Data Science with Concentration in Computation and Modeling, B.S.
Learn more about the Bachelor of Science in Data Science.
Data Science is an interdisciplinary field of study about methods and systems to extract knowledge or insights from large quantities of data coming in various forms. Temple's B.S. in Data Science is designed for students interested in developing expertise in data science. The Computation and Modeling concentration provides the tools necessary to create accurate, robust, and detailed models of real systems in a scientific or professional field. A strong core of mathematics, physics, computational methods and techniques, and data analysis will enable students to model any complex physical system. Elective courses will allow students to specialize in a specific area of interest.
Undergraduate Contact Information:
Department of Computer and Information Sciences
Dr. Jamie Payton, Chair
Science Education and Research Center, Room 304
2152048450
Dr. Gene Kwatny, Vice Chair
Science Education and Research Center, Room 304
2152048450
Dr. Anthony Hughes, Faculty Advisor
Science Education and Research Center, Room 344
2152047910
anthony.hughes@temple.edu
Department of Physics
Dr. James Napolitano, Chair
Science Education and Research Center, Room 406
2152041638
Dr. Bernd Surrow, Vice Chair
Science Education and Research Center, Room 420
2152041638
Dr. Matthew Newby, Faculty Advisor
Science Education and Research Center, Room 476
2152042642
matthew.newby@temple.edu
Bachelor of Science
Summary of Requirements for the Degree
 University Requirements (123 total s.h.)

Students must complete all University requirements including those listed below.

All Temple students must take a minimum of two writingintensive courses at Temple as part of their major. The specific writingintensive course options for this major are:
Course List Code Title Credit Hours PHYS 2796 Introduction to Modern Physics 4 CIS 4496 Projects in Data Science 3  Students must complete the General Education (GenEd) requirements.
 See the General Education section of the Undergraduate Bulletin for the GenEd curriculum.
 Students who complete CST majors receive a waiver for 2 Science & Technology (GS) and 1 Quantitative Literacy (GQ) GenEd courses.
 Students must satisfy general Temple University residency requirements.

 College Requirements

45 Upper Level (2000+) credits within the College of Science & Technology (CST), the College of Liberal Arts (CLA), or the College of Engineering (ENG).

90 credits within the College of Science & Technology (CST), the College of Liberal Arts (CLA), or the College of Engineering (ENG).

All students in the College of Science and Technology are required to take a one credit first year seminar. SCTC 1001 CST First Year Seminar is the appropriate course option for every entering first year CST major. Transfer students should use SCTC 2001 CST Transfer Seminar to fulfill this requirement. Other courses that fulfill this requirement may be found on the CST College Requirements page.

 Major Requirements for Bachelor of Science (7983 s.h.)
At least 9 courses required for the major must be completed at Temple. At least 7 CIS courses must be completed at Temple.Course List Code Title Credit Hours Introductory Science Requirements Select one of the following sets: 8 Elementary Classical Physics I
and Elementary Classical Physics IIHonors Elementary Classical Physics I
and Honors Elementary Classical Physics IIGeneral Physics I
and General Physics IIHonors General Physics I
and Honors General Physics IICalculus Requirements MATH 1041 Calculus I 4 or MATH 1941 Honors Calculus I MATH 1042 Calculus II 4 or MATH 1942 Honors Calculus II Math Methods in Computing Requirements CIS 1166 Mathematical Concepts in Computing I 4 or CIS 1966 Honors Mathematical Concepts in Computing I CIS 2166 Mathematical Concepts in Computing II 4 Probability and Statistics Requirements MATH 3031 Probability Theory I 3 MATH 3032 Mathematical Statistics 3 Programming Requirements CIS 1068 Program Design and Abstraction 4 or CIS 1968 Honors Program Design and Abstraction CIS 2168 Data Structures 4 Common Specialty Course Requirements CIS 3715 Principles of Data Science 4 CIS 4496 Projects in Data Science 3 Concentration Requirements CIS 3223 Data Structures and Algorithms 3 MATH 2043 Calculus III 4 or MATH 2943 Honors Calculus III Select one of the following: 34 Differential Equations with Linear Algebra Linear Algebra Linear Algebra with Computer Lab MATH 3043 Numerical Analysis I 4 PHYS 2511 Scientific Computing I 1.5 PHYS 3511 Scientific Computing II 1.5 PHYS 2502 Mathematical Physics 4 PHYS 2796 Introduction to Modern Physics 4 Computation and Modeling Elective Requirements Select from the following list: 912 Probability, Statistics & Stochastic Methods Computer Graphics and Image Processing Knowledge Discovery and Data Mining or CIS 5523Knowledge Discovery and Data Mining Analysis and Modeling of Social and Information Networks or CIS 5524Analysis and Modeling of Social and Information Networks Foundations of Machine Learning Remote Sensing and GIS Numerical Analysis II Probability Theory II Partial Differential Equations Applied Mathematics Introduction to Numerical Analysis Classical Mechanics Analytical Mechanics Electricity and Magnetism Classical Electromagnetism Introduction to Quantum Mechanics I Thermal Physics Optics Introduction to Solid State Physics Introduction to Quantum Mechanics II Undergraduate Research (max of 3 credits across all independent study) Senior Individual Study (max of 3 credits across all independent study) Total Credit Hours 7983
Calculation of Major GPA
Courses listed under the major requirements for the degree will be included in the calculation of the major GPA. Courses that could not apply toward the major as an elective or a required course are not counted in the calculation of the major GPA.
Distinction in Major
To graduate with Distinction in Major, students are required to have a 3.50 or higher grade point average (GPA) both in the major and overall, as well as be recommended by the department of Computer & Information Sciences.
Suggested Academic Plan
Bachelor of Science in Data Science with Concentration in Computation and Modeling
Requirements for New Students starting in the 20212022 Academic Year
Year 1  

Fall  Credit Hours  
CIS 1068 or 1968  Program Design and Abstraction  4 
MATH 1041 or 1941  Calculus I  4 
SCTC 1001  CST First Year Seminar  1 
ENG 0802, 0812, or 0902  Analytical Reading and Writing [GW]  4 
GenEd Breadth Course  3  
Term Credit Hours  16  
Spring  
CIS 1166 or 1966  Mathematical Concepts in Computing I  4 
MATH 1042 or 1942  Calculus II  4 
IH 0851 or 0951  Intellectual Heritage I: The Good Life [GY]  3 
GenEd Breadth Course  3  
Term Credit Hours  14  
Year 2  
Fall  
CIS 2166  Mathematical Concepts in Computing II  4 
CIS 2168  Data Structures  4 
MATH 2043 or 2943  Calculus III  4 
Select one of the following:  4  
Elementary Classical Physics I  
Honors Elementary Classical Physics I  
General Physics I  
Honors General Physics I  
Term Credit Hours  16  
Spring  
CIS 3223  Data Structures and Algorithms  3 
CIS 3715  Principles of Data Science (S)  4 
Select one of the following; must be continuation of prior Physics course:  4  
Elementary Classical Physics II  
Honors Elementary Classical Physics II  
General Physics II  
Honors General Physics II  
PHYS 2511  Scientific Computing I  1.5 
IH 0852 or 0952  Intellectual Heritage II: The Common Good [GZ]  3 
Term Credit Hours  15.5  
Year 3  
Fall  
MATH 3031  Probability Theory I  3 
Select one of the following:  34  
Differential Equations with Linear Algebra  
Linear Algebra  
Linear Algebra with Computer Lab (F)  
PHYS 3511  Scientific Computing II  1.5 
GenEd Breadth Course  34  
GenEd Breadth Course  3  
Elective  20  
Term Credit Hours  15.5  
Spring  
MATH 3032  Mathematical Statistics (S)  3 
PHYS 2502  Mathematical Physics (S)  4 
PHYS 2796  Introduction to Modern Physics [WI] (S)  4 
GenEd Breadth Course  3  
Elective  1  
Term Credit Hours  15  
Year 4  
Fall  
MATH 3043  Numerical Analysis I (F)  4 
Data Science: Computation & Modeling Elective  34  
Data Science: Computation & Modeling Elective  34  
Elective  3  
Elective  31  
Term Credit Hours  16  
Spring  
CIS 4496  Projects in Data Science [WI]  3 
Data Science: Computation & Modeling Elective  34  
Elective  3  
Elective  3  
Elective  32  
Term Credit Hours  15  
Total Credit Hours:  123 
Code  Title  Credit Hours 

(F)  Fall only course  
(S)  Spring only course 