visual Analytics for Data Sciences3
DS 410Programming Models for Big Data3
IST 230Language, Logic, and Discrete Mathematics3
IST 495Internship1
Additional Courses
Select 6 credits from any combination:6
Emerging Trends in the Data Sciences
Artificial Intelligence
Information Retrieval and Organization
Information Technology in an International Context
Globalization Trends and World Issues
Database Modeling and Applications
Research Design for Social Data Analytics
Supporting Courses and Related Areas 1
Select 12 credits from the lists of Application Focus courses in Appendix B; 6 credits must be at the 400 level. 12

LIST OF APPLIED DATA SCIENCES COURSES

Computational Data Sciences (DTSCE_BS): 44 credits
Only Available through the College of Engineering
Prescribed Courses
CMPSC 448Machine Learning and Algorithmic AI3
Prescribed Courses: Require a grade of C or better
CMPSC 221Object Oriented Programming with Web-Based Applications3
CMPSC 360Discrete Mathematics for Computer Science3
CMPSC 442Artificial Intelligence3
CMPSC 455Introduction to Numerical Analysis I3
CMPSC 465Data Structures and Algorithms3
DS 410Programming Models for Big Data3
MATH 230Calculus and Vector Analysis4
STAT 415Introduction to Mathematical Statistics3
Additional Courses
Additional Courses: Require a grade of C or better
DS 200Introduction to Data Sciences4
or STAT 200 Elementary Statistics Keystone/General Education Course
Supporting Courses and Related Areas 1
Select 6 credits from Applied Option List A in Appendix D6
Select 6 credits from Applied Option List B in Appendix D6

LIST OF COMPUTATIONAL DATA SCIENCES COURSES

Academic Advising

The objectives of the university’s academic advising program are to help advisees identify and achieve their academic goals, to promote their intellectual discovery, and to encourage students to take advantage of both in-and out-of class educational opportunities in order that they become self-directed learners and decision makers.

Both advisers and advisees share responsibility for making the advising relationship succeed. By encouraging their advisees to become engaged in their education, to meet their educational goals, and to develop the habit of learning, advisers assume a significant educational role. The advisee’s unit of enrollment will provide each advisee with a primary academic adviser, the information needed to plan the chosen program of study, and referrals to other specialized resources.

READ SENATE POLICY 32-00: ADVISING POLICY

University Park

Eberly College of Science

Undergraduate Statistics Office
Academic Advising
323 Thomas Building
University Park, PA 16802
814-865-1348
stat-advising@psu.edu

College of Engineering

Alisha Simon
Academic Adviser
W360 Westgate Building
University Park, PA 16802
814-867-4436
anw114@psu.edu

College of Information Sciences and Technology

Undergraduate Academic Advising Center
E103 Westgate Building
University Park, PA 16802
814-865-8947
advising@ist.psu.edu

Suggested Academic Plan

The suggested academic plan(s) listed on this page are the plan(s) that are in effect during the 2020-21 academic year. To access previous years' suggested academic plans, please visit the archive to view the appropriate Undergraduate Bulletin edition (Note: the archive only contain suggested academic plans beginning with the 2018-19 edition of the Undergraduate Bulletin).

Statistical Modeling Data Sciences: Data Sciences, B.S. at University Park Campus

The course series listed below provides only one of the many possible ways to move through this curriculum. The University may make changes in policies, procedures, educational offerings, and requirements at any time. This plan should be used in conjunction with your degree audit (accessible in LionPATH as either an Academic Requirements or What If report). Please consult with a Penn State academic adviser on a regular basis to develop and refine an academic plan that is appropriate for you.

First Year
FallCreditsSpringCredits
MATH 140*4MATH 141*4
PSU 161IST 210*3
CMPSC 131*3CMPSC 132*3
STAT 200*4General Education Course3
ENGL 153General Education Course3
 15 16
Second Year
FallCreditsSpringCredits
STAT 184*1STAT 380*3
MATH 220*2STAT 462*3
MATH 230*4STAT 414*3
DS 220*3ENGL 202C3
CAS 1003General Education Course (with IL or US)3
General Education Course3 
 16 15
Third Year
FallCreditsSpringCredits
STAT/MATH 415*3List B Selection*3
DS 300*3STAT 440*3
DS 310 or CMPSC 448 (List B Selection)*3MATH 311W or CMPSC 360*3
General Education Course3General Education Course3
General Education Course3Elective3
 15 15
Fourth Year
FallCreditsSpringCredits
DS 340W*3DS 440*3
List A Selection*3List A Selection*3
List B Selection*3General Education Course (GHW)1.5
General Education Course3General Education Course3
General Education Course (GHW)1.5Elective3
Elective3Elective3
 16.5 16.5
Total Credits 125

University Requirements and General Education Notes:

US and IL are abbreviations used to designate courses that satisfy University Requirements (United States and International Cultures).

W, M, X, and Y are the suffixes at the end of a course number used to designate courses that satisfy University Writing Across the Curriculum requirement.

GWS, GQ, GHW, GN, GA, GH, and GS are abbreviations used to identify General Education program courses. General Education includes Foundations (GWS and GQ) and Knowledge Domains (GHW, GN, GA, GH, GS, and Integrative Studies). Foundations courses (GWS and GQ) require a grade of ‘C’ or better.

Integrative Studies courses are required for the General Education program. N is the suffix at the end of a course number used to designate an Inter-Domain course and Z is the suffix at the end of a course number used to designate a Linked course.

All incoming Schreyer Honors College first-year students at University Park will take ENGL 137H/CAS 137H in the fall semester and ENGL 138T/CAS 138T in the spring semester. These courses carry the GWS designation and replace both ENGL 30H and CAS 100. Each course is 3 credits.

Advising Notes

List A Courses (6 credits required from this list)

List B Courses (6 credits required from this list)

  • DS 310 Machine Learning for Data Analytics
  • DS 320 Data Integration
  • DS 330 Visual Analytics for Data Sciences
  • DS 410 Programming Models for Big Data
  • DS 402 Emerging Trends in the Data Sciences
  • IST 461 Database Management and Administration
  • CMPSC 442 Artificial Intelligence
  • CMPSC 448 Machine Learning and Algorithmic AI
  • CMPSC 465 Data Structures and Algorithms

Statistical Modeling Data Sciences: Data Sciences, B.S. at Commonwealth Campuses

The course series listed below provides only one of the many possible ways to move through this curriculum. The University may make changes in policies, procedures, educational offerings, and requirements at any time. This plan should be used in conjunction with your degree audit (accessible in LionPATH as either an Academic Requirements or What If report). Please consult with a Penn State academic adviser on a regular basis to develop and refine an academic plan that is appropriate for you.

First Year
FallCreditsSpringCredits
MATH 140*‡#†4MATH 141*‡#†4
STAT 200*†4IST 210*3
PSU 161CMPSC 122 or 132*†3
CMPSC 121 or 131*†3ENGL 15 (or General Education Course)3
ENGL 15 (or General Education Course)3General Education Course3
 15 16
Second Year
FallCreditsSpringCredits
MATH 220*†2STAT 414 (or Supporting Course)*3
MATH 230*4ENGL 202C3
CAS 100A3General Education Course3
General Education Course3General Education Course3
General Education Course3General Education Course3
 15 15
Third Year
FallCreditsSpringCredits
STAT 184*2STAT 380*3
STAT 414 (or Supporting Course (if not taken in 4th semester))*3DS 310 (List B)*3
STAT 462*3STAT 415*3
DS 220*3DS 300*3
General Education Course3General Education Course3
Elective3 
 17 15
Fourth Year
FallCreditsSpringCredits
DS 340W*3DS 440*3
List A*3STAT 440*3
List B*3List A*3
General Education Course (GHW)1.5General Education Course (GHW)1.5
CMPSC 360 or MATH 311W*3Elective3
Elective3Elective3
 16.5 16.5
Total Credits 126

University Requirements and General Education Notes:

US and IL are abbreviations used to designate courses that satisfy University Requirements (United States and International Cultures).

W, M, X, and Y are the suffixes at the end of a course number used to designate courses that satisfy University Writing Across the Curriculum requirement.

GWS, GQ, GHW, GN, GA, GH, and GS are abbreviations used to identify General Education program courses. General Education includes Foundations (GWS and GQ) and Knowledge Domains (GHW, GN, GA, GH, GS, and Integrative Studies). Foundations courses (GWS and GQ) require a grade of ‘C’ or better.

Integrative Studies courses are required for the General Education program. N is the suffix at the end of a course number used to designate an Inter-Domain course and Z is the suffix at the end of a course number used to designate a Linked course.

Advising Notes

List A Courses (6 credits required from this list)

List B Courses (6 credits required from this list)

  • DS 310 Machine Learning for Data Analytics
  • DS 320 Data Integration
  • DS 330 Visual Analytics for Data Sciences
  • DS 410 Programming Models for Big Data
  • DS 402 Emerging Trends in the Data Sciences
  • IST 461 Database Management and Administration
  • CMPSC 442 Artificial Intelligence
  • CMPSC 448 Machine Learning and Algorithmic AI
  • CMPSC 465 Data Structures and Algorithms

Career Paths

Data Sciences blends the technical expertise needed to analyze, interpret, and manage big data with the interpersonal skills needed to communicate insights to a variety of audiences. The program prepares students to meet the growing need for professionals who have the analytical and problem-solving skills to address a wide range of societal challenges. Many companies participate in career fairs in Engineering, IST and Science with an express interest in hiring data science interns or graduates. A growing number of M.S. and Ph.D. programs await those who wish to pursue more advanced studies.

Careers

Because our courses blend technical knowledge with skills in communication and business, a Data Sciences degree allows students to compete for leading-edge analytics positions across many different industry sectors. Possible careers include: Data Analyst, Data and Analytics Manager, Data Architect, Data Engineering, Data Visualizer, Statistician.

MORE INFORMATION FOR THE APPLIED DATA SCIENCES OPTION

MORE INFORMATION FOR THE COMPUTATIONAL DATA SCIENCES OPTION

Professional Resources

Contact

University Park

Eberly College of Science

DEPARTMENT OF STATISTICS
326 Thomas Building
University Park, PA 16802
814-865-1348
stat-advising@psu.edu

http://stat.psu.edu/about-us/contact-us

College of Engineering

DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING
W209 Westgate Building
University Park, PA 16802
814-865-9505
arc88@psu.edu

https://www.eecs.psu.edu

College of Information Sciences and Technology

COLLEGE OF INFORMATION SCIENCES AND TECHNOLOGY
E397 Westgate Building
University Park, PA 16802
814-865-8947

https://ist.psu.edu/about/contact