Program Overview

Data Science BSDS

The Bachelor of Science in Data Science (BSDS) prepares students to meet the challenges presented by the explosive growth of very large scale and complex data sources. The availability of data from sources such as business activities, social media, and scientific instruments constantly creates new problems requiring data-driven solutions and opportunities and problems for innovation. BS in Data Science students develop the knowledge and skill to address these opportunities for the benefit of individuals and organizations. Students in the degree complete a minor, typically in business or the sciences, to provide knowledge and skill in a specific subject area to which data science techniques can be applied.

About the Program

Data Science students learn to:

• Define domain-specific and context-relevant data analytics questions and hypotheses for individuals and organizations
• Select relevant data sources and transform data suitable for solving data analytics problems
• Identify appropriate techniques and tools for acquiring, retrieving, analyzing, and making use of the data
• Apply data analytics techniques and skills to build analytical and predictive models for answering data science questions
• Create visualizations and communicate data analytics results to stakeholders and decision-makers
• Assess the necessary skills arising from the interdisciplinary nature of data science as a combination of hacking skills, analytical techniques, and domain knowledge

The degrees in Computing and Security Technology, Data Science, and Information Systems share a common first year. This allows students to easily switch among the degrees early in their studies. In addition, some of the electives in each degree are accessible to students in the other two majors; this provides a deeper and broader set of advanced topics for students in all three majors.

Degree Requirements

• University and College Requirements:
  • CIVC 101: Introduction to Civic Engagement (1.0)
  • COOP 101: Career Management and Professional Development (1.0)
  • UNIV CI101: The Drexel Experience (2.0)
  • or CI 120: CCI Transfer Student Seminar
• Data Science Requirements:
  • DSCI 351: Recommender Systems (3.0)
  • DSCI 471: Applied Deep Learning (3.0)
  • INFO 101: Introduction to Computing and Security Technology (3.0)
  • INFO 102: Introduction to Information Systems (3.0)
  • INFO 103: Introduction to Data Science (3.0)
  • INFO 202: Data Curation (3.0)
  • INFO 210: Database Management Systems (3.0)
  • or CS 461: Database Systems
  • INFO 212: Data Science Programming I (3.0)
  • INFO 213: Data Science Programming II (3.0)
  • INFO 215: Social Aspects of Information Systems (3.0)
  • INFO 250: Information Visualization (3.0)
  • INFO 323: Cloud Computing and Big Data (3.0)
  • INFO 332: Exploratory Data Analytics (3.0)
  • INFO 432: Advanced Data Analytics (3.0)
  • INFO 440: Social Media Data Analysis (3.0)
  • INFO 442: Data Science Projects (3.0)
• CCI Electives: Select 2 courses from the list below that are 200-499 and not otherwise required (6.0)
  • Any CI (Computing and Informatics) course
  • Any CS (Computer Science) course
  • Any CT (Computing Technology) course
  • Any DSCI (Data Science) course
  • Any INFO (Information Science & Systems) course
  • Any SE (Software Engineering) course
• Data Science Electives (6.0-7.0): Select 2 of the following courses
  • CS 260: Data Structures
  • CS 270: Mathematical Foundations of Computer Science
  • CS 380: Artificial Intelligence
  • CS 383: Machine Learning
  • INFO 200: Systems Analysis I
  • INFO 300: Information Retrieval Systems
  • INFO 315: Advanced Database Management Systems
  • INFO 355: Systems Analysis II
  • INFO 420: Software Project Management
• Computing and Informatics Requirements:
  • CI 101: Computing and Informatics Design I (2.0)
  • CI 102: Computing and Informatics Design II (2.0)
  • CI 103: Computing and Informatics Design III (2.0)
  • CI 491 [WI]: Senior Project I (3.0)
  • CI 492 [WI]: Senior Project II (3.0)
  • CI 493 [WI]: Senior Project III (3.0)
• Introductory Programming:
  • CS 171: Computer Programming I (3.0)
  • CS 172: Computer Programming II (3.0)
  • CS 265: Advanced Programming Tools and Techniques (3.0)
• Mathematics Requirements:
  • MATH 121: Calculus I (4.0)
  • MATH 122: Calculus II (4.0)
  • MATH 180: Discrete Computational Structures (4.0)
  • MATH 201: Linear Algebra (4.0)
• Statistics Requirements:
  • STAT 201: Introduction to Business Statistics (4.0)
  • STAT 202: Business Statistics II (4.0)
• Natural Science Requirements: Select courses in the following subject at the 100-499 level (8.0)
  • Any BIO (Bioscience & Biotechnology) course
  • Any CHEM (Chemistry) course
  • Any ENVS (Environmental Science) course
  • Any FDSC (Food Science) course
  • Any HSCI (Health Sciences) course
  • Any NFS (Nutrition, Foods & Health) course
  • Any PHEV (Physics-Environmental Science) course
  • Any PHYS (Physics) course
• Arts and Humanities Requirements:
  • ENGL 101: Composition and Rhetoric I: Inquiry and Exploratory Research (3.0)
  • or ENGL 111: English Composition I
  • ENGL 102: Composition and Rhetoric II: Advanced Research and Evidence-Based Writing (3.0)
  • or ENGL 112: English Composition II
  • ENGL 103: Composition and Rhetoric III: Themes and Genres (3.0)
  • or ENGL 113: English Composition III
  • COM 230: Techniques of Speaking (3.0)
  • or COM 310: Technical Communication
• Arts & Humanities, Business, or Social Studies electives: Select courses in the 100-499 level from the list below (6.0)
  • Any ACCT (Accounting) course
  • Any ARBC (Arabic) course
  • Any ARCH (Architecture) course
  • Any ARTH (Art History) course
  • Any BLAW (Legal Studies) course
  • Any BUSN (General Business) course
  • Any CHIN (Chinese) course
  • Any CJS (Criminology and Justice Studies) course
  • Any CMGT (Construction Management) course
  • Any COM (Communication) course
  • Any CULA (Culinary Arts) course
  • Any DANC (Dance) course
  • Any ECON (Economics) course
  • Any EDEX (Special Education) course
  • Any EDUC (Teacher Education) course
  • Any ENGL (English) course
  • Any ENTP (Entrepreneurship and Innovation) course
  • Any ESTM (STEM Teacher Education) course
  • Any FASH (Fashion) course
  • Any FIN (Finance) course
  • Any FMTV (Film & Television Production) course
  • Any FREN (French) course
  • Any GER (German) course
  • Any GST (Global Studies) course
  • Any HBRW (Hebrew) course
  • Any HRMT (Human Resource Management) course
  • Any INTB (International Business) course
  • Any INTR (Interior Design) course
  • Any ITAL (Italian) course
  • Any JAPN (Japanese) course
  • Any KOR (Korean) course
  • Any LAW (Law) course
  • Any LING (Linguistics) course
  • Any MGMT (Management) course
  • Any MIS (Management Information Systems) course
  • Any MKTG (Marketing) course
  • Any MUSC (Music) course
  • Any OPM (Operations Management) course
  • Any ORGB (Organizational Behavior) course
  • Any OPR (Operations Research) course
  • Any PHIL (Philosophy) course
  • Any PHTO (Photo) course
  • Any SPAN (Spanish) course
  • Any STAT (Business Statistics) course
  • Any TAX (Taxation) course
  • Any THTR (Theatre) course
  • Any VSCM (Graphic Design) course
  • Any VSST (Visual Studies) course
  • Any WRIT (Writing) course
  • GMAP 260: Overview of Computer Gaming
  • ANIM 140: Computer Graphics Imagery I
  • ANIM 141: Computer Graphics Imagery II
  • ANIM 211: Animation I
  • ANIM 212: Animation II
• Minor Requirements: Choose a minor in a data science application area including business and natural science (24.0)
• Free Electives (21.0)
• Total Credits (183.0-184.0)

Sample Plan of Study

5-year, 3 co-op

• First Year:
  • Fall: CI 101 (2.0), ENGL 101 or 111 (3.0), INFO 101 (3.0), MATH 121 (4.0), UNIV CI101 (1.0), Arts, Humanities, Business, Social Studies Electives (3.0)
  • Winter: CI 102 (2.0), CIVC 101 (1.0), COOP 101 (1.0), CS 171 (3.0), ENGL 102 or 112 (3.0), INFO 102 (3.0), MATH 122 (4.0)
  • Spring: CI 103 (2.0), CS 172 (3.0), ENGL 103 or 113 (3.0), INFO 103 (3.0), MATH 180 (4.0), UNIV CI101 (1.0)
• Second Year:
  • Fall: COOP EXPERIENCE
  • Winter: COOP EXPERIENCE
  • Spring: INFO 202 (3.0), INFO 210 or CS 461 (3.0), INFO 212 (3.0), STAT 201 (4.0)
  • Summer: CS 265 (3.0)
• Third Year:
  • Fall: COOP EXPERIENCE
  • Winter: COOP EXPERIENCE
  • Spring: COM 230 or 310 (3.0), INFO 213 (3.0), INFO 323 (3.0), INFO 440 (3.0), Arts, Humanities, Business, Social Studies Electives (3.0), Data Science Elective (3.0)
  • Summer: DSCI 351 (3.0)
• Fourth Year:
  • Fall: COOP EXPERIENCE
  • Winter: COOP EXPERIENCE
  • Spring: DSCI 471 (3.0), INFO 432 (3.0), INFO 442 (3.0), CCI Elective (3.0), Minor Electives (6.0)
• Fifth Year:
  • Fall: CI 491 (3.0), Free Electives (3.0), Minor Electives (6.0)
  • Winter: CI 492 (3.0), CCI Elective (3.0), Free Electives (6.0)
  • Spring: CI 493 (3.0), Free Electives (6.0), Minor Electives (6.0)

4-year, 1 co-op

• First Year:
  • Fall: CI 101 (2.0), ENGL 101 or 111 (3.0), INFO 101 (3.0), MATH 121 (4.0), UNIV CI101 (1.0), Arts, Humanities, Business, Social Studies Electives (3.0)
  • Winter: CI 102 (2.0), CIVC 101 (1.0), CS 171 (3.0), ENGL 102 or 112 (3.0), INFO 102 (3.0), MATH 122 (4.0)
  • Spring: CI 103 (2.0), CS 172 (3.0), ENGL 103 or 113 (3.0), INFO 103 (3.0), MATH 180 (4.0), UNIV CI101 (1.0)
• Second Year:
  • Fall: CS 265 (3.0), COOP 101 (1.0), INFO 202 (3.0), INFO 210 or CS 461 (3.0), INFO 212 (3.0), STAT 201 (4.0)
  • Winter: INFO 215 (3.0), INFO 250 (3.0), MATH 201 (4.0), STAT 202 (4.0)
  • Spring: COM 230 or 310 (3.0), INFO 213 (3.0), INFO 323 (3.0), Free Elective (3.0), Science Elective (4.0)
  • Summer: DSCI 351 (3.0), INFO 440 (3.0), Arts, Humanities, Business, Social Studies Electives (3.0), Data Science Elective (3.0)
• Third Year:
  • Fall: COOP EXPERIENCE
  • Winter: COOP EXPERIENCE
  • Spring: DSCI 471 (3.0), INFO 432 (3.0), INFO 442 (3.0), CCI Elective (3.0), Minor Electives (6.0)
• Fourth Year:
  • Fall: CI 491 (3.0), Free Electives (3.0), Minor Electives (6.0)
  • Winter: CI 492 (3.0), CCI Elective (3.0), Free Electives (6.0)
  • Spring: CI 493 (3.0), Free Electives (6.0), Minor Electives (6.0)

Co-op/Career Opportunities

Co-Op Options

Two co-op options are available for this program:

• Five-year/three co-op
• Four-year/one co-op

Career Opportunities

The Data Science major provides valuable skills that can be transported to a number of job settings. The demand for graduates with data science knowledge is strong, and employers often want evidence of additional communication and problem-solving skills that can be applicable to specific disciplines. Data Science program graduates could potentially serve as key members of organizational data science teams able to create novel information products, with an emphasis on solving problems that can only be addressed using large and disparate data sources. The program is also an excellent preparation for graduate study in data science.

Sample job titles for data science graduates include:

• Data Scientist
• Business Intelligence Officer
• Information Architect
• Usability Analyst

Program Level Outcomes

The College of Computing & Informatics works continually to improve its degree programs. As part of this effort, the Data Science degree is evaluated relative to the following Objectives and Outcomes.

BS Data Science Program Educational Objectives

Within three to five years of graduation, alumni of the program are expected to achieve one or more of the following milestones:

• Be valued contributors to private or public organizations as demonstrated by promotions, increased responsibility, or other professional recognition
• Contribute to professional knowledge as demonstrated by published papers, technical reports, patents, or conference presentations
• Succeed in continuing professional development as demonstrated by completion of graduate studies or professional certifications
• Display commitment and leadership within the professional and community as demonstrated by contributions towards society's greater good and prosperity

BS Data Science Program Student Outcomes

The program enables students to attain by the time of graduation:

• An ability to apply knowledge of computing and mathematics appropriate to the discipline
• An ability to analyze a problem, and identify and define the computing requirements appropriate to its solution
• An ability to design, implement, and evaluate a computer-based system, process, component, or program to meet desired needs
• An ability to function effectively on teams to accomplish a common goal
• An understanding of professional, ethical, legal, security, and social issues
• An ability to communicate effectively with a range of audiences
• An ability to analyze the local and global impact of computing on individuals, organizations, and society
• Recognition of the need for and an ability to engage in continuing professional development
• An ability to use current techniques, skills, and tools necessary for computing practice