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
215-204-8450
Dr. Gene Kwatny, Vice Chair
Science Education and Research Center, Room 304
215-204-8450
Dr. Anthony Hughes, Faculty Advisor
Science Education and Research Center, Room 344
215-204-7910
anthony.hughes@temple.edu
Department of Physics
Dr. James Napolitano, Chair
Science Education and Research Center, Room 406
215-204-1638
Dr. Bernd Surrow, Vice Chair
Science Education and Research Center, Room 420
215-204-1638
Dr. Matthew Newby, Faculty Advisor
Science Education and Research Center, Room 476
215-204-2642
matthew.newby@temple.edu
Bachelor of Science
Summary of Requirements for the Degree
- University Requirements (123 total s.h.)
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MATH 0701 (4 s.h.) and/or ENG 0701 (4 s.h.), if required by placement testing.
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All Temple students must take a minimum of two writing-intensive courses at Temple as part of their major: PHYS 2796 and CIS 4496.
- 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 typically receive a waiver for 2 Science & Technology (GS) and 1 Quantitative Literacy (GQ) GenEd courses.
- Students must satisfy general Temple University residency requirements.
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- College Requirements
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45 Upper Level (2000+) credits within the College of Science & Technology (CST) or the College of Liberal Arts (CLA).
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90 credits within the College of Science & Technology (CST) or the College of Liberal Arts (CLA).
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First Year Seminar Requirement: All students in the College of Science & Technology (CST) are required to take a 1 credit first year seminar course, SCTC 1001 CST First Year Seminar. Other courses that fulfill this requirement may be found on the CST College Requirements page. Only one course in this category may count towards graduation.
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- Major Requirements for Bachelor of Science (78-80 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: 3-4 Differential Equations with Linear Algebra Linear Algebra Linear Algebra with Computer Lab MATH 3043 Numerical Analysis I 3 to 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: 9 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 78-80
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 2020-2021 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 |
| General Education/Elective Credits | 6 | |
| Term Credit Hours | 15 | |
| Spring | ||
| CIS 1166 or 1966 | Mathematical Concepts in Computing I | 4 |
| MATH 1042 or 1942 | Calculus II | 4 |
| General Education/Elective Credits | 7 | |
| Term Credit Hours | 15 | |
| 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 |
| General Education/Elective Credits | 3 | |
| Term Credit Hours | 15.5 | |
| Year 3 | ||
| Fall | ||
| MATH 3031 | Probability Theory I | 3 |
| Select one of the following: | 3-4 | |
| Differential Equations with Linear Algebra (F) | ||
| Linear Algebra | ||
| Linear Algebra with Computer Lab (F) | ||
| PHYS 3511 | Scientific Computing II | 1.5 |
| General Education/Elective Credits | 7-6 | |
| Term Credit Hours | 14.5 | |
| Spring | ||
| MATH 3032 | Mathematical Statistics (S) | 3 |
| PHYS 2502 | Mathematical Physics (S) | 4 |
| PHYS 2796 | Introduction to Modern Physics [WI] (S) | 4 |
| General Education/Elective Credits | 5 | |
| Term Credit Hours | 16 | |
| Year 4 | ||
| Fall | ||
| MATH 3043 | Numerical Analysis I (F) | 3 to 4 |
| Data Science: Computation & Modeling Elective | 3 | |
| Data Science: Computation & Modeling Elective | 3 | |
| General Education/Elective Credits | 7-6 | |
| Term Credit Hours | 16 | |
| Spring | ||
| CIS 4496 | Projects in Data Science [WI] | 3 |
| Data Science: Computation & Modeling Elective | 3 | |
| General Education/Elective Credits | 9 | |
| Term Credit Hours | 15 | |
| Total Credit Hours: | 123 | |
| Code | Title | Credit Hours |
|---|---|---|
| (F) - Fall only course | ||
| (S) - Spring only course | ||