Data Science B.S. with Cybersecurity Data Analytics Concentration
Data Science B.S. with Cybersecurity Data Analytics Concentration Eight-Semester Plan
| First Year | Units | |
|---|---|---|
| Fall | Spring | |
| MATH 24004 Calculus I (ACTS Equivalency = MATH 2405) (Satisfies General Education Outcome 2.1)1 | 4 | |
| ENGL 10103 Composition I (ACTS Equivalency = ENGL 1013) (Satisfies General Education Outcome 1.1) | 3 | |
| DASC 10003 Introduction to Data Science | 3 | |
| DASC 11004 Programming Languages for Data Science | 4 | |
| MATH 25004 Calculus II | 4 | |
| ECON 21403 Basic Economics: Theory and Practice (Satisfies General Education Outcome 3.3) | 3 | |
| ENGL 10303 Technical Composition II (ACTS Equivalency = ENGL 1023) (Satisfies General Education Outcome 1.2) | 3 | |
| DASC 12004 Introduction to Object Oriented Programming for Data Science | 4 | |
| DASC 12203 Role of Data Science in Today's World | 3 | |
| Year Total: | 14 | 17 |
| Second Year | Units | |
| Fall | Spring | |
| DASC 25904 Multivariable Math for Data Scientists | 4 | |
| STAT 30133 Introduction to Probability4 or INEG 23203 Probability and Stochastic Processes for Industrial Engineers | 3 | |
| DASC 22103 Data Visualization and Communication | 3 | |
| DASC 21103 Principles and Techniques of Data Science | 3 | |
| State Minimum Core U.S. History or Government Elective (Satisfies General Education Outcome 4.2)2 | 3 | |
| SEVI 20503 Business Foundations (Data Science Majors-only section) | 3 | |
| STAT 30043 Statistical Methods4 or INEG 23104 Statistics for Industrial Engineers I | 3-4 | |
| State Minimum Core Natural Science Elective with Lab (Satisfies General Education Outcome 3.4)2 | 4 | |
| DASC 22003 Data Management and Data Base | 3 | |
| ACCT 20103 Accounting Principles or ACCT 20203 Accounting Principles II | 3 | |
| Year Total: | 16 | 16 |
| Third Year | Units | |
| Fall | Spring | |
| DASC 21303 Data Privacy & Ethics (Satisfies General Education Outcome 5.1) | 3 | |
| DASC 31003 Big Data Analytics with Cloud Computing | 3 | |
| DASC 32203 Cyber Crime and Cyber Terrorism (Cyber Crime and Cyber Terrorism) | 3 | |
| State Minimum Core Social Sciences Elective (General Education Outcomes 3.2 and 3.3)2 | 3 | |
| State Minimum Core Natural Science Elective with Lab (Satisfies General Education Outcome 3.4)2 | 4 | |
| DASC 32003 Optimization Methods in Data Science | 3 | |
| DASC 32103 Statistical Learning | 3 | |
| ISYS 40103 Principles of Data and Cybersecurity | 3 | |
| State Minimum Core Social Sciences Elective (Satisfied General Education Outcomes 3.3 and 4.1)2 | 3 | |
| State Minimum Core Fine Arts Elective (Satisfies General Education Outcome 3.1)2 | 3 | |
| Year Total: | 16 | 15 |
| Fourth Year | Units | |
| Fall | Spring | |
| DASC 48902 Data Science Practicum I | 2 | |
| DASC 41103 Machine Learning | 3 | |
| DASC 41203 Social Problems in Data Science and Analytics | 3 | |
| ISYS 40203 Network and Data Security in a Changing World | 3 | |
| ISYS 40403 Cybersecurity, Crime and Data Privacy Law Fundamentals | 3 | |
| DASC 49903 Data Science Practicum II (Satisfies General Education Outcome 6.1) | 3 | |
| Concentration Elective | 3 | |
| Concentration Elective | 3 | |
| General Education Elective3 | 2-3 | |
| Year Total: | 14 | 12 |
| Total Units in Sequence: | 120 | |
- 1
Students have demonstrated successful completion of the learning indicators identified for learning outcome 2.1 by meeting the prerequisites for MATH 24004.
- 2
Students must complete the State Minimum Core requirements as outlined in the Catalog of Studies. The courses that meet the state minimum core also fulfill many of the university's General Education requirements, although there are additional considerations to satisfy the general education learning outcomes. Students are encouraged to consult with their academic adviser when making course selections.
- 3
Students are required to complete 40 hours of upper-division courses (3000-4000 level). It is recommended that students consult with their adviser when making course selections.
- 4
- Data Science Statistics and Computational Analytics Concentration students are advised to select STAT 30133/STAT 30043 to meet the prerequisites required in the concentration.