Business Analytics and Data Science, B.S.
The Bachelor of Science in Business Analytics and Data Science program will prepare students with the skills needed to gather, store, analyze and interpret large amounts of data in order to make business decisions. The program is designed to cater to the burgeoning need for analytics and data science professionals in various industries such as finance, marketing, retail and accounting.
The business analytics and data science bachelor’s program at NJCU reflects the university’s commitment to empower a diverse, underserved population and be an institution of higher education nimble in its response to dynamic 21st Century opportunities and challenges. The program also underscores the resolve of the NJCU School of Business to be a data-driven institution.
The program will be fully geared towards practice. Students learning experiences will be grounded in real world contexts. Students will learn analytical skills and use software tools that are currently popular in the industry, to find solutions to business data analysis problems that are commonly encountered in practice. Students will also learn the ethical responsibilities of working with large amounts of data, which in many cases could be private. Graduates of the program will be thoroughly prepared to take on the role of a data scientist in the industry.
The program will also prepare students to take the Certified Analytics Professional (CAP) certification.
Minimum Grade Requirements
- Students must earn a grade of C or higher in each School of Business course (ACCT, BUSI, ECON, FINC, MGMT, MKTG) used in fulfillment of a graduation requirement.
Total Credit Hours: 75
| Code | Title | Credits |
|---|---|---|
| Common Core Requirements (33 credits) | ||
| MGMT 225 | Business Enterprise Applications | 3 |
| MGMT 251 | Operations and Project Management Fundamentals | 3 |
| ECON 203 | Business Statistics | 3 |
| MGMT 211 | Principles of Management | 3 |
| MKTG 231 | Principles of Marketing | 3 |
| MGMT 241 | Global Business | 3 |
| ACCT 251 | Financial Accounting | 3 |
| ACCT 252 | Management Accounting (Pre-Requisite ACCT 251) | 3 |
| MGMT 235 | Business Law I: Legal Environment of Business | 3 |
| FINC 371 | Managerial Finance (Pre-Requisite ECON 208, ACCT 252, MATH 164) | 3 |
| MGMT 411 | Business Policy (Pre-Requisite FINC 371) | 3 |
| Specialization Requirements (24 credits) | ||
| FINC 305 | Introduction to Data Science | 3 |
| FINC 306 | Statistical and Mathematical Foundations for Business Analytics and Data Science | 3 |
| FINC 405 | Programming Basics for Business Analytics and Data Science | 3 |
| FINC 415 | Basics of Data Collection, Data Warehousing, and Data Cleansing | 3 |
| FINC 410 | Introduction to Forecasting Models and Experimental Design for Business Analytics and Data Science | 3 |
| FINC 403 | Fundamentals of Data Visualization for Business Analytics and Data Sciences | 3 |
| FINC 430 | Principles of Machine Learning | 3 |
| FINC 495 | Capstone in Data Science | 3 |
| Electives (18 credits) | ||
| Students may take electives as approved by the Department Advisor in general business, or across disciplines including but not limited to courses from Economics, Finance, Accounting, Marketing, Computer Science, Political Science, GeoScience, or group classes for a Minor or Specialization. | ||
| General Education Courses Required | ||
| MATH 164 | Pre-Calculus for Business Students | 4 |
| or ECON 221 | Analytics For Business and Economics | |
| ECON 207 | Principles of Economics:Macro | 3 |
| ECON 208 | Principles of Economics:Micro | 3 |
| Freshman | ||
|---|---|---|
| Semester 2 | Credits | |
| MATH 164 or ECON 221 | Pre-Calculus for Business Students or Analytics For Business and Economics | 3-4 |
| MGMT 211 | Principles of Management | 3 |
| Credits | 6-7 | |
| Sophomore | ||
| Semester 1 | ||
| MGMT 241 | Global Business | 3 |
| ECON 207 | Principles of Economics:Macro | 3 |
| MGMT 225 | Business Enterprise Applications | 3 |
| ACCT 251 | Financial Accounting | 3 |
| Credits | 12 | |
| Semester 2 | ||
| ECON 208 | Principles of Economics:Micro | 3 |
| ECON 203 | Business Statistics | 3 |
| ACCT 252 | Management Accounting | 3 |
| Credits | 9 | |
| Junior | ||
| Semester 1 | ||
| MGMT 251 | Operations and Project Management Fundamentals | 3 |
| MGMT 235 | Business Law I: Legal Environment of Business | 3 |
| FINC 305 | Introduction to Data Science | 3 |
| FINC 405 | Programming Basics for Business Analytics and Data Science | 3 |
| Credits | 12 | |
| Semester 2 | ||
| MKTG 231 | Principles of Marketing | 3 |
| FINC 371 | Managerial Finance | 3 |
| FINC 306 | Statistical and Mathematical Foundations for Business Analytics and Data Science | 3 |
| FINC 430 | Principles of Machine Learning | 3 |
| Major Elective or Minor Requirement | 3 | |
| Credits | 15 | |
| Senior | ||
| Semester 1 | ||
| FINC 410 | Introduction to Forecasting Models and Experimental Design for Business Analytics and Data Science | 3 |
| FINC 403 | Fundamentals of Data Visualization for Business Analytics and Data Sciences | 3 |
| FINC 415 | Basics of Data Collection, Data Warehousing, and Data Cleansing | 3 |
| Major Elective or Minor Requirement | 3 | |
| Major Elective or Minor Requirement | 3 | |
| Credits | 15 | |
| Semester 2 | ||
| FINC 495 | Capstone in Data Science | 3 |
| MGMT 411 | Business Policy | 3 |
| Major Elective or Minor Requirement | 3 | |
| Major Elective or Minor Requirement | 3 | |
| Major Elective or Minor Requirement | 3 | |
| Credits | 15 | |
| Total Credits | 84-85 | |
School of Business: Core Student Learning Outcomes
Students will demonstrate achievement of the following outcomes:
- Students will compose clear and concise forms of written communications to effectively convey ideas and information associated with business topics.
- Students will communicate business concepts effectively through oral presentations.
- Students will identify ethical issues and understand the implications of social responsibility for sustainable business practices.
- Students will evaluate information and apply critical thinking skills to identify solutions and inform business decisions.
- Students will utilize technology, apply quantitative methods, and interpret data to solve business problems.
- Students will be able to integrate knowledge of core business concepts and collaborate productively as part of a team.
- Students will work effectively in a diverse environment and understand how global and cultural issues affect the organization and its stakeholders.
Discipline Specific Student Learning Outcomes
Students will demonstrate achievement of the following outcomes:
- Demonstrate the ability to collect, clean, manage, and store data
- Demonstrate the ability to combine and describe diverse datasets and interpret results to understand business problems.
- Apply various data analytic techniques and the principles of machine learning to solve business problems and make informed business decisions.