## Overview

Science and technology are the foundations of our future. The Department of Computer and Information Sciences (CIS) is focused on the understanding of fundamental scientific principles and the application of these principles to solving complex problems, using computing technology.

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. The **Bachelor of Science in Data Science** is designed for students interested in developing expertise in data science.

Data Science students **must select one of the following concentrations**:

- Computation and Modeling
- Computational Analytics
- Genomics and Bioinformatics

The **Concentration in Computational Analytics** provides a strong background in mathematics, algorithmic and computational thinking, computer systems, and data analysis, and will enable students to analyze large quantities of data to discover new knowledge and facilitate decision making.

**Campus Location:** Main

**Program Code:** ST-DTSC-BS

### Distinction in Major

To graduate with distinction in this major, a student must satisfy the following criteria:

- have a minimum 3.50 major GPA and
- have a minimum 3.50 cumulative GPA.

### Accelerated Programs

Accelerated programs provide a pathway for students to pursue both an undergraduate degree and an advanced degree in a shorter amount of time. Below is a list of available accelerated programs for students in the BS in Data Science.

### Undergraduate Contact Information

Jamie Payton, Chair

Science Education and Research Center, Room 304

215-204-8450

Gene Kwatny, Vice Chair

Science Education and Research Center, Room 304

215-204-8450

Andrew Rosen, Faculty Advisor

Science Education and Research Center, Room 349

215-204-3193

andrew.rosen@temple.edu

*These requirements are for students who matriculated in academic year 2024-2025. Students who matriculated prior to fall 2024 should refer to the Archives to view the requirements for their Bulletin year.*

## Bachelor of Science Requirements

### Summary of Requirements for the Degree

- University Requirements (123 total s.h.)
- Students must complete all University requirements including those listed below.
- All undergraduate students must complete at least two writing-intensive courses for a total of at least six credits at Temple as part of their major. The specific writing-intensive course options for this major are:
Course List Code Title Credit Hours CIS 3296 Software Design 3-4 or ENG 2696 Technical Writing 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.

- See the General Education section of the
- Students must satisfy general Temple University residency requirements.

- College Requirements
- A minimum of 90 total credits within the College of Science & Technology (CST), the College of Liberal Arts (CLA), and/or the College of Engineering (ENG).
- A minimum of 45 of these credits must be upper-level (courses numbered 2000 and above).

- Complete a one-credit first-year or transfer seminar.

- A minimum of 90 total credits within the College of Science & Technology (CST), the College of Liberal Arts (CLA), and/or the College of Engineering (ENG).
- Major Requirements for Bachelor of Science (81-86 s.h.)

At least 9 courses required for the major must be completed at Temple. At least 6 CIS courses must be completed at Temple.Course List Code Title Credit Hours Introductory Science Requirements Must select either the Chemistry sequence or the Physics sequence 8 General Chemistry I

and General Chemistry II

and General Chemistry Laboratory I

and General Chemistry Laboratory IIHonors General Chemical Science I

and Honors General Chemical Science II

and Honors Chemical Science Laboratory I

and Honors Chemical Science Laboratory IIElementary 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 2107 Computer Systems and Low-Level Programming 4 CIS 3223 Data Structures and Algorithms 3 CIS 4331 Principles of Database Systems 4 CIS 4517 Data-Intensive and Cloud Computing 3 CIS 4526 Foundations of Machine Learning 3 Select one of the following: 3-4 Software Design ^{1}Technical Writing 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 Computational Analytics Elective Requirements Select from the following list: 9-12 Biomedical Signals and Systems Probability, Statistics & Stochastic Methods Environmental Engineering Intelligent Transportation Systems Life Cycle Assessment and Carbon Footprinting Introduction to Artificial Intelligence Introduction to Systems Programming and Operating Systems Computer Graphics and Image Processing Cooperative Education Experience in Computer Science ^{2}Introduction to Mobile Application Development Introduction to Digital Forensics Independent Study ^{2}Independent Study ^{2}Knowledge Discovery and Data Mining or CIS 5523Knowledge Discovery and Data Mining Analysis and Modeling of Social and Information Networks Remote Sensing and GIS Introduction to Health Services Systems Numerical Analysis I Numerical Analysis II Probability Theory II Applied Mathematics Digital Marketing (need permission to register) Customer Data Analytics (need permission to register) Survey Design and Sampling Design of Experiments and Quality Control Time Series and Forecasting Models Nonparametric and Categorical Data Analysis Total Credit Hours 81-86

## Suggested Academic Plan

### Bachelor of Science in Data Science with Concentration in Computational Analytics

#### Suggested Plan for New Students Starting in the 2024-2025 Academic Year

Year 1 | ||
---|---|---|

Fall | Credit Hours | |

CIS 1068 or CIS 1968 | Program Design and Abstraction or Honors Program Design and Abstraction | 4 |

MATH 1041 or MATH 1941 | Calculus I or Honors Calculus I | 4 |

SCTC 1001 | CST First Year Seminar | 1 |

ENG 0802 | Analytical Reading and Writing [GW] or Analytical Reading and Writing: ESL [GW] or Honors Analytical Reading and Writing [GW] | 4 |

GenEd Breadth Course | 3 | |

Credit Hours | 16 | |

Spring | ||

CIS 1166 or CIS 1966 | Mathematical Concepts in Computing I or Honors Mathematical Concepts in Computing I | 4 |

MATH 1042 or MATH 1942 | Calculus II or Honors Calculus II | 4 |

IH 0851 or IH 0951 | Intellectual Heritage I: The Good Life [GY] or Honors Intellectual Heritage I: The Good Life [GY] | 3 |

GenEd Breadth Course | 3 | |

Credit Hours | 14 | |

Year 2 | ||

Fall | ||

CIS 2166 | Mathematical Concepts in Computing II | 4 |

CIS 2168 | Data Structures | 4 |

MATH 2043 or MATH 2943 | Calculus III or Honors Calculus III | 4 |

Select one of the following Chemistry or Physics sequences: | 4 | |

General Chemistry I and General Chemistry Laboratory I | ||

Honors General Chemical Science I and Honors Chemical Science Laboratory I | ||

Elementary Classical Physics I | ||

Honors Elementary Classical Physics I | ||

General Physics I | ||

Honors General Physics I | ||

Credit Hours | 16 | |

Spring | ||

CIS 2107 | Computer Systems and Low-Level Programming | 4 |

CIS 3223 | Data Structures and Algorithms | 3 |

CIS 3715 | Principles of Data Science (S) | 4 |

Select one of the following. Note: Must be continuation of the Chemistry or Physics course taken in prior semester: | 4 | |

General Chemistry II and General Chemistry Laboratory II | ||

Honors General Chemical Science II and Honors Chemical Science Laboratory II | ||

Elementary Classical Physics II | ||

Honors Elementary Classical Physics II | ||

General Physics II | ||

Honors General Physics II | ||

Credit Hours | 15 | |

Year 3 | ||

Fall | ||

CIS 4331 | Principles of Database Systems | 4 |

MATH 3031 | Probability Theory I | 3 |

Select one of the following: | 3-4 | |

Differential Equations with Linear Algebra | ||

Linear Algebra | ||

Linear Algebra with Computer Lab (F) | ||

IH 0852 or IH 0952 | Intellectual Heritage II: The Common Good [GZ] or Honors Intellectual Heritage II: The Common Good [GZ] | 3 |

Elective | 3-2 | |

Credit Hours | 16 | |

Spring | ||

CIS 4517 | Data-Intensive and Cloud Computing (S) | 3 |

MATH 3032 | Mathematical Statistics (S) | 3 |

GenEd Breadth Course | 3-4 | |

GenEd Breadth Course | 3 | |

Elective | 3 | |

Elective | 1-0 | |

Credit Hours | 16 | |

Year 4 | ||

Fall | ||

CIS 4526 | Foundations of Machine Learning (F) | 3 |

Data Science: Computational Analytics Elective | 3-4 | |

Data Science: Computational Analytics Elective | 3-4 | |

GenEd Breadth Course | 3 | |

Elective | 3-1 | |

Credit Hours | 15 | |

Spring | ||

CIS 4496 | Projects in Data Science [WI] | 3 |

Select one of the following: | 3-4 | |

Software Design [WI] ^{1} | ||

Technical Writing [WI] | ||

Data Science: Computational Analytics Elective | 3-4 | |

Elective | 3 | |

Elective | 3-1 | |

Credit Hours | 15 | |

Total Credit Hours | 123 |

Code | Title | Credit Hours |
---|---|---|

(F) - Fall only course | ||

(S) - Spring only course |

## Accelerated Programs

Students may opt to pursue an accelerated +1 program, enabling them to complete both a bachelor's degree and master's degree in less time than the traditional route.

The following accelerated programs may be of interest to students in the Data Science BS with Computational Analytics Concentration:

**College of Science and Technology**