Bachelor of Science, Major in Data Science
Additional information: Reference the Program Landing Page for additional information, such as cost, delivery format, contact information, or to schedule a visit.
Code | Title | Hours |
---|---|---|
Bachelor of Science, Major in Data Science | ||
Core Curriculum | ||
Component Area I (Communication) | 6 | |
Component Area II (Mathematics) ^{1} | 3 | |
Component Area III (Life and Physical Science) (Courses for Science Majors) | 8 | |
Component Area IV (Language, Philosophy, and Culture) | 3 | |
Component Area V (Creative Arts) | 3 | |
Component Area VI (U.S. History) | 6 | |
Component Area VII (Political Science/Government) | 6 | |
Component Area VIII (Social and Behavioral Sciences) | 3 | |
Component Area IX (Component Area Option) | 4 | |
Degree Specific Requirements | ||
MATH 1420 | Calculus I ^{1} | 4 |
Major: Foundation | ||
BANA 4373 | Advanced Business Analytics for Economics and Business | 3 |
COSC 1436 | Programming Fundamentals I | 4 |
COSC 1437 | Programming Fundamentals II | 4 |
COSC 3318 | Data Base Management Systems | 3 |
MATH 1430 | Calculus II | 4 |
MATH 3377 | Introduction to Linear Algebra and Matrices | 3 |
STAT 3379 | Statistical Methods in Practice | 3 |
STAT 3381 | Sample Survey Methods | 3 |
STAT 3382 | Introduction to Statistical Computing | 3 |
STAT 3385 | Statistical Methods for Data Science | 3 |
STAT 4371 | Theory and Applications of Probability and Statistics I | 3 |
STAT 4373 | Nonparametric Statistics | 3 |
STAT 4374 | Regression Modeling & Analysis | 3 |
STAT 4390 | Introduction to Statistical Learning | 3 |
Major: Concentration | ||
Select one concentration from below options: ^{2} | 33-34 | |
Statistics | ||
Computer Science | ||
Economics | ||
Minor: Not Required ^{3} | ||
Total Hours | 120-121 |
- ^{ 1 }
MATH 1420 satisfies the Core Curriculum requirement for Component Area II (Mathematics) and one semester credit hour of the Core Curriculum requirement for Component Area IX (Component Area Option). MATH 1420 satisfies the prerequisite requirement for MATH 1430.
- ^{ 2 }
Select one Concentration (Statistics, Computer Science, or Economics) from the options below.
- ^{ 3 }
A minor is not required for this degree program; however, a student has the option to add a minor, but to do so additional semester credits hours may be needed above the degree program’s stated total semester credit hours.
Notes
Students must earn a 2.0 minimum overall GPA in all coursework.
Students must meet a 2.0 minimum overall major GPA in all major coursework.
Students must earn a 2.0 minimum SHSU GPA in all coursework.
Students must meet a 2.0 minimum SHSU major GPA in all major coursework.
Code | Title | Hours |
---|---|---|
Major: Concentration (Statistics) ^{2} | ||
GEOG 2464 | Introduction to Geographic Information Systems (GIS) | 4 |
ECON 2300 | Introduction To Economics ^{1} | 3 |
or ECON 2301 | Principles Of Macroeconomics | |
or ECON 2302 | Principles Of Microeconomics | |
STAT 4372 | Theory and Applications of Probability and Statistics II | 3 |
Select three from the following: | 9 | |
Statistical Design and Analysis of Experiments | ||
Special Topics in Statistics | ||
Quality Control & Reliability | ||
Time Series and Forecasting | ||
Introduction to Applied Bayesian Analysis | ||
Select three from the following: | 9-10 | |
Discrete Mathematics | ||
Calculus III | ||
Introduction to Mathematics Thought | ||
Theory of Interest | ||
Differential Equations | ||
Numerical Methods | ||
Introductory Analysis | ||
Elementary Analysis | ||
Special Topics in Mathematics | ||
General Electives | 8 | |
Total Hours | 33-34 |
- ^{ 1 }
ECON 2300, ECON 2301, and ECON 2302 satisfy the Core Curriculum requirement for Component Area VIII (Social and Behavioral Sciences).
Code | Title | Hours |
---|---|---|
Major: Concentration (Computer Science) ^{2} | ||
COSC 3337 | Information Systems Design & Management | 3 |
COSC 4320 | System Modeling and Simulation | 3 |
ECON 2300 | Introduction To Economics ^{1} | 3 |
or ECON 2301 | Principles Of Macroeconomics | |
or ECON 2302 | Principles Of Microeconomics | |
Select two from the following: | 6 | |
Special Topics/Programming | ||
Data Structures and Algorithms | ||
Data Mining | ||
Special Topics in Computer Science | ||
Select three from the following: | 9 | |
Statistical Design and Analysis of Experiments | ||
Special Topics in Statistics | ||
Quality Control & Reliability | ||
Time Series and Forecasting | ||
Introduction to Applied Bayesian Analysis | ||
Select two from the following: | 6-7 | |
Discrete Mathematics | ||
Calculus III | ||
Introduction to Mathematics Thought | ||
Theory of Interest | ||
Differential Equations | ||
Numerical Methods | ||
Introductory Analysis | ||
Elementary Analysis | ||
Special Topics in Mathematics | ||
Theory and Applications of Probability and Statistics II | ||
General Electives | 6 | |
Total Hours | 33-34 |
- ^{ 1 }
ECON 2300, ECON 2301, and ECON 2302 satisfy the Core Curriculum requirement for Component Area VIII (Social and Behavioral Sciences).
Code | Title | Hours |
---|---|---|
Major: Concentration (Economics) ^{2} | ||
ECON 2301 | Principles Of Macroeconomics ^{1} | 3 |
ECON 2302 | Principles Of Microeconomics ^{1} | 3 |
ECON 3357 | Intermediate Microeconomics | 3 |
ECON 3372 | Intermediate Macroeconomics | 3 |
ECON 4362 | Econometrics for Business | 3 |
Select three from the following: | 9 | |
ECON 3000-4000 or BANA 4000 | ||
Select two from the following: | 6-7 | |
Discrete Mathematics | ||
Calculus III | ||
Introduction to Mathematics Thought | ||
Theory of Interest | ||
Differential Equations | ||
Numerical Methods | ||
Introductory Analysis | ||
Elementary Analysis | ||
Special Topics in Mathematics | ||
Theory and Applications of Probability and Statistics II | ||
General Electives | 6 | |
Total Hours | 33-34 |
Additional information: Reference the Program Landing Page for additional information, such as cost, delivery format, contact information, or to schedule a visit.
First Year | |||
---|---|---|---|
Fall | Hours | Spring | Hours |
Component Area III | 4 | Component Area III | 4 |
ENGL 1301^{1} | 3 | ENGL 1302^{1} | 3 |
HIST 1301^{2} | 3 | HIST 1302^{2} | 3 |
MATH 1420^{3} | 4 | MATH 1430 | 4 |
14 | 14 | ||
Second Year | |||
Fall | Hours | Spring | Hours |
Component Area IV | 3 | Concentration^{5} | 3 - 4 |
Component Area IX | 3 | COSC 1437 | 4 |
COSC 1436 | 4 | POLS 2306^{4} | 3 |
POLS 2305^{4} | 3 | STAT 3382 | 3 |
STAT 3379 | 3 | STAT 3385 | 3 |
16 | 16-17 | ||
Third Year | |||
Fall | Hours | Spring | Hours |
Component Area V | 3 | Component Area VIII^{6} | 3 |
COSC 3318 | 3 | Concentration ^{5} | 9 |
MATH 3377 | 3 | STAT 4373 | 3 |
STAT 3381 | 3 | ||
STAT 4371 | 3 | ||
15 | 15 | ||
Fourth Year | |||
Fall | Hours | Spring | Hours |
Concentration ^{5} | 9 | BANA 4373 | 3 |
STAT 4374 | 3 | Concentration ^{5} | 12 |
STAT 4390 | 3 | ||
15 | 15 | ||
Total Hours: 120-121 |
- ^{ 1 }
ENGL 1301 and ENGL 1302 satisfy the Core Curriculum requirement for Component Area I (Communications).
- ^{ 2 }
HIST 1301 and HIST 1302 satisfy the Core Curriculum requirement for Component Area VI (U.S. History).
- ^{ 3 }
MATH 1420 satisfies the Core Curriculum requirement for Component Area II (Mathematics) and fulfills the prerequisite requirement for MATH 1430.
- ^{ 4 }
POLS 2305 and POLS 2306 satisfy the Core Curriculum requirement for Component Area VII (Political Science/Government).
- ^{ 5 }
Select one Concentration (Statistics, Computer Science, or Economics) from the options below.
- ^{ 6 }
ECON 2300, ECON 2301, and ECON 2302 satisfy the Core Curriculum Requirement for Component Area VIII (Social and Behavioral Sciences).
Notes
Students must earn a 2.0 minimum overall GPA in all coursework.
Students must meet a 2.0 minimum overall major GPA in all major coursework.
Students must earn a 2.0 minimum SHSU GPA in all coursework.
Students must meet a 2.0 minimum SHSU major GPA in all major coursework.
A minor is not required for this degree program; however, a student has the option to add a minor, but to do so additional semester credits hours may be needed above the degree program’s stated total semester credit hours.
Code | Title | Hours |
---|---|---|
Major: Concentration (Statistics) ^{5} | ||
GEOG 2464 | Introduction to Geographic Information Systems (GIS) | 4 |
ECON 2300 | Introduction To Economics ^{1} | 3 |
or ECON 2301 | Principles Of Macroeconomics | |
or ECON 2302 | Principles Of Microeconomics | |
STAT 4372 | Theory and Applications of Probability and Statistics II | 3 |
Select three from the following: | 9 | |
Statistical Design and Analysis of Experiments | ||
Special Topics in Statistics | ||
Quality Control & Reliability | ||
Time Series and Forecasting | ||
Introduction to Applied Bayesian Analysis | ||
Select three from the following: | 9-10 | |
Discrete Mathematics | ||
Calculus III | ||
Introduction to Mathematics Thought | ||
Theory of Interest | ||
Differential Equations | ||
Numerical Methods | ||
Introductory Analysis | ||
Elementary Analysis | ||
Special Topics in Mathematics | ||
General Electives | 8 | |
Total Hours | 33-34 |
- ^{ 1 }
ECON 2300, ECON 2301, and ECON 2302 satisfy the Core Curriculum requirement for Component Area VIII (Social and Behavioral Sciences).
Code | Title | Hours |
---|---|---|
Major: Concentration (Computer Science) ^{5} | ||
COSC 3337 | Information Systems Design & Management | 3 |
COSC 4320 | System Modeling and Simulation | 3 |
ECON 2300 | Introduction To Economics ^{1} | 3 |
or ECON 2301 | Principles Of Macroeconomics | |
or ECON 2302 | Principles Of Microeconomics | |
Select two from the following: | 6 | |
Special Topics/Programming | ||
Data Structures and Algorithms | ||
Data Mining | ||
Special Topics in Computer Science | ||
Select three from the following: | 9 | |
Statistical Design and Analysis of Experiments | ||
Special Topics in Statistics | ||
Quality Control & Reliability | ||
Time Series and Forecasting | ||
Introduction to Applied Bayesian Analysis | ||
Select two from the following: | 6-7 | |
Discrete Mathematics | ||
Calculus III | ||
Introduction to Mathematics Thought | ||
Theory of Interest | ||
Differential Equations | ||
Numerical Methods | ||
Introductory Analysis | ||
Elementary Analysis | ||
Special Topics in Mathematics | ||
Theory and Applications of Probability and Statistics II | ||
General Electives | 6 | |
Total Hours | 33-34 |
- ^{ 1 }
ECON 2300, ECON 2301, and ECON 2302 satisfy the Core Curriculum requirement for Component Area VIII (Social and Behavioral Sciences).
Code | Title | Hours |
---|---|---|
Major: Concentration (Economics) ^{5} | ||
ECON 2301 | Principles Of Macroeconomics ^{1} | 3 |
ECON 2302 | Principles Of Microeconomics ^{1} | 3 |
ECON 3357 | Intermediate Microeconomics | 3 |
ECON 3372 | Intermediate Macroeconomics | 3 |
ECON 4362 | Econometrics for Business | 3 |
Select three from the following: | 9 | |
ECON 3000-4000 or BANA 4000 | ||
Select two from the following: | 6-7 | |
Discrete Mathematics | ||
Calculus III | ||
Introduction to Mathematics Thought | ||
Theory of Interest | ||
Differential Equations | ||
Numerical Methods | ||
Introductory Analysis | ||
Elementary Analysis | ||
Special Topics in Mathematics | ||
Theory and Applications of Probability and Statistics II | ||
General Electives | 6 | |
Total Hours | 33-34 |
The Texas Higher Education Coordinating Board (THECB) marketable skills initiative is part of the state’s 60x30TX plan and was designed to help students articulate their skills to employers. Marketable skills are those skills valued by employers and/or graduate programs that can be applied in a variety of work or education settings and may include interpersonal, cognitive, and applied skill areas.
The BS in Data Science is designed to provide graduates with the following marketable skills:
- Use critical thinking skills, along with inductive and deductive reasoning, to translate substantive questions into well-defined problems requiring effective, on time solutions.
- Develop the competence and capacity for data collection, data wrangling, and data visualization techniques for pursuing real world problems.
- Utilize programming and database management skills to organize and analyze data effectively, including capabilities for developing statistical/predictive modeling.
- Apply statistical/machine learning techniques for model-building and testing, while also being effective in applying other data science methodologies to provide actionable insights.
- Demonstrate efficient and effective written and oral communication skills necessary for presenting problem solutions and results to both data-oriented and non-data-oriented stakeholders.
These skills will be introduced and continually refined, at the appropriate developmental levels, as students progress through the curriculum.