Curriculum Requirements
B.S. in Business Artificial Intelligence and Analytics
General Education
| Foundations | Credits: | |
| FCWR 101 | Writing I: Foundations of College Composition | 3 |
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Prerequisite: Prerequisite: WRIT 100 or Writing Placement Exam A course introducing students to the fundamentals of college composition. Topics include writing process, rhetorical strategies, basics of critical reading and thinking, analytical writing, and argumentative writing. This course serves as a foundation to prepare students to succeed in other academic writing contexts. Coursework includes a computer lab component. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
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| FCWR 151 | Writing II: Foundations of Research Writing | 3 |
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Prerequisite: Prerequisite: FCWR 101 or WRIT 101 Further development of the academic writing process, critical thinking, and analytical reading skills taught in FCWR 101. Focus on academic research planning, source evaluation skills, and audience awareness leading to a documented research paper. Specific attention to academic integrity in research writing. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
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| FCWR 301 | Communication for Business | 3 |
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Prerequisite: Prerequisite: Take one course in each group: Group 1 (FCWR 101 or FCWR 111 or WRIT 101 or WRIT 111) and Group 2 (FCWR 151 or FCWR 161 or WRIT 151 or WRIT 161) Building on courses taken in their majors, students will learn and apply concepts of effective written and oral communication appropriate for business careers. Focusing on communicating to specific audiences and developing an effective writing process, students will write in business formats such as memos, letters, reports, proposals, and resumes. Some assignments will include research and documentation. Students will deliver informative and persuasive oral presentations. Course work includes a computer lab component. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
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| Total: 9 Credits | ||
| Data Literacy | Credits: | |
| DATA 101 | Making Sense of a Data-Oriented Society | 3 |
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This course introduces students to the power of data as applied to real-life problems in today's data-driven world. Students will learn basic statistical concepts, how to identify reliable data, and to think critically about how to extract meaning from data. The course will discuss various biases, including social biases, how they affect data gathering and analysis, and how to address these biases. The course will also address ethical and moral issues associated with statistics, data collection and visualization, and data analysis. Students will learn how to present a narrative supported by data. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
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| Seminars (select courses from at least three of the four areas) | Credits: | |
| ICBS 3XX | Behavioral Science choice | 3 |
| Please view all course descriptions: http://www.nyit.edu/courses | ||
| ICLT 3XX | Literature choice | 3 |
| Please view all course descriptions: http://www.nyit.edu/courses | ||
| ICPH 3XX | Philosophy choice | 3 |
| Please view all course descriptions: http://www.nyit.edu/courses | ||
| ICSS 3XX | Social Science choice | 3 |
| Please view all course descriptions: http://www.nyit.edu/courses | ||
| Total: 12 Credits | ||
| Students must take four seminar courses from at least three different areas of study. | ||
| Math and Science Core | Credits: | |
| MATH 125 | Finite Mathematics | 3 |
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Prerequisite: Prerequisite: MATH 101 or Math Placement Exam. Review of elementary algebra and selected topics in statistics and probability. Sets, real numbers, graphing, linear and quadratic equations and inequalities, relations and functions, solving systems of linear equations, descriptive statistics, frequency distributions, graphical displays of data, measures of central tendency and dispersion, introduction to probability. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
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| Science choice | 3 | |
| Please view all course descriptions: http://www.nyit.edu/courses | ||
| Total: 6 Credits | ||
| Choose any course from PHYS, CHEM, or BIOL. | ||
Major Requirements
| Liberal Arts for Business | Credits: | |
| ECON 202 | Principles of Economics I | 3 |
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A study of basic economic concepts emphasizing analysis of the aggregate economy. The fundamental concepts of national income and its determination, economic fluctuations, monetary and fiscal policies, and economic growth are covered. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
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| ECON 204 | Principles of Economics II | 3 |
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An examination of the processes of price determination, output, and resource allocation in perfect and in imperfect competition. Also covers labor economics, international trade and finance, and alternative economic systems. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
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| QANT 201 | Statistical Sampling Theory | 3 |
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Prerequisite: Prerequisite: MATH 141 or MATH 151 or MATH 170. This course introduces students to both descriptive and inferential statistics. Coverage includes applications to business and other disciplines and the use of technology as a decision support tool. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
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| MATH 151 | Fundamentals of Calculus | 3 |
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Prerequisite: Prerequisite: MATH 125 or higher or Math Placement Exam. This course provides a comprehensive introduction to calculus and its applications in business and the applied sciences. Topics covered include functions, limits, continuity, derivatives, tangent lines, extrema, concavity, curve sketching, optimization, exponential and logarithmic functions, antiderivatives, definite integrals, and applications such as marginal analysis, business models, optimization of tax revenue, minimization of storage costs, finding areas, and concepts of probability extended to discrete and continuous sample spaces. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
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| —OR— | ||
| Please view all course descriptions: http://www.nyit.edu/courses | ||
| MATH 161 | Basic Applied Calculus | 3 |
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Prerequisite: Prerequisite: MATH 136 or higher or Math Placement Exam. This course provides a comprehensive introduction to calculus and its applications in business and the applied sciences. Topics covered include functions, limits, continuity, derivatives, tangent lines, extrema, concavity, curve sketching, optimization, exponential and logarithmic functions, antiderivatives, definite integrals, and applications such as marginal analysis, business models, optimization of tax revenue, minimization of storage costs, finding areas, and concepts of probability extended to discrete and continuous sample spaces. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
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| Total: 12 Credits | ||
| Business Core | Credits: | |
| ACCT 101 | Accounting I | 3 |
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A study of accounting fundamentals. Topics include the accounting cycle, statement preparation, systems, asset valuations, accounting concepts, and principles for the sole proprietorship. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
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| ACCT 110 | Managerial Accounting | 3 |
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Prerequisite: Prerequisite: ACCT 101 Special emphasis is placed on the collection and interpretation of data for managerial decision-making purposes. A study is made of cost concepts used in planning and control, cost- profit-volume analysis, and budgeting. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
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| FINC 201 | Corporation Finance | 3 |
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Prerequisite: Prerequisite: Take ACCT 101 or ECON 202 and one course in this group: MATH 125 or MATH 141 or MATH 151 or MATH 170. An overview of the financial management function in modern business, emphasizing the time value of money and financial analysis. The financial and economic environment and capital markets and securities are covered. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
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| MIST 216 | Information Systems | 3 |
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This course provides an introduction to information technology and application software. It also introduces students to how information is used in organizations and how information technology enables improvement in decision making at all managerial levels. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
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| MGMT 102 | Principles of Management | 3 |
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A study of organizations and of the activities of a manager in an organization. The course follows a functional approach, analyzing such management concepts as organizing decentralization, use of staff, human relations, conflict, decision-making, planning , supervision, communication, and financial and production control systems such as budgeting and PERT. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
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| MRKT 102 | Introduction to Marketing | 3 |
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Study of the process by which consumers' needs and wants are analyzed and satisfied within the context of a modern marketing system. Investigation of current developments in the external environment affecting the marketing process. The role of marketing institutions in facilitating the flow of goods and services from producers to consumers is analyzed. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
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| MGMT 235 | International Business | 3 |
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Techniques for analyzing and understanding the world of international business. Students will examine the challenges posed by the multinational firm and the dynamic nature of international business. Team projects will complement lectures. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
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| BUSI 450 | Business Analytics | 3 |
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Prerequisite: Prerequisites: MRKT 102, FINC 201, QANT 300 This course discusses applications of business analytics to strengthening decision-making ability in different business areas such as marketing, finance, operations, and strategic planning. This course provides students with an understanding of the emerging role of analytics in business disciplines. It shows how to use analytics tools in a spreadsheet environment to effectively utilize and interpret analytic models and results for better decisions making. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
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| Total: 24 Credits | ||
| Computer Science | Credits: | |
| CSCI 202 | Introduction to Computer Science and Artificial Intelligence | 3 |
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This course provides a comprehensive introduction to computer science, covering core concepts such as hardware systems, programming essentials, algorithms, data handling, and the basics of artificial intelligence. It is designed for both technical and non-technical majors interested in gaining a foundational understanding of computer science and AI. Through a blend of lectures, hands-on projects, and problem-solving exercises, students will acquire the skills and knowledge necessary to pursue further studies in computer science, engineering/technology programs, or a minor in Artificial Intelligence. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
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| Quantitative Analysis | Credits: | |
| QANT 300 | Production And Operations Management | 3 |
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Prerequisite: Prerequisite: QANT 201 Addresses activities required in the process of production of products and delivery of services. Background of concepts, processes and institutions in the production of goods and services will be covered. Computer applications are an integral part of this course. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
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| QANT 405 | Management Science | 3 |
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Prerequisite: Prerequisite: QANT 201 Quantitative techniques for managerial decision-making are covered. These techniques include linear and integer programming, nonlinear programming, decision analysis, queuing theory and simulation. Problems are modeled and then solved using computer software. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
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| Total: 6 Credits | ||
| AI And Analytics | Credits: | |
| BUSI 101 | Business AI And Analytics Orientation1 | 0 |
| Please view all course descriptions: http://www.nyit.edu/courses | ||
| BUSA 301 | Data Management And Visualization For AI | 3 |
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This course covers key aspects of data management, focusing on AI-powered data acquisition, preparation, and visualization. Students will learn how to leverage AI tools to collect data from diverse sources, including textual sources such as social media and company reports, and use AI-driven methods to clean data efficiently. The course also emphasizes using AI-enhanced visualization tools to create insightful representations that help stakeholders identify patterns and trends. Through hands-on projects, students will apply these tools to solve real-world business challenges. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
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| BUSA 305 | Python For Business Analytics | 3 |
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Prerequisite: Prerequisites: QANT 201 This course discusses applications of business analytics using Python to strengthen data-driven decision-making across various business functions. Students will explore AI-powered tools to enhance data mining, predictive analytics, and decision-making processes. Through practical projects, students will apply these techniques to real-world business challenges using AI-assisted solutions, for better decision-making. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
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| BUSA 310 | Database Systems and Big Data Management | 3 |
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This course provides an introduction to contemporary database management systems, with a focus on AI-enhanced database technologies. The students will learn current developments in database theory and practice. They will design, implement, and manage databases while using AI tools for query optimization, data modeling, and performance tuning. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
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| BUSA 315 | AI-Enhanced Business Analytics | 3 |
| Please view all course descriptions: http://www.nyit.edu/courses | ||
| BUSA 325 | Applied Statistical Modeling and Quantitative Analysis | 3 |
| Please view all course descriptions: http://www.nyit.edu/courses | ||
| FINC 422 | AI Applications In Financial Services | 3 |
| Please view all course descriptions: http://www.nyit.edu/courses | ||
| MGMT 450 | AI Strategy, Ethics and Business Implementation | 3 |
| Please view all course descriptions: http://www.nyit.edu/courses | ||
| MRKT 435 | Marketing AI And Analytics | 3 |
| Please view all course descriptions: http://www.nyit.edu/courses | ||
| Total: 24 Credits | ||
| [1] Pass/Fail grading | ||
| Internship or Practicum (choose one) | Credits: | |
| BUSA 425 | Collaborative AI Analytics Practicum | 3 |
| Please view all course descriptions: http://www.nyit.edu/courses | ||
| MGMTE 390 | Internship In Management | 3 |
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An advanced elective course which permits the student to apply theoretical knowledge in a real-world setting and gain supervised on-the-job experience. Term paper is required. Approval of the chairperson required. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 0-3-3 |
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| Total: 3 Credits | ||
| Capstone Project | Credits: | |
| BUSA 460 | Advanced AI and Analytics Capstone Project | 3 |
| Please view all course descriptions: http://www.nyit.edu/courses | ||
| Science Choice | Credits: | |
| Any PHYS, CHEM, or BIOL course | 3 | |
| Please view all course descriptions: http://www.nyit.edu/courses | ||
| Liberal Arts Electives | Credits: | |
| Choose electives with an academic advisor | 12 | |
| Please view all course descriptions: http://www.nyit.edu/courses | ||
| Total Required Credits = 120 |