BS- Data Science and Analytics 24
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The Bachelor of Science with a major in Data Science and Analytics will provide a student with foundational mathematical, statistical, and computational knowledge, skills, and methodologies within the context of the ethical and professional standards of Data Science. A student will also complete at least 16 hours of courses in either a domain of expertise in data science and analytics or a minor to provide them a context in which to apply their data science abilities. Thus, the degree will enable the student to either begin a career in industry, government, or community and non-profit organizations in a range of domains, or pursue graduate study.
Students will begin the program by building a foundation in mathematics, statistics, computer programming, and algorithmic techniques. They will then take 38 credit hours of data science core courses covering the/fundamentals of data science,/programming, machine learning,/data mining, data science ethics, and communication. After completing the core, students will complete 6 credit hours of elective courses in data science and statistical learning. Students will also be required to take at least 16 hours in a suitable domain knowledge concentration to begin exploring an expert area of application. The program will conclude with a required/data science capstone/course, in which the student will demonstrate overall knowledge of the discipline by completing a data science project, incorporating all the knowledge learned in the courses.
Term 1
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Requirement
Hours
ENGL 1101 English Composition IENGL 1101 English Composition I3 Credits
A composition course focusing on skills required for effective writing in a variety of contexts, with emphasis on exposition, analysis, and argumentation, and also including introductory use of a variety of research skills.
3
POLS 1101 American GovernmentPOLS 1101 American Government3 Credits
This course examines the institutions and processes of American government and Georgia State government. Global comparisons are made between the governments of the U.S. and other modern nation-states.
3
-
3
-
3
-
3
Total: 15
Term 2
-
Requirement
Hours
ENGL 1102 English Composition IIENGL 1102 English Composition II3 Credits
A composition course that develops writing skills beyond the levels of proficiency required by ENGL 1101, that emphasizes interpretation, and evaluation, and that incorporates a variety of more advanced research methods.
Prerequisites: (
ENGL 1101 with a minimum grade of C or
ENGL 101 with a minimum grade of C)
3
CSE 1321 Programming Problem Solving ICSE 1321 Credits
Description not available
Prerequisites: CSE 1321L** with a minimum grade of C
3
CSE 1321L Program Problem Solving I LabCSE 1321L Credits
Description not available
Prerequisites: CSE 1321** with a minimum grade of C
1
ECON 1000 Contemporary Economic IssuesECON 1000 Credits
Description not available
2
-
4
-
3
Total: 16
Year 1 (Hours: 31)
Term 3
-
Requirement
Hours
MATH 2202 Calculus IIMATH 2202 Calculus II4 Credits
This course is the second in the calculus curriculum and consists of two parts. The first part is concerned with the techniques of integration and applications of the integral. The second part is concerned with infinite sequences and series.
Prerequisites: MATH 1190 with a minimum grade of C or
MATH 1179 with a minimum grade of C and
MATH 1189 with a minimum grade of C
4
CSE 1322 Programming Problem Solving IICSE 1322 Credits
Description not available
Prerequisites: (
CSE 1321 with a minimum grade of B and
CSE 1321L with a minimum grade of B and
CSE 1322L** with a minimum grade of C and (
MATH 1113** with a minimum grade of C or
MATH 1190** with a minimum grade of C or
MATH 1179** with a minimum grade of C) or
MATH 2202** with a minimum grade of C)
3
CSE 1322L Program Problem Solving II LabCSE 1322L Credits
Description not available
Prerequisites: CSE 1321 with a minimum grade of B and
CSE 1321L with a minimum grade of B and
CSE 1322** with a minimum grade of C
1
DATA 3010 Computer Applications of StatsDATA 3010 Computer Applications of Stats3 Credits
This course is an introduction to the use of computer-based statistical software packages and applications in the analysis and interpretation of data. Topics include both descriptive statistics and inference methods. Software packages include SAS, Excel, and R, and one of JMP, SPSS or Minitab.
Prerequisites: MATH 1107 with a minimum grade of C or
STAT 1401 with a minimum grade of C or
MATH 1107 with a minimum grade of C or
MATH 1401 with a minimum grade of C or
ECON 2300 with a minimum grade of C or
STAT 2332 with a minimum grade of C or
STAT 3125 with a minimum grade of C
3
-
3
Total: 14
Term 4
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Requirement
Hours
MATH 3260 Linear Algebra IMATH 3260 Linear Algebra I3 Credits
An introduction to linear algebra and some of its classical and modern applications. Among topics to be included will be systems of linear equations, matrices, determinants of matrices and applications, vector spaces, and inner product spaces. Significant use of technology will be employed in performing matrix computations.
Prerequisites: MATH 1190 with a minimum grade of C or
MATH 1179 with a minimum grade of C and
MATH 1189 with a minimum grade of C
3
General Education Core Curriculum Technology, Mathematics, and Science (1 of 2)General Education Core Curriculum Technology, Mathematics, and Science (1 of 2)4 Credits
(CHEM 1211 and CHEM 1211L) or (CHEM 1212 and CHEM 1212L) or (PHYS 1111 and PHYS 1111L) or (PHYS 1112 and PHYS 1112L) or (PHYS 2211 and PHYS 2211L) or (PHYS 2212 and PHYS 2212L) or (BIOL 1107 and BIOL 1107L) or (BIOL 1108 and BIOL 1108L)
4
-
3
-
3
-
3
Total: 16
Year 2 (Hours: 30)
Term 5
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Requirement
Hours
STAT 3130 Statistical Methods IISTAT 3130 Statistical Methods II3 Credits
Students continue to build their foundation in statistical methods in this course beginning with review of t-tests. They perform and analyze results of Wilcoxon Signed Rank and Rank Sum tests (Non-Parametric t-tests), ANOVA, Kruskal Wallis (Non-Parametric ANOVA) and Multiple Regression. These concepts are taught with heavy emphasis on statistical computing software (especially SAS) and real world datasets.
Prerequisites: (
STAT 3010 with a minimum grade of C and (
STAT 3120 with a minimum grade of C or
STAT 3125 with a minimum grade of C or
STAT 2332 with a minimum grade of C or
PSYC 3000 with a minimum grade of C or
PSYC 3301 with a minimum grade of C))
3
DATA 3230 Data VisualizationDATA 3230 Data Visualization3 Credits
This course introduces students to the field of data visualization. The course covers basic design and evaluation principles to prepare and analyze large datasets, and standard visualization techniques for different types of data using modern data visualization software. The course prepares students to communicate clearly, efficiently, and in a visually compelling manner to a variety of audiences.
Prerequisites: STAT 1401 with a minimum grade of C or
DATA 1501 with a minimum grade of C or
STAT 2332 with a minimum grade of C or
STAT 3125 with a minimum grade of C
3
General Education Core Curriculum Technology, Mathematics, and Science (2 of 2)General Education Core Curriculum Technology, Mathematics, and Science (2 of 2)4 Credits
(CHEM 1211 and CHEM 1211L) or (CHEM 1212 and CHEM 1212L) or (PHYS 1111 and PHYS 1111L) or (PHYS 1112 and PHYS 1112L) or (PHYS 2211 and PHYS 2211L) or (PHYS 2212 and PHYS 2212L) or (BIOL 1107 and BIOL 1107L) or (BIOL 1108 and BIOL 1108L)
4
-
3
-
3
Total: 16
Term 6
-
Requirement
Hours
STAT 4210 Topics in RegressionSTAT 4210 Topics in Regression3 Credits
Topics include simple linear regression, multiple regression models, generalized linear model, multicollinearty, qualitative predictor variables, model selection and validation, identifying outliers and influential observations, diagnostics for multicollinearity, and logistic regression and discriminant analysis.
Prerequisites: STAT 3130 with a minimum grade of C
3
DATA 3300 Data Science EthicsDATA 3300 Data Science Ethics3 Credits
As the field of data science and artificial intelligence continues to rapidly grow, so does the need for strong ethical guidelines. Throughout this course, students will learn the foundational ethical theories and frameworks, and the origins of ethics within data science. Students will use case studies to learn about the ethical dilemmas around the collection, management, and use of data, the use of models and algorithms, and the future of artificial intelligence and machine learning. Topics include Privacy, Informed Consent, Ownership, Security, Bias, Misinformation, Data Governance and Codes of Ethics.
Prerequisites: STAT 3130 with a minimum grade of C
3
-
3
Major Elective (1 of 2)Major Elective (1 of 2)3 Credits
DATA 3396 or DATA 3398 or STAT 4025 or DATA 4030 or STAT 4120 or STAT 4125 or DATA 4330 or DATA 4400 or DATA 4490 or DATA 4140 or CSE 4983
3
-
3
Total: 15
Year 3 (Hours: 31)
Term 7
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Requirement
Hours
STAT 4310 Statistical Data MiningSTAT 4310 Statistical Data Mining3 Credits
Data Mining is an information extraction activity whose goal is to discover hidden facts contained in databases, perform prediction and forecasting, and generally improve their performance through interaction with data. The process includes data selection, cleaning, coding, using different statistical, pattern recognition and machine learning techniques, and reporting and visualization of the generated structures. The course will cover all these issues and will illustrate the whole process by examples of practical applications. The students will use recent SAS Enterprise Miner software.
Prerequisites: STAT 3130 with a minimum grade of C
3
DATA 4000 Data Science CommunicationDATA 4000 Data Science Communication3 Credits
This course equips students to orally communicate data analysis results adapted to both technical and non-technical audiences. Students learn and practice essential data presentation skills, such as using narratives and visuals to communicate data analysis insights for solving business problems.
Prerequisites: STAT 2332 with a minimum grade of C or
STAT 3010 with a minimum grade of C and (
STAT 3120 with a minimum grade of C or
STAT 3125 with a minimum grade of C)
3
-
3
-
3
Major Elective (2 of 2)Major Elective (2 of 2)3 Credits
DATA 3396 or DATA 3398 or STAT 4025 or DATA 4030 or STAT 4120 or STAT 4125 or DATA 4330 or DATA 4400 or DATA 4490 or DATA 4140 or CSE 4983
3
Total: 15
Term 8
-
Requirement
Hours
DATA 4990 Data Science CapstoneDATA 4990 Data Science Capstone3 Credits
Capstone projects challenge students to acquire and analyze data to solve real-world problems. Students will have to synthesize and strengthen the knowledge and skills learned through the program such as data visualization, inference and modeling, data wrangling, data organization, data mining and machine learning, as well as storytelling with the data.
Prerequisites: STAT 4210 with a minimum grade of C
3
-
3
-
3
-
3
-
1
Total: 13
Year 4 (Hours: 28)
Program Total: 120 Hours
Milestones: All courses indicated as a Milestone with this icon ( ) should be completed in the term suggested to prevent delays in program completion.
Disclaimer: An academic map is a suggested four-year schedule of courses based on degree requirements in the KSU undergraduate catalog. This sample schedule serves as a general guideline to help build a full schedule each term. Some departments allow students to use the three credit first-year seminar course as a free elective for a degree program, which may impact the program's total credit hours. Milestones, courses, and special requirements necessary for timely progress to complete a major are designated to keep you on track to graduate in four years. Missing milestones could delay your program. Enrolled Students should reference DegreeWorks and not this plan.
This map is not a substitute for academic advisement—contact your advisor if you have any questions about scheduling or about your degree requirements. Also
see the current undergraduate catalog (catalog.kennesaw.edu) for a complete list of requirements and electives. Note: Requirements are continually under revision, and
there is no guarantee they will not be changed or revoked; contact the department and/or program area for current information.
You may choose to attend a summer term to reduce your load during fall or spring terms but still stay on track to graduate in four years.