Data Science B.S. with Biomedical and Healthcare Informatics Concentration
Data Science B.S. with Biomedical and Healthcare Informatics Concentration Eight-Semester Program
| First Year | Units | |
|---|---|---|
| Fall | Spring | |
| MATH 24004 Calculus I (ACTS Equivalency = MATH 2405) (Satisfies General Education Outcome 2.1 )1 | 4 | |
| Satisfies General Education Outcome 3.4: | ||
| CHEM 14103 University Chemistry I (ACTS Equivalency = CHEM 1414 Lecture) & CHEM 14101 University Chemistry I Laboratory (ACTS Equivalency = CHEM 1414 Lab) | 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 | |
| Satisfies General Education Outcome 3.4: | ||
| PHYS 20304 University Physics I (ACTS Equivalency = PHYS 2034) (Satisfies General Education Outcome 3.4) | 4 | |
| 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: | 18 | 18 |
| 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 | |
| BMEG 26104 Introduction to Biomedical Engineering | 4 | |
| SEVI 20503 Business Foundations (Data Science Majors-only section) | 3 | |
| STAT 30043 Statistical Methods4 or INEG 23104 Statistics for Industrial Engineers I | 3-4 | |
| DASC 22003 Data Management and Data Base | 3 | |
| CHEM 14203 University Chemistry II (ACTS Equivalency = CHEM 1424 Lecture) | 3 | |
| Year Total: | 17 | 12 |
| 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 | |
| BIOL 24103 Human Physiology (ACTS Equivalency = BIOL 2414 Lecture) | 3 | |
| ECON 21403 Basic Economics: Theory and Practice (Satisfies General Education Outcome 3.3) | 3 | |
| State Minimum Core Social Sciences Elective (Satisfies General Education Outcomes 3.2 and 3.3)2 | 3 | |
| DASC 32003 Optimization Methods in Data Science | 3 | |
| DASC 32103 Statistical Learning | 3 | |
| BMEG 38001 Clinical Observations and Needs Finding | 1 | |
| State Minimum Core Fine Arts Elective (Satisfies General Outcome 3.1)2 | 3 | |
| State Minimum Core Social Sciences Elective (Satisfies General Education Outcomes 3.3 and 4.1) 2 | 3 | |
| Year Total: | 15 | 13 |
| 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 | |
| Concentration Elective Course | 1 | |
| Concentration Elective Course | 3 | |
| DASC 49903 Data Science Practicum II (Satisfies General Education Outcome 6.1) | 3 | |
| Concentration Elective Course | 3 | |
| Concentration Elective Course | 3 | |
| State Minimum Core U.S. History or Government Elective (Satisfies General Education Outcome 4.2)2 | 3 | |
| General Elective Course3 | 2-3 | |
| Year Total: | 12 | 15 |
| 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.