Data Science B.S. with Supply Chain Analytics
Data Science B.S. with Supply Chain Analytics Concentration
Eight-Semester ProgramÌý
| First Year | Units | |
|---|---|---|
| Fall | Spring | |
| ²Ñ´¡°Õ±áÌý24004 Calculus I (ACTS Equivalency = MATH 2405) (Satisifies General Education Outcome 2.1)1 | 4 | Ìý |
| ENGLÌý10103 Composition I (ACTS Equivalency = ENGL 1013) (Satisifies General Education Outcome 1.1) | 3 | Ìý |
| DASCÌý10003 Introduction to Data Science | 3 | Ìý |
| DASCÌý11004 Programming Languages for Data Science | 4 | Ìý |
| MATHÌý25004 Calculus II | Ìý | 4 |
| ECONÌý21403 Basic Economics: Theory and Practice (Satisfies General Education Outcome 3.3) | Ìý | 3 |
| ENGLÌý10303 Technical Composition II (ACTS Equivalency = ENGL 1023) (Satisifies General Education Outcome 1.2) | Ìý | 3 |
| DASCÌý12004 Introduction to Object Oriented Programming for Data Science | Ìý | 4 |
| DASCÌý12203 Role of Data Science in Today's World | Ìý | 3 |
| Year Total: | 14 | 17 |
| Ìý | ||
| Second Year | Units | |
| Fall | Spring | |
| DASCÌý25904 Multivariable Math for Data Scientists | 4 | Ìý |
| STATÌý30133 Introduction to Probability4 or INEGÌý23203 Probability and Stochastic Processes for Industrial Engineers | 3 | Ìý |
| DASCÌý22103 Data Visualization and Communication | 3 | Ìý |
| DASCÌý21103 Principles and Techniques of Data Science | 3 | Ìý |
| State Minimum Core U.S. History or Government Elective (Satisfies General Education Outcome 4.2)2 | 3 | Ìý |
| SEVIÌý20503 Business Foundations (Data Science Majors-only section) | Ìý | 3 |
| STATÌý30043 Statistical Methods4 or INEGÌý23104 Statistics for Industrial Engineers I | Ìý | 3-4 |
| State Minimum Core Natural Science Elective with Lab (Satisfies General Education Outcome 3.4)2 | Ìý | 4 |
| DASCÌý22003 Data Management and Data Base | Ìý | 3 |
| ACCTÌý20103 Accounting Principles (This pre-req to SYDA Concentration courses uses the "General Elective" to allow a full 21 hours for Concentration courses) | Ìý | 3 |
| Year Total: | 16 | 16 |
| Ìý | ||
| Third Year | Units | |
| Fall | Spring | |
| DASCÌý21303 Data Privacy & Ethics (Satisfies General Education Outcome 5.1) | 3 | Ìý |
| DASCÌý31003 Big Data Analytics with Cloud Computing | 3 | Ìý |
| State Minimum Core Social Sciences Elective (Satisfies General Education Outcomes 3.2 and 3.3)2 | 3 | Ìý |
| State Minimum Core Natural Science Elective with Lab (Satisfies General Education Outcome 3.4)2 | 4 | Ìý |
| SCMTÌý21003 Integrated Supply Chain Management | 3 | Ìý |
| DASCÌý32003 Optimization Methods in Data Science | Ìý | 3 |
| DASCÌý32103 Statistical Learning | Ìý | 3 |
| SCMTÌý34403 DELIVER: Transportation and Distribution Management | Ìý | 3 |
| State Minimum Core Fine Arts Elective (Satisfies General Education Outcome 3.1)2 | Ìý | 3 |
| State Minimum Core Social Sciences Elective (Satisfies General Education Outcomes 3.3 and 4.1)2 | Ìý | 3 |
| Year Total: | 16 | 15 |
| Ìý | ||
| Fourth Year | Units | |
| Fall | Spring | |
| DASCÌý48902 Data Science Practicum I | 2 | Ìý |
| DASCÌý41103 Machine Learning | 3 | Ìý |
| DASCÌý41203 Social Problems in Data Science and Analytics | 3 | Ìý |
| SCMTÌý36103 SOURCE: Procurement and Supply Management | 3 | Ìý |
| SCMTÌý36203 PLAN: Inventory and Forecasting Analytics | 3 | Ìý |
| DASCÌý49903 Data Science Practicum II (Satisifies General Education Outcome 6.1) | Ìý | 3 |
| SCMTÌý36603 MAKE: Supply Chain Process Improvement | Ìý | 3 |
| SCMTÌý46503 Supply Chain Strategy and Change Management | Ìý | 3 |
| Supply Chain Analytics Concentration Elective3 | Ìý | 3 |
| Year Total: | 14 | 12 |
| Ìý | ||
| Total Units in Sequence: | Ìý | 120 |
- 1
Students have demonstrated successful completion of the learning indicators identified for learning outcome 2.1, by meeting the prerequisites for ²Ñ´¡°Õ±áÌý24004.
- 2
Students must complete theÌýState Minimum Core requirementsÌýas outlined in the Catalog of Studies. The courses that meet the state minimum core also fulfill many of the university'sÌýGeneral 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.Ìý
- 3
Students are required to complete 40 hours of upper-division courses (30000-40000 level).Ìý 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 STATÌý30133/STATÌý30043 to meet the prerequisites required in the concentration.