Students with a minor in Applied Data Science will receive essential training in computer science, mathematics and statistics in order to apply methods of modern data science within their major field of study.
Learning Objectives
Upon successful completion, students will be able to:
- Perform essential data handling practices in python and R.
- Identify basic mathematical and statistical concepts underpinning modern data science.
- Perform basic analyses using modern data science software.
- Interpret and present the results in the context of their major course of study.
Effective Fall 2020
Students must satisfactorily complete the total credits required for the minor. Minors and interdisciplinary minors require 12 or more upper-division (300- to 400-level) credits.
Additional coursework may be required due to prerequisites.
| Code | Title | Credits |
|---|---|---|
| CS 152 | Python for STEM | 2 |
| DSCI 335 | Inferential Reasoning in Data Analysis | 3 |
| DSCI 369 | Linear Algebra for Data Science | 4 |
| STAT 158 | Introduction to R Programming | 1 |
| STAT 301 | Introduction to Applied Statistical Methods | 3 |
| or STAT 307 | Introduction to Biostatistics | |
| or STAT 315 | Intro to Theory and Practice of Statistics | |
| STAT 341 | Statistical Data Analysis I | 3 |
| Elective (select a minimum of 6 credits from the list below) | 6 | |
| Program Total Credits: | 22 | |
Electives
| Code | Title | Credits |
|---|---|---|
| AREC 335/ECON 335 | Introduction to Econometrics | 3 |
| BZ 346 | Population and Evolutionary Genetics | 3 |
| BZ 350 | Molecular and General Genetics | 4 |
| BZ 425 | Conservation and Population Genomics | 3 |
| BZ 466 | Biological Basis of Animal Behavior | 4 |
| CS 345 | Machine Learning Foundations and Practice | 3 |
| ERHS 332 | Principles of Epidemiology | 3 |
| ERHS 430 | Human Disease and the Environment | 3 |
| ESS 330 | Quantitative Reasoning for Ecosystem Science | 3 |
| F 321 | Forest Biometry | 3 |
| FW 370 | Design of Fish and Wildlife Projects | 3 |
| FW 401 | Fishery Science | 3 |
| FW 455 | Principles of Conservation Biology | 3 |
| FW 469 | Conservation and Management of Large Mammals | 3 |
| FW 475 | Conservation Decision Making | 3 |
| GEOL 454 | Geomorphology | 4 |
| HDFS 350 | Applied Research Methods | 3 |
| MKT 410 | Marketing Research | 3 |
| NR 421 | Natural Resources Sampling | 3 |
| PSY 250 | Research Design and Analysis I | 3 |
| PSY 350 | Research Design and Analysis II | 3 |
| RS 432 | Rangeland Measurements and Monitoring | 2 |
| SOWK 300 | Research in Applied Professions | 3 |
| STAT 305 | Sampling Techniques | 3 |
| STAT 342 | Statistical Data Analysis II | 3 |
| WR 416 | Land Use Hydrology | 3 |