Major in Data Science
The Bachelor of Science in Data Science degree aims to produce graduates who can combine business expertise, quantitative reasoning, and computer software skills to extract meaningful insights from data. These skills prepare students to interpret business data in the 21st century, to compete in the marketplace with combined business and data science skills, and to apply these insights to answer business questions and solve business problems.
Program graduates are expected to be able to
- Demonstrate knowledge about business functions and processes.
- Collect, clean, prepare, and maintain data from different sources with relevant technologies.
- Analyze data using popular statistical tools and programming skills and generate reports.
- Visualize data using Power BI, Tableau, and Microsoft Excel and communicate the results effectively to address business questions and make recommendations.
- Understand the role of data governance and the ethical use of data in data science.
- Demonstrate knowledge about enterprise systems.
The program will focus on the following eight student learning outcomes:
- Written Communication
- Oral Communication
- Critical Thinking
- Quantitative Literacy
- Information Literacy
- Teamwork
- Ethical Reasoning
- Reflective Practice
More information on major requirements can be found below in the Program Requirements section.
Where can a data science degree take you?
BS in Data Science graduates can apply for positions such as Data Scientist, Business Analyst, Business Intelligence Engineer, Operations Research Analyst, etc. Most of the data science related job descriptions have mentioned following preferred qualifications:
- Knowledge of data analysis and statistical modeling techniques. [These techniques will be taught in Data and Text Mining (DSCI 355) and Time Series Modeling & Forecasting (DSCI 375) classes.]
- Knowledge of machine learning driven algorithms to improve systems. [These machine learning algorithms will be taught in Machine Learning (DSCI 420) class.]
- Knowledge of Tableau, AWS QuickSight, Power BI, or other data visualizations software. [Students will learn these visualization tools in Data Visualization (DSCI 351) class.]
- Knowledge of Excel, Python, R, Access, SQL, Perl, or other scripting languages. [These programming languages will be taught in Data Science Programming (DSCI 310), Small System Software (MISY 341), and Database Management Principles (MISY 360) classes. Students need to complete their class projects using these programming languages. They will be familiar with how to develop Data-driven decision models using both Python and R programming languages.]
- Knowledge of prediction techniques to improve forecast accuracy. [These forecasting techniques will be taught in Time Series Modeling & Forecasting (DSCI 375) class.]
- Knowledge of processing large-scale complex datasets and making optimal decisions using optimization techniques. [Optimization techniques for large-scale datasets will be taught in Data-driven Decision Making (DSCI 490) class.]
- Knowledge of optimization programming languages and commercial solvers. [Students will learn popular optimization languages, such as AMPL, GAMS and commercial solver, such as CPLEX, in Data-driven Decision Making (DSCI 490) class.]
Data Science graduates typically work in one of the following positions: Data Scientist, Data Analyst, Business Intelligence Analyst, Operations Research Analyst, and Data Engineer. National average annual salary for the above mentioned five positions from Year 2012 to 2021 is shown in the following Figure (data source: zippia)
Year | Business Intelligence Analyst | Data Analyst | Data Scientist | Operations Research Analyst | Data Engineer |
|---|---|---|---|---|---|
2012 | $63,600 | $61,100 | $82,400 | $62,400 | $83,600 |
2013 | $64,300 | $63,400 | $83,300 | $63,200 | $84,500 |
2014 | $65,500 | $63,700 | $83,600 | $64,000 | $86,000 |
2015 | $66,600 | $63,800 | $84,600 | $64,200 | $86,700 |
2016 | $67,600 | $64,800 | $88,000 | $66,400 | $89,200 |
2017 | $68,400 | $65,600 | $89,700 | $68,200 | $92,000 |
2018 | $69,900 | $66,000 | $91,500 | $70,000 | $94,600 |
2019 | $71,000 | $66,000 | $92,500 | $70,500 | $96,400 |
2020 | $72,600 | $66,900 | $94,800 | $72,400 | $98,000 |
2021 | $74,100 | $67,900 | $98,000 | $74,200 | $99,800 |
Data Source: Zippia
Program Requirements
To graduate with a Bachelor of Science degree in Data Science, students must complete 120 credit hours. These credit hours are split among:
- General Education Requirements, or GERs (40 credits)
- College of Business Core Requirements (42 credits)
- Data Science Core Courses (27 credits)
- Data Science Elective (3 credits)
- Free Electives (7 credits)
- Coppin-Specific Requirements (1 credit)
General Education Requirements (GERs) (40 credits)
Students must complete 40 GER credits. Specifically for data science majors, your program plan should include:
- ECON 103, Introduction to Business & Entrepreneurial Economics, to satisfy the Social and Behavioral Sciences category of GER
- MATH 131, College Algebra for Mathematics and Science Majors, to satisfy the Mathematics category of GER
- MISY 150, Technology Fluency, to satisfy the Interdisciplinary and Emerging Issues-Local to Global category of GER
College of Business Requirements (42 credits)
Students must complete following 42 credits of College of Business core requirements:
| Course | Credits | Name |
|---|---|---|
| ACCT 201 | 3 | Principles of Financial Accounting |
| ACCT 202 | 3 | Principles of Managerial Accounting |
| BDSC 322 | 3 | Business Statistics |
| BDSC 340 | 3 | Operations and Production Management |
| BUSI 310 | 3 | Business Law |
| BUSI 320 | 3 | International Business |
| BUSI 495 | 3 | Seminar in Business Strategy and Policy |
| ECON 211 | 3 | Principles of Economics I |
| ECON 212 | 3 | Principles of Economics II |
| FINM 330 | 3 | Principles of Business Finance |
| MGMT 305 | 3 | Business Communications |
| MGMT 320 | 3 | Principles of Management |
| MISY 341 | 3 | Small Systems Software |
| MKTG 310 | 3 | Principles of Marketing |
Data Science Core Courses (27 credits)
Students must complete following 27 Data Science core credits:
| Course | Credits | Name |
|---|---|---|
| DSCI 201 | 3 | Introduction to Data Science |
| DSCI 310 | 3 | Data Science Programming |
| DSCI 351 | 3 | Data Visualization |
| DSCI 355 | 3 | Data and Text Mining |
| DSCI 356 | 3 | Data Science Cloud Computing |
| MISY 360 | 3 | Database Management Principles |
| DSCI 375 | 3 | Time Series Modeling and Forecasting |
| DSCI 420 | 3 | Machine Learning |
| DSCI 490 | 3 | Data-driven Decision Making |
Data Science Elective (3 credits)
Students need to select one of the following courses as the Data Science elective requirement:
- DSCI 450 Special Topics in Data Science
- DSCI 485 Internship in Data Science
Free Electives (7 credits)
Students are recommended to take COSC 199 Introduction to Computer Programming and/or any other computer science/mathematics/management information systems courses, but other college level courses are acceptable too.
Coppin Specific Requirements (1 credit)
- FRSEM 101 Freshman Seminar
Transfer students transferring 25 or more credits are exempt from this FRSEM 101 course.
Sample Course Plan
Be sure to connect with your academic advisor to plan your semester courses. The plan below is just an example—your journey may have different requirements.
Fall Semester (16 Credits)
| Course | Credits | Name |
| ENGL 101 or 101E | 3 | English Composition I |
| MATH 131 | 3 | College Algebra |
| PHIL 102 | 3 | Introduction to Logic |
| HIST 201, 203, or 205 | 3 | History I |
| MISY 150 | 3 | Technology Fluency |
| FRSEM 101 | 1 | Freshman Seminar |
Spring Semester (15 Credits)
| Course | Credits | Name |
| ENGL 102 | 3 | English Composition II |
| HIST 202, 204, or 206 | 3 | History II |
| PHSC 101 or 103 | 3 | Physical Science |
| SPCH 105 | 3 | Introduction to Speech Communication |
| ECON 103 | 3 | Introduction to Business & Entrepreneurial Economics |
Fall Semester (15 Credits)
| Course | Credits | Name |
| Arts & Humanities | 3 | ART 103, MUSC 201, DANC 226, THEA 211, IDIS 102/103, or Foreign Language 101 |
| PSYC 201 | 3 | General Psychology |
| ACCT 201 | 3 | Principle of Financial Accounting |
| ECON 211 | 3 | Principles of Economics I |
| DSCI 201 | 3 | Introduction to Data Science |
Spring Semester (16 Credits)
| Course | Credits | Name |
| ECON 212 | 3 | Principles of Economics II |
| BIOL 101 | 4 | Biology |
| ACCT 202 | 3 | Principles of Managerial Accounting |
| BDSC 322 | 3 | Business Statistics |
| FINM 330 | 3 | Principles of Business Finance |
Fall Semester (15 Credits)
| Course | Credits | Name |
| MKTG 310 | 3 | Principles of Marketing |
| BDSC 340 | 3 | Operations Management |
| DSCI 310 | 3 | Data Science Programming |
| DSCI 351 | 3 | Data Visualization |
| MISY 341 | 3 | Small Systems Software |
Spring Semester (15 Credits)
| Course | Credits | Name |
| BUSI 310 | 3 | Business Law |
| BUSI 320 | 3 | Fundamentals of International Business |
| MGMT 320 | 3 | Principles of Management |
| DSCI 355 | 3 | Data and Text Mining |
| ELECTIVE (Reading 101 or general elective) | 3 | COSC 199 Introduction to Computer Programming (Recommended) |
Fall Semester (15 Credits)
| Course | Credits | Name |
| MGMT 305 | 3 | Business Communication |
| DSCI 356 | 3 | Data Science Cloud Computing |
| DSCI 375 | 3 | Time Series Modeling & Forecasting |
| DSCI 420 | 3 | Machine Learning |
| ELECTIVE | 3 | Any COSC, MATH, or MISY course (recommended) |
Spring Semester (13 Credits)
| Course | Credits | Name |
| MISY 360 | 3 | Database Management Principles |
| Data Science Elective | 3 | DSCI 450 Special Topics or DSCI 485 Internship |
| DSCI 490 | 3 | Data-driven Decision Making |
| BUSI 495 | 3 | Seminar in Business Strategy & Policy |
| ELECTIVE | 1 | Open Elective |
| Exit Exam |
The data science major lives in the Department of Accounting, Data Science and Management Information Systems within the College of Business.