Decoration Graphic

The “4+1” Program

Graceland undergraduates majoring in Data Science and those undergraduates that will have completed an Analytics Track by graduation may take up to 15 semester hours in the Master of Science in Data Science and Analytics program and count these as credit toward their BS degree and credit toward their MS degree. Note that all applicants must also have completed the course requirements, GPA requirement, and letter of recommendation requirement of the Twenty-Two month program. Completion of DSCI5300, DSCI5320, and DSCI5330 as undergraduates will allow students the opportunity to finish the Master Degree within 16 months or less after graduation from the BS program.

  • BS Degree — Data Science Major

    In addition to the general education requirements, majors in Data Science must complete 35 semester hours of coursework as described below:

    *General Education Requirement

    Courses Offered
    • CSIT1100Principles of Computing
      CSIT1100 Principles of Computing - 3 s.h.

      An introduction to the fundamentals of computer programming through extensive practice developing software in the Python language. Fundamental terminology and topics such as integrated development environments, variables, data types, control structures, functions, and objects will be covered. ELO4 Global Learning - Innovation

    • CSIT1200Data Structures
      CSIT1200 Data Structures - 3 s.h.

      Continuation of CSIT1100 with emphasis on more advanced programming that involve classic data structures such as arrays, dictionaries, linked lists, queues, stacks, and trees. Recursive techniques and efficiency considerations will also be covered. Prerequisite: CSIT1100.

    • CSIT3300Database Concepts and SQL
      CSIT3300 Database Concepts and SQL - 3 s.h.

      A study of the concepts and structures required to implement a database system including the logical design and physical organization of the database. Emphasis is given to the design and development of database systems that includes understanding and applying entity-relationship models. Implementation of a database using SQL on a database system is included. Prerequisite: CSIT1100.

    • CSIT4200Machine Learning
      CSIT4200 Machine Learning - 3 s.h.

      A study of regression, kernels, support vector machines, clustering, Neural networks. Prerequisites: MATH3340, MATH2510, CSIT1200. (Students participating in the 4+1 Masters program in Data Science and Analytics should sign up for DSCI5370 Machine Learning.)

    • DSCI1500Beginning Data Science and Data Analytics
      DSCI1500 Beginning Data Science and Data Analytics - 3 s.h.

      Introduction to the basic methods of analysis in Data Science and Data Analytics. This course introduces students to the basic statistical methods, coding applications, problem solving, and data integrity issues common to the field.

    • DSCI4320Practical Applications of Data Science
      DSCI4320 Practical Applications of Data Science - 3 s.h.

      Exploratory data analysis is introduced along with fundamental considerations for data analysis on real data sets. Classical models and techniques for classification are included. Methods of data visualization are introduced. Prerequisites: CSIT4200 (Students participating in the 4+1 Masters program in Data Science and Analytics should sign up for DSCI5320 Practical Application of Data Science.)

    • MATH1370Statistics for Sciences
      MATH1370 Statistics for Sciences - 3 s.h.

      Data analysis and measures of central tendency, dispersion, and correlation. Introduction to probability. Estimation and hypothesis testing. Bivariate regression. ANOVA. Introduction to nonparametric techniques. ELO6 Math, GE2B Foundational Skills-Mathematics/Quantitative.

    • MATH1510Calculus I
      MATH1510 Calculus I - 4 s.h.

      Limits, continuity, differentiation, and applications including exponential, logarithmic, trigonometric, and inverse functions. Mean value theorem, curve sketching, Riemann sums, and the fundamental theorem of calculus. Prerequisite: 2 years high school algebra. ELO6 Math, GE2B Foundational Skills-Mathematics/Quantitative.

    • MATH1520Calculus II
      MATH1520 Calculus II - 4 s.h.

      Integration techniques and applications, polar coordinates, improper integrals, sequences and series of real numbers, and power series. Prerequisite: MATH1510.

    • MATH2350Discrete Mathematics
      MATH2350 Discrete Mathematics - 3 s.h.

      A survey of topics in discrete mathematics focusing on introductory logic, methods of mathematical proof, set theory, determinants and matrices, combinatorics, and graph theory. Prerequisite: Instructor approval for non-CSIT/MATH majors, 2 years high school algebra or MATH1280. ELO6 Math, GE2B Foundational Skills-Mathematics/Quantitative.

    • MATH2510Calculus III
      MATH2510 Calculus III - 4 s.h.

      Conic sections, vectors in space, functions of several variables, partial differentiation, multiple integration, line integrals, and Green’s Theorem. Prerequisite: MATH1520.

    • MATH3340Linear Algebra
      MATH3340 Linear Algebra - 3 s.h.

      Matrices, vector spaces, linear transformations. Prerequisite: MATH1510 and MATH2350. +This course is only offered every other year.

    • MATH4350Probability and Advanced Statistics
      MATH4350 Probability and Advanced Statistics - 3 s.h.

      Introduction to probability, classical probability models and processes, random variables, conditional probability, bivariate distributions and their development, goodness of fit tests, and other nonparametric methods. Prerequisite: MATH1520 and MATH2350. +This course is only offered every other year. (Students participating in the 4+1 Masters program in Data Science and Analytics should sign up for DSCI5340 Probability and Statistical Inference.)

    CSIT1100Principles of Computing CSIT1200Data Structures CSIT3300Database Concepts and SQL CSIT4200Machine Learning DSCI1500Beginning Data Science and Data Analytics DSCI4320Practical Applications of Data Science MATH1370Statistics for Sciences MATH1510Calculus I MATH1520Calculus II MATH2350Discrete Mathematics MATH2510Calculus III MATH3340Linear Algebra MATH4350Probability and Advanced Statistics
    Course Descriptions
    CSIT1100 Principles of Computing - 3 s.h.

    An introduction to the fundamentals of computer programming through extensive practice developing software in the Python language. Fundamental terminology and topics such as integrated development environments, variables, data types, control structures, functions, and objects will be covered. ELO4 Global Learning - Innovation

    CSIT1200 Data Structures - 3 s.h.

    Continuation of CSIT1100 with emphasis on more advanced programming that involve classic data structures such as arrays, dictionaries, linked lists, queues, stacks, and trees. Recursive techniques and efficiency considerations will also be covered. Prerequisite: CSIT1100.

    CSIT3300 Database Concepts and SQL - 3 s.h.

    A study of the concepts and structures required to implement a database system including the logical design and physical organization of the database. Emphasis is given to the design and development of database systems that includes understanding and applying entity-relationship models. Implementation of a database using SQL on a database system is included. Prerequisite: CSIT1100.

    CSIT4200 Machine Learning - 3 s.h.

    A study of regression, kernels, support vector machines, clustering, Neural networks. Prerequisites: MATH3340, MATH2510, CSIT1200. (Students participating in the 4+1 Masters program in Data Science and Analytics should sign up for DSCI5370 Machine Learning.)

    DSCI1500 Beginning Data Science and Data Analytics - 3 s.h.

    Introduction to the basic methods of analysis in Data Science and Data Analytics. This course introduces students to the basic statistical methods, coding applications, problem solving, and data integrity issues common to the field.

    DSCI4320 Practical Applications of Data Science - 3 s.h.

    Exploratory data analysis is introduced along with fundamental considerations for data analysis on real data sets. Classical models and techniques for classification are included. Methods of data visualization are introduced. Prerequisites: CSIT4200 (Students participating in the 4+1 Masters program in Data Science and Analytics should sign up for DSCI5320 Practical Application of Data Science.)

    MATH1370 Statistics for Sciences - 3 s.h.

    Data analysis and measures of central tendency, dispersion, and correlation. Introduction to probability. Estimation and hypothesis testing. Bivariate regression. ANOVA. Introduction to nonparametric techniques. ELO6 Math, GE2B Foundational Skills-Mathematics/Quantitative.

    MATH1510 Calculus I - 4 s.h.

    Limits, continuity, differentiation, and applications including exponential, logarithmic, trigonometric, and inverse functions. Mean value theorem, curve sketching, Riemann sums, and the fundamental theorem of calculus. Prerequisite: 2 years high school algebra. ELO6 Math, GE2B Foundational Skills-Mathematics/Quantitative.

    MATH1520 Calculus II - 4 s.h.

    Integration techniques and applications, polar coordinates, improper integrals, sequences and series of real numbers, and power series. Prerequisite: MATH1510.

    MATH2350 Discrete Mathematics - 3 s.h.

    A survey of topics in discrete mathematics focusing on introductory logic, methods of mathematical proof, set theory, determinants and matrices, combinatorics, and graph theory. Prerequisite: Instructor approval for non-CSIT/MATH majors, 2 years high school algebra or MATH1280. ELO6 Math, GE2B Foundational Skills-Mathematics/Quantitative.

    MATH2510 Calculus III - 4 s.h.

    Conic sections, vectors in space, functions of several variables, partial differentiation, multiple integration, line integrals, and Green’s Theorem. Prerequisite: MATH1520.

    MATH3340 Linear Algebra - 3 s.h.

    Matrices, vector spaces, linear transformations. Prerequisite: MATH1510 and MATH2350. +This course is only offered every other year.

    MATH4350 Probability and Advanced Statistics - 3 s.h.

    Introduction to probability, classical probability models and processes, random variables, conditional probability, bivariate distributions and their development, goodness of fit tests, and other nonparametric methods. Prerequisite: MATH1520 and MATH2350. +This course is only offered every other year. (Students participating in the 4+1 Masters program in Data Science and Analytics should sign up for DSCI5340 Probability and Statistical Inference.)

  • Data Science Minor

    A minor in Data Science requires 20 semester hours as described below:

    Courses Offered
    • CSIT1100Principles of Computing
      CSIT1100 Principles of Computing - 3 s.h.

      An introduction to the fundamentals of computer programming through extensive practice developing software in the Python language. Fundamental terminology and topics such as integrated development environments, variables, data types, control structures, functions, and objects will be covered. ELO4 Global Learning - Innovation

    • CSIT1200Data Structures
      CSIT1200 Data Structures - 3 s.h.

      Continuation of CSIT1100 with emphasis on more advanced programming that involve classic data structures such as arrays, dictionaries, linked lists, queues, stacks, and trees. Recursive techniques and efficiency considerations will also be covered. Prerequisite: CSIT1100.

    • DSCI1500Beginning Data Science and Data Analytics
      DSCI1500 Beginning Data Science and Data Analytics - 3 s.h.

      Introduction to the basic methods of analysis in Data Science and Data Analytics. This course introduces students to the basic statistical methods, coding applications, problem solving, and data integrity issues common to the field.

    • MATH1370Statistics for Sciences
      MATH1370 Statistics for Sciences - 3 s.h.

      Data analysis and measures of central tendency, dispersion, and correlation. Introduction to probability. Estimation and hypothesis testing. Bivariate regression. ANOVA. Introduction to nonparametric techniques. ELO6 Math, GE2B Foundational Skills-Mathematics/Quantitative.

    • MATH1510Calculus I
      MATH1510 Calculus I - 4 s.h.

      Limits, continuity, differentiation, and applications including exponential, logarithmic, trigonometric, and inverse functions. Mean value theorem, curve sketching, Riemann sums, and the fundamental theorem of calculus. Prerequisite: 2 years high school algebra. ELO6 Math, GE2B Foundational Skills-Mathematics/Quantitative.

    • MATH1520Calculus II
      MATH1520 Calculus II - 4 s.h.

      Integration techniques and applications, polar coordinates, improper integrals, sequences and series of real numbers, and power series. Prerequisite: MATH1510.

    CSIT1100Principles of Computing CSIT1200Data Structures DSCI1500Beginning Data Science and Data Analytics MATH1370Statistics for Sciences MATH1510Calculus I MATH1520Calculus II
    Course Descriptions
    CSIT1100 Principles of Computing - 3 s.h.

    An introduction to the fundamentals of computer programming through extensive practice developing software in the Python language. Fundamental terminology and topics such as integrated development environments, variables, data types, control structures, functions, and objects will be covered. ELO4 Global Learning - Innovation

    CSIT1200 Data Structures - 3 s.h.

    Continuation of CSIT1100 with emphasis on more advanced programming that involve classic data structures such as arrays, dictionaries, linked lists, queues, stacks, and trees. Recursive techniques and efficiency considerations will also be covered. Prerequisite: CSIT1100.

    DSCI1500 Beginning Data Science and Data Analytics - 3 s.h.

    Introduction to the basic methods of analysis in Data Science and Data Analytics. This course introduces students to the basic statistical methods, coding applications, problem solving, and data integrity issues common to the field.

    MATH1370 Statistics for Sciences - 3 s.h.

    Data analysis and measures of central tendency, dispersion, and correlation. Introduction to probability. Estimation and hypothesis testing. Bivariate regression. ANOVA. Introduction to nonparametric techniques. ELO6 Math, GE2B Foundational Skills-Mathematics/Quantitative.

    MATH1510 Calculus I - 4 s.h.

    Limits, continuity, differentiation, and applications including exponential, logarithmic, trigonometric, and inverse functions. Mean value theorem, curve sketching, Riemann sums, and the fundamental theorem of calculus. Prerequisite: 2 years high school algebra. ELO6 Math, GE2B Foundational Skills-Mathematics/Quantitative.

    MATH1520 Calculus II - 4 s.h.

    Integration techniques and applications, polar coordinates, improper integrals, sequences and series of real numbers, and power series. Prerequisite: MATH1510.

  • Data Analytics for Accounting Certificate

    Students wishing to earn the Data Analytics for Accounting certificate must complete the following 18 credit hours with Graceland University.

    Courses Offered
    • ACCT2310Financial Accounting
      ACCT2310 Financial Accounting - 3 s.h.

      An introduction to the study of accounting dealing with the preparation and analysis of the balance sheet, income statement, and related accounting records. Prerequisites: One MATH course.

    • ACCT2320Managerial Accounting
      ACCT2320 Managerial Accounting - 3 s.h.

      The selection and analysis of accounting information for internal use by management. Prerequisite: ACCT2310.

    • ACCT4100Auditing Concepts and Applications – A Risk Analysis Approach
      ACCT4100 Auditing Concepts and Applications – A Risk Analysis Approach - 3 s.h.

      An introduction to the study of auditing principles and standards. Provides a working knowledge of auditing procedures. Prerequisite: ACCT3360.

    • CSIT1100Principles of Computing
      CSIT1100 Principles of Computing - 3 s.h.

      An introduction to the fundamentals of computer programming through extensive practice developing software in the Python language. Fundamental terminology and topics such as integrated development environments, variables, data types, control structures, functions, and objects will be covered. ELO4 Global Learning - Innovation

    • DSCI1500Beginning Data Science and Data Analytics
      DSCI1500 Beginning Data Science and Data Analytics - 3 s.h.

      Introduction to the basic methods of analysis in Data Science and Data Analytics. This course introduces students to the basic statistical methods, coding applications, problem solving, and data integrity issues common to the field.

    • DSCI4700Capstone for Data Analytics Certificates
      DSCI4700 Capstone for Data Analytics Certificates - 3 s.h.

      The course covers the basic aspects of a complete data analytics project. Students will use data sets obtained from community partners. Students will work in teams with each team producing a problem definition in conjunction with the client, conducting the proposed analysis directed at providing insight into the problem, and disseminating the results of the analysis in written and oral form.

    ACCT2310Financial Accounting ACCT2320Managerial Accounting ACCT4100Auditing Concepts and Applications – A Risk Analysis Approach CSIT1100Principles of Computing DSCI1500Beginning Data Science and Data Analytics DSCI4700Capstone for Data Analytics Certificates
    Course Descriptions
    ACCT2310 Financial Accounting - 3 s.h.

    An introduction to the study of accounting dealing with the preparation and analysis of the balance sheet, income statement, and related accounting records. Prerequisites: One MATH course.

    ACCT2320 Managerial Accounting - 3 s.h.

    The selection and analysis of accounting information for internal use by management. Prerequisite: ACCT2310.

    ACCT4100 Auditing Concepts and Applications – A Risk Analysis Approach - 3 s.h.

    An introduction to the study of auditing principles and standards. Provides a working knowledge of auditing procedures. Prerequisite: ACCT3360.

    CSIT1100 Principles of Computing - 3 s.h.

    An introduction to the fundamentals of computer programming through extensive practice developing software in the Python language. Fundamental terminology and topics such as integrated development environments, variables, data types, control structures, functions, and objects will be covered. ELO4 Global Learning - Innovation

    DSCI1500 Beginning Data Science and Data Analytics - 3 s.h.

    Introduction to the basic methods of analysis in Data Science and Data Analytics. This course introduces students to the basic statistical methods, coding applications, problem solving, and data integrity issues common to the field.

    DSCI4700 Capstone for Data Analytics Certificates - 3 s.h.

    The course covers the basic aspects of a complete data analytics project. Students will use data sets obtained from community partners. Students will work in teams with each team producing a problem definition in conjunction with the client, conducting the proposed analysis directed at providing insight into the problem, and disseminating the results of the analysis in written and oral form.

  • Data Analytics for Agricultural Business Certificate

    Students wishing to earn the Data Analytics for Agricultural Business certificate must complete the following 18 credit hours with Graceland University.

    Courses Offered
    • ACCT3220Agricultural Accounting and Taxation
      ACCT3220 Agricultural Accounting and Taxation - 3 s.h.

      Exposure to accounting methods and taxation policies specific to agricultural producers and businesses. Prerequisite: ACCT2310 Financial Accounting.

    • AGRI3100Agricultural Finance and Resource Allocation
      AGRI3100 Agricultural Finance and Resource Allocation - 3 s.h.

      Application of economics and financial resource allocation to agricultural businesses from producer to distributor to the end consumer. Content includes equity and credit practices for operations and for capital investments. Prerequisite: ECON1320 Microeconomics.

    • CSIT1100Principles of Computing
      CSIT1100 Principles of Computing - 3 s.h.

      An introduction to the fundamentals of computer programming through extensive practice developing software in the Python language. Fundamental terminology and topics such as integrated development environments, variables, data types, control structures, functions, and objects will be covered. ELO4 Global Learning - Innovation

    • DSCI1500Beginning Data Science and Data Analytics
      DSCI1500 Beginning Data Science and Data Analytics - 3 s.h.

      Introduction to the basic methods of analysis in Data Science and Data Analytics. This course introduces students to the basic statistical methods, coding applications, problem solving, and data integrity issues common to the field.

    • DSCI4700Capstone for Data Analytics Certificates
      DSCI4700 Capstone for Data Analytics Certificates - 3 s.h.

      The course covers the basic aspects of a complete data analytics project. Students will use data sets obtained from community partners. Students will work in teams with each team producing a problem definition in conjunction with the client, conducting the proposed analysis directed at providing insight into the problem, and disseminating the results of the analysis in written and oral form.

    • ECON2100Introductory Economic Data Analysis
      ECON2100 Introductory Economic Data Analysis - 3 s.h.

      An introduction to economic data and statistical techniques commonly applied in business settings. Topics include understanding the basics of data interpretation, manipulation, and visualization. Students will learn how to carry out and interpret basic linear regression and other methods of statistical analysis in Excel.

    ACCT3220Agricultural Accounting and Taxation AGRI3100Agricultural Finance and Resource Allocation CSIT1100Principles of Computing DSCI1500Beginning Data Science and Data Analytics DSCI4700Capstone for Data Analytics Certificates ECON2100Introductory Economic Data Analysis
    Course Descriptions
    ACCT3220 Agricultural Accounting and Taxation - 3 s.h.

    Exposure to accounting methods and taxation policies specific to agricultural producers and businesses. Prerequisite: ACCT2310 Financial Accounting.

    AGRI3100 Agricultural Finance and Resource Allocation - 3 s.h.

    Application of economics and financial resource allocation to agricultural businesses from producer to distributor to the end consumer. Content includes equity and credit practices for operations and for capital investments. Prerequisite: ECON1320 Microeconomics.

    CSIT1100 Principles of Computing - 3 s.h.

    An introduction to the fundamentals of computer programming through extensive practice developing software in the Python language. Fundamental terminology and topics such as integrated development environments, variables, data types, control structures, functions, and objects will be covered. ELO4 Global Learning - Innovation

    DSCI1500 Beginning Data Science and Data Analytics - 3 s.h.

    Introduction to the basic methods of analysis in Data Science and Data Analytics. This course introduces students to the basic statistical methods, coding applications, problem solving, and data integrity issues common to the field.

    DSCI4700 Capstone for Data Analytics Certificates - 3 s.h.

    The course covers the basic aspects of a complete data analytics project. Students will use data sets obtained from community partners. Students will work in teams with each team producing a problem definition in conjunction with the client, conducting the proposed analysis directed at providing insight into the problem, and disseminating the results of the analysis in written and oral form.

    ECON2100 Introductory Economic Data Analysis - 3 s.h.

    An introduction to economic data and statistical techniques commonly applied in business settings. Topics include understanding the basics of data interpretation, manipulation, and visualization. Students will learn how to carry out and interpret basic linear regression and other methods of statistical analysis in Excel.

  • Data Analytics for Business Management Certificate

    Students wishing to earn the Data Analytics for Business Management certificate must complete the following 18 credit hours with Graceland University.

    Courses Offered
    • BUAD3320Principles of Management
      BUAD3320 Principles of Management - 3 s.h.

      Fundamentals of planning, organizing, directing, coordinating, and controlling business activity. Prerequisites: Junior standing.

    • BUAD3450Organizational Behavior
      BUAD3450 Organizational Behavior - 3 s.h.

      Human aspects of business organization, as distinguished from economic and technical aspects, and how they influence efficiency, morale, and management practice. Offered Fall even years. +This course is only offered every other year.

    • CSIT1100Principles of Computing
      CSIT1100 Principles of Computing - 3 s.h.

      An introduction to the fundamentals of computer programming through extensive practice developing software in the Python language. Fundamental terminology and topics such as integrated development environments, variables, data types, control structures, functions, and objects will be covered. ELO4 Global Learning - Innovation

    • DSCI1500Beginning Data Science and Data Analytics
      DSCI1500 Beginning Data Science and Data Analytics - 3 s.h.

      Introduction to the basic methods of analysis in Data Science and Data Analytics. This course introduces students to the basic statistical methods, coding applications, problem solving, and data integrity issues common to the field.

    • DSCI4700Capstone for Data Analytics Certificates
      DSCI4700 Capstone for Data Analytics Certificates - 3 s.h.

      The course covers the basic aspects of a complete data analytics project. Students will use data sets obtained from community partners. Students will work in teams with each team producing a problem definition in conjunction with the client, conducting the proposed analysis directed at providing insight into the problem, and disseminating the results of the analysis in written and oral form.

    • ECON2100Introductory Economic Data Analysis
      ECON2100 Introductory Economic Data Analysis - 3 s.h.

      An introduction to economic data and statistical techniques commonly applied in business settings. Topics include understanding the basics of data interpretation, manipulation, and visualization. Students will learn how to carry out and interpret basic linear regression and other methods of statistical analysis in Excel.

    BUAD3320Principles of Management BUAD3450Organizational Behavior CSIT1100Principles of Computing DSCI1500Beginning Data Science and Data Analytics DSCI4700Capstone for Data Analytics Certificates ECON2100Introductory Economic Data Analysis
    Course Descriptions
    BUAD3320 Principles of Management - 3 s.h.

    Fundamentals of planning, organizing, directing, coordinating, and controlling business activity. Prerequisites: Junior standing.

    BUAD3450 Organizational Behavior - 3 s.h.

    Human aspects of business organization, as distinguished from economic and technical aspects, and how they influence efficiency, morale, and management practice. Offered Fall even years. +This course is only offered every other year.

    CSIT1100 Principles of Computing - 3 s.h.

    An introduction to the fundamentals of computer programming through extensive practice developing software in the Python language. Fundamental terminology and topics such as integrated development environments, variables, data types, control structures, functions, and objects will be covered. ELO4 Global Learning - Innovation

    DSCI1500 Beginning Data Science and Data Analytics - 3 s.h.

    Introduction to the basic methods of analysis in Data Science and Data Analytics. This course introduces students to the basic statistical methods, coding applications, problem solving, and data integrity issues common to the field.

    DSCI4700 Capstone for Data Analytics Certificates - 3 s.h.

    The course covers the basic aspects of a complete data analytics project. Students will use data sets obtained from community partners. Students will work in teams with each team producing a problem definition in conjunction with the client, conducting the proposed analysis directed at providing insight into the problem, and disseminating the results of the analysis in written and oral form.

    ECON2100 Introductory Economic Data Analysis - 3 s.h.

    An introduction to economic data and statistical techniques commonly applied in business settings. Topics include understanding the basics of data interpretation, manipulation, and visualization. Students will learn how to carry out and interpret basic linear regression and other methods of statistical analysis in Excel.

  • Data Analytics for Business Marketing Certificate

    Students wishing to earn the Data Analytics for Marketing certificate must complete the following 18 credit hours with Graceland University.

    Courses Offered
    • BUAD3240Marketing Research and Analytics
      BUAD3240 Marketing Research and Analytics - 3 s.h.

      A focus on the practice of studying and managing marketing metrics data in order to enhance decision making for marketing efforts including calls-to-action (CTAs), blog posts, channel performance, and thought leadership pieces, and to identify opportunities for improvement and maximize marketing outcomes. Students will learn how marketing analytics professionals serve as liaisons between those who make marketing decisions and those who work with the data.

    • BUAD3480International Marketing & Advertising
      BUAD3480 International Marketing & Advertising - 3 s.h.

      The aim of the course is to give the students a deeper understanding of marketing on a global basis. The students examine the international similarities and differences in marketing functions as related to the cultural, economic, political, social, and physical dimensions of the environment. This course is designed to provide students with an applied understanding of international marketing activities based on real-life examples.

    • BUAD4460Strategic Marketing
      BUAD4460 Strategic Marketing - 3 s.h.

      This course is designed to equip students with the knowledge and skills to develop, implement, and evaluate strategic marketing initiatives in various business contexts. This course explores the fundamental principles, theories, and practices of strategic marketing, emphasizing its critical role in achieving a competitive advantage in today's dynamic and global business environment. Prerequisites: BUAD2330 and BUAD3240.

    • CSIT1100Principles of Computing
      CSIT1100 Principles of Computing - 3 s.h.

      An introduction to the fundamentals of computer programming through extensive practice developing software in the Python language. Fundamental terminology and topics such as integrated development environments, variables, data types, control structures, functions, and objects will be covered. ELO4 Global Learning - Innovation

    • DSCI1500Beginning Data Science and Data Analytics
      DSCI1500 Beginning Data Science and Data Analytics - 3 s.h.

      Introduction to the basic methods of analysis in Data Science and Data Analytics. This course introduces students to the basic statistical methods, coding applications, problem solving, and data integrity issues common to the field.

    • DSCI4700Capstone for Data Analytics Certificates
      DSCI4700 Capstone for Data Analytics Certificates - 3 s.h.

      The course covers the basic aspects of a complete data analytics project. Students will use data sets obtained from community partners. Students will work in teams with each team producing a problem definition in conjunction with the client, conducting the proposed analysis directed at providing insight into the problem, and disseminating the results of the analysis in written and oral form.

    BUAD3240Marketing Research and Analytics BUAD3480International Marketing & Advertising BUAD4460Strategic Marketing CSIT1100Principles of Computing DSCI1500Beginning Data Science and Data Analytics DSCI4700Capstone for Data Analytics Certificates
    Course Descriptions
    BUAD3240 Marketing Research and Analytics - 3 s.h.

    A focus on the practice of studying and managing marketing metrics data in order to enhance decision making for marketing efforts including calls-to-action (CTAs), blog posts, channel performance, and thought leadership pieces, and to identify opportunities for improvement and maximize marketing outcomes. Students will learn how marketing analytics professionals serve as liaisons between those who make marketing decisions and those who work with the data.

    BUAD3480 International Marketing & Advertising - 3 s.h.

    The aim of the course is to give the students a deeper understanding of marketing on a global basis. The students examine the international similarities and differences in marketing functions as related to the cultural, economic, political, social, and physical dimensions of the environment. This course is designed to provide students with an applied understanding of international marketing activities based on real-life examples.

    BUAD4460 Strategic Marketing - 3 s.h.

    This course is designed to equip students with the knowledge and skills to develop, implement, and evaluate strategic marketing initiatives in various business contexts. This course explores the fundamental principles, theories, and practices of strategic marketing, emphasizing its critical role in achieving a competitive advantage in today's dynamic and global business environment. Prerequisites: BUAD2330 and BUAD3240.

    CSIT1100 Principles of Computing - 3 s.h.

    An introduction to the fundamentals of computer programming through extensive practice developing software in the Python language. Fundamental terminology and topics such as integrated development environments, variables, data types, control structures, functions, and objects will be covered. ELO4 Global Learning - Innovation

    DSCI1500 Beginning Data Science and Data Analytics - 3 s.h.

    Introduction to the basic methods of analysis in Data Science and Data Analytics. This course introduces students to the basic statistical methods, coding applications, problem solving, and data integrity issues common to the field.

    DSCI4700 Capstone for Data Analytics Certificates - 3 s.h.

    The course covers the basic aspects of a complete data analytics project. Students will use data sets obtained from community partners. Students will work in teams with each team producing a problem definition in conjunction with the client, conducting the proposed analysis directed at providing insight into the problem, and disseminating the results of the analysis in written and oral form.

  • Data Analytics for Chemistry Certificate

    Students wishing to earn the Data Analytics for Chemistry certificate must complete the following 21 credit hours with Graceland University.

    Courses Offered
    • CHEM3300Analytical Chemistry with Lab
      CHEM3300 Analytical Chemistry with Lab - 4 s.h.

      Study of theory and practice of modern separation and analytical techniques. Includes use of electrochemical, spectrometric and chromatographic instruments. Additional fee required. Prerequisite: CHEM1420. Offered odd years Spring.

    • CHEM3610Physical Chemistry I with Lab
      CHEM3610 Physical Chemistry I with Lab - 4 s.h.

      A study of thermodynamics, thermochemistry, chemical kinetics, equilibrium, atomic and molecular structure, electrochemistry, and quantum chemistry. Additional fee required. Prerequisites: CHEM1420, PHYS1420, and MATH1520. Offered odd years Fall. +This course is only offered every other year.

    • CHEM3620Physical Chemistry II with Lab
      CHEM3620 Physical Chemistry II with Lab - 4 s.h.

      Additional fee required. Continuation of CHEM3610, which is a prerequisite. Offered even years Spring. +This course is only offered every other year.

    • CSIT1100Principles of Computing
      CSIT1100 Principles of Computing - 3 s.h.

      An introduction to the fundamentals of computer programming through extensive practice developing software in the Python language. Fundamental terminology and topics such as integrated development environments, variables, data types, control structures, functions, and objects will be covered. ELO4 Global Learning - Innovation

    • DSCI1500Beginning Data Science and Data Analytics
      DSCI1500 Beginning Data Science and Data Analytics - 3 s.h.

      Introduction to the basic methods of analysis in Data Science and Data Analytics. This course introduces students to the basic statistical methods, coding applications, problem solving, and data integrity issues common to the field.

    • DSCI4700Capstone for Data Analytics Certificates
      DSCI4700 Capstone for Data Analytics Certificates - 3 s.h.

      The course covers the basic aspects of a complete data analytics project. Students will use data sets obtained from community partners. Students will work in teams with each team producing a problem definition in conjunction with the client, conducting the proposed analysis directed at providing insight into the problem, and disseminating the results of the analysis in written and oral form.

    CHEM3300Analytical Chemistry with Lab CHEM3610Physical Chemistry I with Lab CHEM3620Physical Chemistry II with Lab CSIT1100Principles of Computing DSCI1500Beginning Data Science and Data Analytics DSCI4700Capstone for Data Analytics Certificates
    Course Descriptions
    CHEM3300 Analytical Chemistry with Lab - 4 s.h.

    Study of theory and practice of modern separation and analytical techniques. Includes use of electrochemical, spectrometric and chromatographic instruments. Additional fee required. Prerequisite: CHEM1420. Offered odd years Spring.

    CHEM3610 Physical Chemistry I with Lab - 4 s.h.

    A study of thermodynamics, thermochemistry, chemical kinetics, equilibrium, atomic and molecular structure, electrochemistry, and quantum chemistry. Additional fee required. Prerequisites: CHEM1420, PHYS1420, and MATH1520. Offered odd years Fall. +This course is only offered every other year.

    CHEM3620 Physical Chemistry II with Lab - 4 s.h.

    Additional fee required. Continuation of CHEM3610, which is a prerequisite. Offered even years Spring. +This course is only offered every other year.

    CSIT1100 Principles of Computing - 3 s.h.

    An introduction to the fundamentals of computer programming through extensive practice developing software in the Python language. Fundamental terminology and topics such as integrated development environments, variables, data types, control structures, functions, and objects will be covered. ELO4 Global Learning - Innovation

    DSCI1500 Beginning Data Science and Data Analytics - 3 s.h.

    Introduction to the basic methods of analysis in Data Science and Data Analytics. This course introduces students to the basic statistical methods, coding applications, problem solving, and data integrity issues common to the field.

    DSCI4700 Capstone for Data Analytics Certificates - 3 s.h.

    The course covers the basic aspects of a complete data analytics project. Students will use data sets obtained from community partners. Students will work in teams with each team producing a problem definition in conjunction with the client, conducting the proposed analysis directed at providing insight into the problem, and disseminating the results of the analysis in written and oral form.

  • Data Analytics for Computer Science and Information Technology Certificate

    Students wishing to earn the Data Analytics for Computer Science and Information Technology certificate must complete the following 18 credit hours with Graceland University.

    Courses Offered
    • CSIT1100Principles of Computing
      CSIT1100 Principles of Computing - 3 s.h.

      An introduction to the fundamentals of computer programming through extensive practice developing software in the Python language. Fundamental terminology and topics such as integrated development environments, variables, data types, control structures, functions, and objects will be covered. ELO4 Global Learning - Innovation

    • CSIT1200Data Structures
      CSIT1200 Data Structures - 3 s.h.

      Continuation of CSIT1100 with emphasis on more advanced programming that involve classic data structures such as arrays, dictionaries, linked lists, queues, stacks, and trees. Recursive techniques and efficiency considerations will also be covered. Prerequisite: CSIT1100.

    • CSIT3300Database Concepts and SQL
      CSIT3300 Database Concepts and SQL - 3 s.h.

      A study of the concepts and structures required to implement a database system including the logical design and physical organization of the database. Emphasis is given to the design and development of database systems that includes understanding and applying entity-relationship models. Implementation of a database using SQL on a database system is included. Prerequisite: CSIT1100.

    • CSIT4200Machine Learning
      CSIT4200 Machine Learning - 3 s.h.

      A study of regression, kernels, support vector machines, clustering, Neural networks. Prerequisites: MATH3340, MATH2510, CSIT1200. (Students participating in the 4+1 Masters program in Data Science and Analytics should sign up for DSCI5370 Machine Learning.)

    • DSCI1500Beginning Data Science and Data Analytics
      DSCI1500 Beginning Data Science and Data Analytics - 3 s.h.

      Introduction to the basic methods of analysis in Data Science and Data Analytics. This course introduces students to the basic statistical methods, coding applications, problem solving, and data integrity issues common to the field.

    • DSCI4320Practical Applications of Data Science
      DSCI4320 Practical Applications of Data Science - 3 s.h.

      Exploratory data analysis is introduced along with fundamental considerations for data analysis on real data sets. Classical models and techniques for classification are included. Methods of data visualization are introduced. Prerequisites: CSIT4200 (Students participating in the 4+1 Masters program in Data Science and Analytics should sign up for DSCI5320 Practical Application of Data Science.)

    • DSCI4700Capstone for Data Analytics Certificates
      DSCI4700 Capstone for Data Analytics Certificates - 3 s.h.

      The course covers the basic aspects of a complete data analytics project. Students will use data sets obtained from community partners. Students will work in teams with each team producing a problem definition in conjunction with the client, conducting the proposed analysis directed at providing insight into the problem, and disseminating the results of the analysis in written and oral form.

    CSIT1100Principles of Computing CSIT1200Data Structures CSIT3300Database Concepts and SQL CSIT4200Machine Learning DSCI1500Beginning Data Science and Data Analytics DSCI4320Practical Applications of Data Science DSCI4700Capstone for Data Analytics Certificates
    Course Descriptions
    CSIT1100 Principles of Computing - 3 s.h.

    An introduction to the fundamentals of computer programming through extensive practice developing software in the Python language. Fundamental terminology and topics such as integrated development environments, variables, data types, control structures, functions, and objects will be covered. ELO4 Global Learning - Innovation

    CSIT1200 Data Structures - 3 s.h.

    Continuation of CSIT1100 with emphasis on more advanced programming that involve classic data structures such as arrays, dictionaries, linked lists, queues, stacks, and trees. Recursive techniques and efficiency considerations will also be covered. Prerequisite: CSIT1100.

    CSIT3300 Database Concepts and SQL - 3 s.h.

    A study of the concepts and structures required to implement a database system including the logical design and physical organization of the database. Emphasis is given to the design and development of database systems that includes understanding and applying entity-relationship models. Implementation of a database using SQL on a database system is included. Prerequisite: CSIT1100.

    CSIT4200 Machine Learning - 3 s.h.

    A study of regression, kernels, support vector machines, clustering, Neural networks. Prerequisites: MATH3340, MATH2510, CSIT1200. (Students participating in the 4+1 Masters program in Data Science and Analytics should sign up for DSCI5370 Machine Learning.)

    DSCI1500 Beginning Data Science and Data Analytics - 3 s.h.

    Introduction to the basic methods of analysis in Data Science and Data Analytics. This course introduces students to the basic statistical methods, coding applications, problem solving, and data integrity issues common to the field.

    DSCI4320 Practical Applications of Data Science - 3 s.h.

    Exploratory data analysis is introduced along with fundamental considerations for data analysis on real data sets. Classical models and techniques for classification are included. Methods of data visualization are introduced. Prerequisites: CSIT4200 (Students participating in the 4+1 Masters program in Data Science and Analytics should sign up for DSCI5320 Practical Application of Data Science.)

    DSCI4700 Capstone for Data Analytics Certificates - 3 s.h.

    The course covers the basic aspects of a complete data analytics project. Students will use data sets obtained from community partners. Students will work in teams with each team producing a problem definition in conjunction with the client, conducting the proposed analysis directed at providing insight into the problem, and disseminating the results of the analysis in written and oral form.

  • Data Analytics for Economics Certificate

    Students wishing to earn the Data Analytics for Economics certificate must complete the following 18 credit hours with Graceland University.

    Courses Offered
    • CSIT1100Principles of Computing
      CSIT1100 Principles of Computing - 3 s.h.

      An introduction to the fundamentals of computer programming through extensive practice developing software in the Python language. Fundamental terminology and topics such as integrated development environments, variables, data types, control structures, functions, and objects will be covered. ELO4 Global Learning - Innovation

    • DSCI1500Beginning Data Science and Data Analytics
      DSCI1500 Beginning Data Science and Data Analytics - 3 s.h.

      Introduction to the basic methods of analysis in Data Science and Data Analytics. This course introduces students to the basic statistical methods, coding applications, problem solving, and data integrity issues common to the field.

    • DSCI4700Capstone for Data Analytics Certificates
      DSCI4700 Capstone for Data Analytics Certificates - 3 s.h.

      The course covers the basic aspects of a complete data analytics project. Students will use data sets obtained from community partners. Students will work in teams with each team producing a problem definition in conjunction with the client, conducting the proposed analysis directed at providing insight into the problem, and disseminating the results of the analysis in written and oral form.

    • ECON2100Introductory Economic Data Analysis
      ECON2100 Introductory Economic Data Analysis - 3 s.h.

      An introduction to economic data and statistical techniques commonly applied in business settings. Topics include understanding the basics of data interpretation, manipulation, and visualization. Students will learn how to carry out and interpret basic linear regression and other methods of statistical analysis in Excel.

    • ECON3220Economics of Sports
      ECON3220 Economics of Sports - 3 s.h.

      An application of economic theory to the business of sports. Areas include labor economics, public finance, and the theory of the firm. Prerequisite: ECON1320 and either two MATH courses or MATH1360.

    • ECON3430Managerial Economics
      ECON3430 Managerial Economics - 3 s.h.

      Considers the business enterprise as an economic and social institution. Particular attention is given to the theory of the firm and the application of the theory in problem-solving. Prerequisites: MATH1360 and ECON3350. +This course is only offered every other year.

    CSIT1100Principles of Computing DSCI1500Beginning Data Science and Data Analytics DSCI4700Capstone for Data Analytics Certificates ECON2100Introductory Economic Data Analysis ECON3220Economics of Sports ECON3430Managerial Economics
    Course Descriptions
    CSIT1100 Principles of Computing - 3 s.h.

    An introduction to the fundamentals of computer programming through extensive practice developing software in the Python language. Fundamental terminology and topics such as integrated development environments, variables, data types, control structures, functions, and objects will be covered. ELO4 Global Learning - Innovation

    DSCI1500 Beginning Data Science and Data Analytics - 3 s.h.

    Introduction to the basic methods of analysis in Data Science and Data Analytics. This course introduces students to the basic statistical methods, coding applications, problem solving, and data integrity issues common to the field.

    DSCI4700 Capstone for Data Analytics Certificates - 3 s.h.

    The course covers the basic aspects of a complete data analytics project. Students will use data sets obtained from community partners. Students will work in teams with each team producing a problem definition in conjunction with the client, conducting the proposed analysis directed at providing insight into the problem, and disseminating the results of the analysis in written and oral form.

    ECON2100 Introductory Economic Data Analysis - 3 s.h.

    An introduction to economic data and statistical techniques commonly applied in business settings. Topics include understanding the basics of data interpretation, manipulation, and visualization. Students will learn how to carry out and interpret basic linear regression and other methods of statistical analysis in Excel.

    ECON3220 Economics of Sports - 3 s.h.

    An application of economic theory to the business of sports. Areas include labor economics, public finance, and the theory of the firm. Prerequisite: ECON1320 and either two MATH courses or MATH1360.

    ECON3430 Managerial Economics - 3 s.h.

    Considers the business enterprise as an economic and social institution. Particular attention is given to the theory of the firm and the application of the theory in problem-solving. Prerequisites: MATH1360 and ECON3350. +This course is only offered every other year.

  • Data Analytics for Environmental Science Certificate

    Students wishing to earn the Data Analytics for Environmental Science certificate must complete the following 20-21 credit hours with Graceland University.

    Courses Offered
    • BIOL1200Environmental Science with Lab (also CHEM1200)
      BIOL1200 Environmental Science with Lab (also CHEM1200) - 4 s.h.

      An exploration of the biotic and abiotic components of the environment, including the biological, physical, and chemical processes that shape natural ecosystems (e.g., biogeochemical cycles). The course will also examine the impact of human population growth, resource use, emissions production, and technological innovations on the environment. Current environmental issues, such as loss of biodiversity, ecosystem degradation, air and water pollution, and climate change, will be considered. Additional fee required. ELO6 Science - Innovation, GE3D Liberal Learning-Natural Sciences

    • BIOL3400Ecology and Conservation Biology with Lab
      BIOL3400 Ecology and Conservation Biology with Lab - 4 s.h.

      A study of how organisms interact with one another and with their physical environments at the physiological, population, community, and ecosystem levels. Case studies will use ecological concepts to develop conservation strategies for species, habitats, and ecosystems. Includes a lab. Additional fee required. EL06 Science - World Citizenship, ELO6 Science - Sustainability +This course is only offered every other year.

    • CHEM1200Environmental Science with Lab (also BIOL1200)
      CHEM1200 Environmental Science with Lab (also BIOL1200) - 4 s.h.

      An exploration of the biotic and abiotic components of the environment, including the biological, physical, and chemical processes that shape natural ecosystems (e.g., biogeochemical cycles). The course will also examine the impact of human population growth, resource use, emissions production, and technological innovations on the environment. Current environmental issues, such as loss of biodiversity, ecosystem degradation, air and water pollution, and climate change, will be considered. Additional fee required. ELO6 Science - Innovation, GE3D Liberal Learning-Natural Sciences.

    • CHEM3300Analytical Chemistry with Lab
      CHEM3300 Analytical Chemistry with Lab - 4 s.h.

      Study of theory and practice of modern separation and analytical techniques. Includes use of electrochemical, spectrometric and chromatographic instruments. Additional fee required. Prerequisite: CHEM1420. Offered odd years Spring.

    • CSIT1100Principles of Computing
      CSIT1100 Principles of Computing - 3 s.h.

      An introduction to the fundamentals of computer programming through extensive practice developing software in the Python language. Fundamental terminology and topics such as integrated development environments, variables, data types, control structures, functions, and objects will be covered. ELO4 Global Learning - Innovation

    • CSIT2110Introduction to Geographic Information Sciences (also SUST2100)
      CSIT2110 Introduction to Geographic Information Sciences (also SUST2100) - 3 s.h.

      Students will learn theoretical and practical foundations related to geographic information systems and spatial analysis. Emphasis on teaching students to integrate and analyze spatial information from various sources. Includes a weekly laboratory section. Prerequisite: MATH1380.

    • DSCI1500Beginning Data Science and Data Analytics
      DSCI1500 Beginning Data Science and Data Analytics - 3 s.h.

      Introduction to the basic methods of analysis in Data Science and Data Analytics. This course introduces students to the basic statistical methods, coding applications, problem solving, and data integrity issues common to the field.

    • DSCI4700Capstone for Data Analytics Certificates
      DSCI4700 Capstone for Data Analytics Certificates - 3 s.h.

      The course covers the basic aspects of a complete data analytics project. Students will use data sets obtained from community partners. Students will work in teams with each team producing a problem definition in conjunction with the client, conducting the proposed analysis directed at providing insight into the problem, and disseminating the results of the analysis in written and oral form.

    • SUST2100Introduction to Geographic Information Sciences (also CSIT2110)
      SUST2100 Introduction to Geographic Information Sciences (also CSIT2110) - 3 s.h.

      Students will learn theoretical and practical foundations related to geographic information systems and spatial analysis. Emphasis on teaching students to integrate and analyze spatial information from various sources. Includes a weekly laboratory section. Prerequisite: MATH1370.

    BIOL1200Environmental Science with Lab (also CHEM1200) BIOL3400Ecology and Conservation Biology with Lab CHEM1200Environmental Science with Lab (also BIOL1200) CHEM3300Analytical Chemistry with Lab CSIT1100Principles of Computing CSIT2110Introduction to Geographic Information Sciences (also SUST2100) DSCI1500Beginning Data Science and Data Analytics DSCI4700Capstone for Data Analytics Certificates SUST2100Introduction to Geographic Information Sciences (also CSIT2110)
    Course Descriptions
    BIOL1200 Environmental Science with Lab (also CHEM1200) - 4 s.h.

    An exploration of the biotic and abiotic components of the environment, including the biological, physical, and chemical processes that shape natural ecosystems (e.g., biogeochemical cycles). The course will also examine the impact of human population growth, resource use, emissions production, and technological innovations on the environment. Current environmental issues, such as loss of biodiversity, ecosystem degradation, air and water pollution, and climate change, will be considered. Additional fee required. ELO6 Science - Innovation, GE3D Liberal Learning-Natural Sciences

    BIOL3400 Ecology and Conservation Biology with Lab - 4 s.h.

    A study of how organisms interact with one another and with their physical environments at the physiological, population, community, and ecosystem levels. Case studies will use ecological concepts to develop conservation strategies for species, habitats, and ecosystems. Includes a lab. Additional fee required. EL06 Science - World Citizenship, ELO6 Science - Sustainability +This course is only offered every other year.

    CHEM1200 Environmental Science with Lab (also BIOL1200) - 4 s.h.

    An exploration of the biotic and abiotic components of the environment, including the biological, physical, and chemical processes that shape natural ecosystems (e.g., biogeochemical cycles). The course will also examine the impact of human population growth, resource use, emissions production, and technological innovations on the environment. Current environmental issues, such as loss of biodiversity, ecosystem degradation, air and water pollution, and climate change, will be considered. Additional fee required. ELO6 Science - Innovation, GE3D Liberal Learning-Natural Sciences.

    CHEM3300 Analytical Chemistry with Lab - 4 s.h.

    Study of theory and practice of modern separation and analytical techniques. Includes use of electrochemical, spectrometric and chromatographic instruments. Additional fee required. Prerequisite: CHEM1420. Offered odd years Spring.

    CSIT1100 Principles of Computing - 3 s.h.

    An introduction to the fundamentals of computer programming through extensive practice developing software in the Python language. Fundamental terminology and topics such as integrated development environments, variables, data types, control structures, functions, and objects will be covered. ELO4 Global Learning - Innovation

    CSIT2110 Introduction to Geographic Information Sciences (also SUST2100) - 3 s.h.

    Students will learn theoretical and practical foundations related to geographic information systems and spatial analysis. Emphasis on teaching students to integrate and analyze spatial information from various sources. Includes a weekly laboratory section. Prerequisite: MATH1380.

    DSCI1500 Beginning Data Science and Data Analytics - 3 s.h.

    Introduction to the basic methods of analysis in Data Science and Data Analytics. This course introduces students to the basic statistical methods, coding applications, problem solving, and data integrity issues common to the field.

    DSCI4700 Capstone for Data Analytics Certificates - 3 s.h.

    The course covers the basic aspects of a complete data analytics project. Students will use data sets obtained from community partners. Students will work in teams with each team producing a problem definition in conjunction with the client, conducting the proposed analysis directed at providing insight into the problem, and disseminating the results of the analysis in written and oral form.

    SUST2100 Introduction to Geographic Information Sciences (also CSIT2110) - 3 s.h.

    Students will learn theoretical and practical foundations related to geographic information systems and spatial analysis. Emphasis on teaching students to integrate and analyze spatial information from various sources. Includes a weekly laboratory section. Prerequisite: MATH1370.

  • Data Analytics for Health and Movement Science Certificate

    Students wishing to earn the Data Analytics for Health and Movement Science certificate must complete the following 18 credit hours with Graceland University.

    Courses Offered
    • CSIT1100Principles of Computing
      CSIT1100 Principles of Computing - 3 s.h.

      An introduction to the fundamentals of computer programming through extensive practice developing software in the Python language. Fundamental terminology and topics such as integrated development environments, variables, data types, control structures, functions, and objects will be covered. ELO4 Global Learning - Innovation

    • DSCI1500Beginning Data Science and Data Analytics
      DSCI1500 Beginning Data Science and Data Analytics - 3 s.h.

      Introduction to the basic methods of analysis in Data Science and Data Analytics. This course introduces students to the basic statistical methods, coding applications, problem solving, and data integrity issues common to the field.

    • DSCI4700Capstone for Data Analytics Certificates
      DSCI4700 Capstone for Data Analytics Certificates - 3 s.h.

      The course covers the basic aspects of a complete data analytics project. Students will use data sets obtained from community partners. Students will work in teams with each team producing a problem definition in conjunction with the client, conducting the proposed analysis directed at providing insight into the problem, and disseminating the results of the analysis in written and oral form.

    • HLTH3220Personal and Community Health
      HLTH3220 Personal and Community Health - 3 s.h.

      A foundational course designed for students to become informed about health as well as becoming responsible and active participants in the maintenance of their personal health and affecting the health of their community. The course is intended to provide coverage of health promotion, mental health, stress management, afflictions and diseases, aging, environmental health, consumerism and health care and promotion. ELO4 Global Learning - Sustainability.

    • HMSC3200Foundations of Evidence Based Practice
      HMSC3200 Foundations of Evidence Based Practice - 3 s.h.

      Presentation of introductory research and writing methods. Introduction to the application of evidence-based practice using various tools to evaluate the research as evidence. This class will result in a final critically appraised topic paper and poster presentation.

    • PHED3340Biomechanics
      PHED3340 Biomechanics - 3 s.h.

      A systematic study of the bones, joints, and muscles of the human body as well as internal external forces initiating and modifying movement. Prerequisite: BIOL2300 or BIOL3420 with a grade of "C" or higher. A grade of C or higher required to count toward the Allied Health major.

    • PHED4360Physiology of Exercise
      PHED4360 Physiology of Exercise - 3 s.h.

      The principles and practices of energizing the human body for physical exercise. Prerequisite: BIOL2300 or BIOL3440 with a grade of "C" or better. A grade of C or higher required to count toward the Allied Health major.

    CSIT1100Principles of Computing DSCI1500Beginning Data Science and Data Analytics DSCI4700Capstone for Data Analytics Certificates HLTH3220Personal and Community Health HMSC3200Foundations of Evidence Based Practice PHED3340Biomechanics PHED4360Physiology of Exercise
    Course Descriptions
    CSIT1100 Principles of Computing - 3 s.h.

    An introduction to the fundamentals of computer programming through extensive practice developing software in the Python language. Fundamental terminology and topics such as integrated development environments, variables, data types, control structures, functions, and objects will be covered. ELO4 Global Learning - Innovation

    DSCI1500 Beginning Data Science and Data Analytics - 3 s.h.

    Introduction to the basic methods of analysis in Data Science and Data Analytics. This course introduces students to the basic statistical methods, coding applications, problem solving, and data integrity issues common to the field.

    DSCI4700 Capstone for Data Analytics Certificates - 3 s.h.

    The course covers the basic aspects of a complete data analytics project. Students will use data sets obtained from community partners. Students will work in teams with each team producing a problem definition in conjunction with the client, conducting the proposed analysis directed at providing insight into the problem, and disseminating the results of the analysis in written and oral form.

    HLTH3220 Personal and Community Health - 3 s.h.

    A foundational course designed for students to become informed about health as well as becoming responsible and active participants in the maintenance of their personal health and affecting the health of their community. The course is intended to provide coverage of health promotion, mental health, stress management, afflictions and diseases, aging, environmental health, consumerism and health care and promotion. ELO4 Global Learning - Sustainability.

    HMSC3200 Foundations of Evidence Based Practice - 3 s.h.

    Presentation of introductory research and writing methods. Introduction to the application of evidence-based practice using various tools to evaluate the research as evidence. This class will result in a final critically appraised topic paper and poster presentation.

    PHED3340 Biomechanics - 3 s.h.

    A systematic study of the bones, joints, and muscles of the human body as well as internal external forces initiating and modifying movement. Prerequisite: BIOL2300 or BIOL3420 with a grade of "C" or higher. A grade of C or higher required to count toward the Allied Health major.

    PHED4360 Physiology of Exercise - 3 s.h.

    The principles and practices of energizing the human body for physical exercise. Prerequisite: BIOL2300 or BIOL3440 with a grade of "C" or better. A grade of C or higher required to count toward the Allied Health major.

  • Data Analytics for Sport Management Certificate

    Students wishing to earn the Data Analytics for Sport Marketing certificate must complete the following 18 credit hours with Graceland University.

    Courses Offered
    • CSIT1100Principles of Computing
      CSIT1100 Principles of Computing - 3 s.h.

      An introduction to the fundamentals of computer programming through extensive practice developing software in the Python language. Fundamental terminology and topics such as integrated development environments, variables, data types, control structures, functions, and objects will be covered. ELO4 Global Learning - Innovation

    • DSCI1500Beginning Data Science and Data Analytics
      DSCI1500 Beginning Data Science and Data Analytics - 3 s.h.

      Introduction to the basic methods of analysis in Data Science and Data Analytics. This course introduces students to the basic statistical methods, coding applications, problem solving, and data integrity issues common to the field.

    • DSCI4700Capstone for Data Analytics Certificates
      DSCI4700 Capstone for Data Analytics Certificates - 3 s.h.

      The course covers the basic aspects of a complete data analytics project. Students will use data sets obtained from community partners. Students will work in teams with each team producing a problem definition in conjunction with the client, conducting the proposed analysis directed at providing insight into the problem, and disseminating the results of the analysis in written and oral form.

    • ECON2100Introductory Economic Data Analysis
      ECON2100 Introductory Economic Data Analysis - 3 s.h.

      An introduction to economic data and statistical techniques commonly applied in business settings. Topics include understanding the basics of data interpretation, manipulation, and visualization. Students will learn how to carry out and interpret basic linear regression and other methods of statistical analysis in Excel.

    • ECON3220Economics of Sports
      ECON3220 Economics of Sports - 3 s.h.

      An application of economic theory to the business of sports. Areas include labor economics, public finance, and the theory of the firm. Prerequisite: ECON1320 and either two MATH courses or MATH1360.

    • SPMT3300Sport Marketing
      SPMT3300 Sport Marketing - 3 s.h.

      An analysis of the field of marketing from a sports perspective with focus on the elements of and development of a marketing plan. Prerequisite: ECON1320.

    CSIT1100Principles of Computing DSCI1500Beginning Data Science and Data Analytics DSCI4700Capstone for Data Analytics Certificates ECON2100Introductory Economic Data Analysis ECON3220Economics of Sports SPMT3300Sport Marketing
    Course Descriptions
    CSIT1100 Principles of Computing - 3 s.h.

    An introduction to the fundamentals of computer programming through extensive practice developing software in the Python language. Fundamental terminology and topics such as integrated development environments, variables, data types, control structures, functions, and objects will be covered. ELO4 Global Learning - Innovation

    DSCI1500 Beginning Data Science and Data Analytics - 3 s.h.

    Introduction to the basic methods of analysis in Data Science and Data Analytics. This course introduces students to the basic statistical methods, coding applications, problem solving, and data integrity issues common to the field.

    DSCI4700 Capstone for Data Analytics Certificates - 3 s.h.

    The course covers the basic aspects of a complete data analytics project. Students will use data sets obtained from community partners. Students will work in teams with each team producing a problem definition in conjunction with the client, conducting the proposed analysis directed at providing insight into the problem, and disseminating the results of the analysis in written and oral form.

    ECON2100 Introductory Economic Data Analysis - 3 s.h.

    An introduction to economic data and statistical techniques commonly applied in business settings. Topics include understanding the basics of data interpretation, manipulation, and visualization. Students will learn how to carry out and interpret basic linear regression and other methods of statistical analysis in Excel.

    ECON3220 Economics of Sports - 3 s.h.

    An application of economic theory to the business of sports. Areas include labor economics, public finance, and the theory of the firm. Prerequisite: ECON1320 and either two MATH courses or MATH1360.

    SPMT3300 Sport Marketing - 3 s.h.

    An analysis of the field of marketing from a sports perspective with focus on the elements of and development of a marketing plan. Prerequisite: ECON1320.

  • Course list - Data Science
    Courses Offered
    • DSCI1500Beginning Data Science and Data Analytics
      DSCI1500 Beginning Data Science and Data Analytics - 3 s.h.

      Introduction to the basic methods of analysis in Data Science and Data Analytics. This course introduces students to the basic statistical methods, coding applications, problem solving, and data integrity issues common to the field.

    • DSCI4300Introduction to Data Science
      DSCI4300 Introduction to Data Science - 3 s.h.

      An introduction to the methods of data science through a combination of computational exploration, visualization, and theory. Students will learn scientific computing basics, topics in numerical linear algebra, mathematical probability, statistics, and social and political issues raised by data science. Prerequisites: Prior courses in statistics, calculus and basic programming. (Students participating in the 4+1 Masters program in Data Science and Analytics should sign up for DSCI5300 Introduction to Data Science.)

    • DSCI4320Practical Applications of Data Science
      DSCI4320 Practical Applications of Data Science - 3 s.h.

      Exploratory data analysis is introduced along with fundamental considerations for data analysis on real data sets. Classical models and techniques for classification are included. Methods of data visualization are introduced. Prerequisites: CSIT4200 (Students participating in the 4+1 Masters program in Data Science and Analytics should sign up for DSCI5320 Practical Application of Data Science.)

    • DSCI4330Extracting and Transforming Data
      DSCI4330 Extracting and Transforming Data - 3 s.h.

      Students will learn skills of data acquisition, methods of data cleaning, imputing data, data storage and other important issues required to producing useable data sets. Codebooks, data standards, and markdown files will be introduced as well as the concept of the data lake. Prerequisites: DSCI4300. (Students participating in the 4+1 Masters program in Data Science and Analytics should sign up for DSCI5330 Extracting and Transforming Data.)

    • DSCI4700Capstone for Data Analytics Certificates
      DSCI4700 Capstone for Data Analytics Certificates - 3 s.h.

      The course covers the basic aspects of a complete data analytics project. Students will use data sets obtained from community partners. Students will work in teams with each team producing a problem definition in conjunction with the client, conducting the proposed analysis directed at providing insight into the problem, and disseminating the results of the analysis in written and oral form.

    DSCI1500Beginning Data Science and Data Analytics DSCI4300Introduction to Data Science DSCI4320Practical Applications of Data Science DSCI4330Extracting and Transforming Data DSCI4700Capstone for Data Analytics Certificates
    Course Descriptions
    DSCI1500 Beginning Data Science and Data Analytics - 3 s.h.

    Introduction to the basic methods of analysis in Data Science and Data Analytics. This course introduces students to the basic statistical methods, coding applications, problem solving, and data integrity issues common to the field.

    DSCI4300 Introduction to Data Science - 3 s.h.

    An introduction to the methods of data science through a combination of computational exploration, visualization, and theory. Students will learn scientific computing basics, topics in numerical linear algebra, mathematical probability, statistics, and social and political issues raised by data science. Prerequisites: Prior courses in statistics, calculus and basic programming. (Students participating in the 4+1 Masters program in Data Science and Analytics should sign up for DSCI5300 Introduction to Data Science.)

    DSCI4320 Practical Applications of Data Science - 3 s.h.

    Exploratory data analysis is introduced along with fundamental considerations for data analysis on real data sets. Classical models and techniques for classification are included. Methods of data visualization are introduced. Prerequisites: CSIT4200 (Students participating in the 4+1 Masters program in Data Science and Analytics should sign up for DSCI5320 Practical Application of Data Science.)

    DSCI4330 Extracting and Transforming Data - 3 s.h.

    Students will learn skills of data acquisition, methods of data cleaning, imputing data, data storage and other important issues required to producing useable data sets. Codebooks, data standards, and markdown files will be introduced as well as the concept of the data lake. Prerequisites: DSCI4300. (Students participating in the 4+1 Masters program in Data Science and Analytics should sign up for DSCI5330 Extracting and Transforming Data.)

    DSCI4700 Capstone for Data Analytics Certificates - 3 s.h.

    The course covers the basic aspects of a complete data analytics project. Students will use data sets obtained from community partners. Students will work in teams with each team producing a problem definition in conjunction with the client, conducting the proposed analysis directed at providing insight into the problem, and disseminating the results of the analysis in written and oral form.