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Applied Mathematics, Bachelor of Science

 

(Students who plan to transfer a completed Associate's degree should review the Applied Mathematics Completion Degree information below.)

 

Program Philosophy and Objectives

While some math degree programs dive deeply into advanced mathematic theory, WilmU’s program prepares graduates for the workforce by focusing on solid foundational skills in mathematics, statistics, analysis and communication. Integrating curriculum taught by WilmU’s Mathematics, Business and Technology faculty—experts who apply these concepts in their own careers—this well-rounded STEM program uses project-based learning, coupled with co-ops/internships, to help students develop skills and apply their knowledge in context.

Concentrations

Choose from two concentrations, each with multiple embedded certificates.

Program Competencies

In addition to the University’s undergraduate graduation competencies (aligned with NACE* Career Readiness skills), students will demonstrate knowledge, skills, and abilities related to:

Core Program Competencies

  1. Analyze and solve complex, real-world problems using mathematical techniques and statistical methods.
  2. Use a variety of technologies to analyze quantitative problems and draw appropriate conclusions.
  3. Employ critical thinking strategies, such as quantitative, qualitative, and scientific reasoning, to analyze consequences and outcomes and determine logical solutions.
  4. Communicate methodologies and analyses effectively for diverse professional contexts.
  5. Employ ethical principles required of analysts and programmers.

Data Visualization Concentration Competencies

  1. Transform data into visual forms that clearly “tells a story” to the end-user.
  2. Use data and appropriate analytic techniques to select and create models to make predictions and inform decision-making.
  3. Demonstrate proficiency in the use of data visualization software to analyze problems.
  4. Develop fluency in the theory and best practices of using visual means to explore, draw insights from, and communicate the meaning of data.

Programming Concentration Competencies

  1. Apply computer science theory and software development fundamentals to produce computing-based solutions to contextual problems.
  2. Apply computer science best practices and current methodologies to create, deliver, and support information technology projects.
  3. Analyze requirements for computer hardware, network security, and software applications using best practices and methodologies.
  4. Write, modify, and test code for a variety of programming languages to solve contextual problems.

*National Association of Colleges and Employers. To learn more about career readiness, please visit:
https://www.naceweb.org/career-readiness/competencies/career-readiness-defined

Curriculum

The program design consists of four parts: 39 General Education requirements, 39 Applied Mathematics Core requirements, 33 Concentration requirements, and 9 elective credits. The General Education courses provide a well-rounded academic foundation. Students are strongly encouraged to use the elective courses to earn additional certificates.

General Education Requirements (39 credits)

A minimum passing grade of "C" is required for ENG 121, ENG 122, ENG 131, ENG 310, and MAT 205.

CTA 326 Integrating Excel into Business Problem Solving

ECO 101 Economics I

ENG 121 English Composition I

ENG 122 English Composition II

ENG 131 Public Speaking

ENG 310 Research Writing

HIS 381 Contemporary Global Issues

OR

POL 300 American Politics

MAT 205 Introductory Survey of Mathematics

PHI 100 Introduction to Critical Thinking

PSY 101 Introduction to Psychology

OR

SOC 101 Introduction to Sociology

Natural Science Elective

HUM Humanities Elective

HUM Humanities Elective


Applied Mathematics Core Requirements (39 credits)

A minimum passing grade of "C" is required for MAT 200, while a minimum grade of "C-" is required for MAT 312.

MAT 200 Pre-Calculus

MAT 310 Calculus I

MAT 311 Calculus II

MAT 315 Calculus III

MAT 322 Linear Algebra with Applications

MAT 320 Finite Mathematics

MAT 330 Discrete Math

MAT 312 Business Statistics

MAT 313 Experimental Design

CSC 402 Data Analysis Storytelling

CSC 414 Ethics for AI and Data Analytics

BBA 460 R for Business Analytics

MAT 490 Experiential Learning in Applied Mathematics

OR

MAT 491 Internship in Applied Mathematics


Concentration Requirements: Data Visualization (33 credits)

BBA 301 Intro to Business Analytics

BBA 305 Advanced Excel for Business Analytics

BBA 350 Predictive Analytics

BBA 360 Forecasting for Business Analytics

BBA 420 Data Mining

BBA 430 Data Visualization

BBA 450 Advanced Visualization

GIS 300 Geographic Information Systems Science & Technology

CSC 345 Database Foundations

CSC 407 Statistics for Data Analysis

CSC 419 Python for Data Science

Concentration Requirements: Programming (33 credits)

CSC 315 Fund. of O-O Programming

CSC 400 O-O Sys Anlys and Design

CSC 325 Java Programming I

AND

CSC 335 Java Programming II

OR

CSC 310 Microsoft .NET I

AND

CSC 311 Microsoft .NET II

CSC 340 JavaScript I

CSC 345 Database Foundations

CSC 407 Statistics for Data Analysis

CSC 419 Python for Data Science

CSC 420 Intro to Artificial Intelligence

CSC 430 Machine Learning Principles

ISM 420 Data Modeling and Warehousing

Applied Mathematics Bachelor of Science Completion Degree

What is a Completion Degree?

A completion degree is a personalized version of a bachelor's degree created exclusively for students who have completed an associate's degree at an accredited institution. (Students who have not completed an associate's degree should return to the full Interdisciplinary Studies, Bachelor of Science degree information, or the Interdisciplinary, Associate of Arts degree information.) Completion degrees are available for most Wilmington University Bachelor of Science degrees. A student who expects to transfer a completed associate's degree should communicate with a Wilmington University academic advisor before registering for courses. A transcript with documentation of the conferred degree must be received by Wilmington University to confirm eligibility.

Program Philosophy and Objectives

While some math degree programs dive deeply into advanced mathematic theory, WilmU’s program prepares graduates for the workforce by focusing on solid foundational skills in mathematics, statistics, analysis and communication. Integrating curriculum taught by WilmU’s Mathematics, Business and Technology faculty—experts who apply these concepts in their own careers—this well-rounded STEM program uses project-based learning, coupled with co-ops/internships, to help students develop skills and apply their knowledge in context.

Concentrations

Choose from two concentrations, each with multiple embedded certificates.

Program Competencies

In addition to the University’s undergraduate graduation competencies (aligned with NACE* Career Readiness skills), students will demonstrate knowledge, skills, and abilities related to:

Core Program Competencies

  1. Analyze and solve complex, real-world problems using mathematical techniques and statistical methods.
  2. Use a variety of technologies to analyze quantitative problems and draw appropriate conclusions.
  3. Employ critical thinking strategies, such as quantitative, qualitative, and scientific reasoning, to analyze consequences and outcomes and determine logical solutions.
  4. Communicate methodologies and analyses effectively for diverse professional contexts.
  5. Employ ethical principles required of analysts and programmers.

Data Visualization Concentration Competencies

  1. Transform data into visual forms that clearly “tells a story” to the end-user.
  2. Use data and appropriate analytic techniques to select and create models to make predictions and inform decision-making.
  3. Demonstrate proficiency in the use of data visualization software to analyze problems.
  4. Develop fluency in the theory and best practices of using visual means to explore, draw insights from, and communicate the meaning of data.

Programming Concentration Competencies

  1. Apply computer science theory and software development fundamentals to produce computing-based solutions to contextual problems.
  2. Apply computer science best practices and current methodologies to create, deliver, and support information technology projects.
  3. Analyze requirements for computer hardware, network security, and software applications using best practices and methodologies.
  4. Write, modify, and test code for a variety of programming languages to solve contextual problems.

*National Association of Colleges and Employers. To learn more about career readiness, please visit:
https://www.naceweb.org/career-readiness/competencies/career-readiness-defined

Applied Mathematics Bachelor of Science Completion Degree Pre-requirements for either Concentration

ENG 121 English Composition I

ENG 122 English Composition II

MAT 205 Introductory Survey of Mathematics

CTA 326 Integrating Excel into Business Problem Solving

MAT 200 Pre-Calculus

MAT 310 Calculus I

MAT 311 Calculus II

MAT 312 Business Statistics

Applied Mathematics Completion Version for Data Visualization (60 credits)

MAT 315 Calculus III

MAT 322 Linear Algebra with Applications

MAT 320 Finite Mathematics

MAT 330 Discrete Math

MAT 313 Experimental Design

CSC 402 Data Analysis Storytelling

CSC 414 Ethics for AI and Data Analytics

BBA 460 R for Business Analytics

MAT 490 Experiential Learning in Applied Mathematics

OR

MAT 491 Internship in Applied Mathematics

BBA 301 Intro to Business Analytics

BBA 305 Advanced Excel for Business Analytics

BBA 350 Predictive Analytics

BBA 360 Forecasting for Business Analytics

BBA 420 Data Mining

BBA 430 Data Visualization

BBA 450 Advanced Visualization

GIS 300 Geographic Information Systems Science & Technology

CSC 345 Database Foundations

CSC 407 Statistics for Data Analysis

CSC 419 Python for Data Science

Applied Mathematics Completion Version for Programming (60 credits)

MAT 315 Calculus III

MAT 322 Linear Algebra with Applications

MAT 320 Finite Mathematics

MAT 330 Discrete Math

MAT 313 Experimental Design

CSC 402 Data Analysis Storytelling

CSC 414 Ethics for AI and Data Analytics

BBA 460 R for Business Analytics

MAT 490 Experiential Learning in Applied Mathematics

OR

MAT 491 Internship in Applied Mathematics

CSC 315 Fund. of O-O Programming

CSC 400 O-O Sys Anlys and Design

CSC 325 Java Programming I

AND

CSC 335 Java Programming II

OR

CSC 310 Microsoft .NET I

AND

CSC 311 Microsoft .NET II

CSC 340 JavaScript I

CSC 345 Database Foundations

CSC 407 Statistics for Data Analysis

CSC 419 Python for Data Science

CSC 420 Intro to Artificial Intelligence

CSC 430 Machine Learning Principles

ISM 420 Data Modeling and Warehousing

This information applies to students who enter this degree program during the 2023-2024 Academic Year. If you entered this degree program before the Fall 2022 semester, please refer to the academic catalog for the year you began your degree program.