Become your Organization's Data Superhero
With a unique blend of theory and application, our graduate level data analytics program prepares the analyst to solve real business problems using cutting-edge tools. Students are trained in lab-based courses to extract, clean, and analyze data using parametric, non-parametric, and machine learning methods.
Further, classes are structured to replicate the real world as much as possible. Students will interact with large, messy datasets housed in SQL databases, combine them with other sources such as flat files, and write algorithmic cleaning procedures.
The data analytics program trains the analyst not just in today's methods but gives them the foundation to learn new procedures in the future.
| Course Number | Course Title | Description | Credits | ⓘ |
|---|---|---|---|---|
| ECON 8320 | Tools for Data Analysis |
Covers basic principles of programming languages, as well as libraries useful in collecting, cleaning and analyzing data to answer research questions. While the course uses Python, the student should be able to move to other languages frequently used in data analysis using the principles taught in this course. |
3 | ↓ |
| ECON 8310 | Business Forecasting |
The course will cover forecasting tools and applications applied to business settings using Python. Traditional Econometric foresting methods as well as predictive analytics and machine learning approaches are covered in the course. |
3 | n/a |
| ECON 8330 | Data Analysis from Scratch |
This class trains the student to build all estimators from scratch. Additionally, it introduces numerous non-parametric, machine learning, and simulation techniques. This approach to econometrics results in a stronger understanding of statistical assumptions and methods, a better understanding of when a method is appropriate, and stronger programming abilities. |
3 | ↓ |
| If a course description has been provided by the course instructor, you can download the description by clicking the ↓ in the ⓘ column. | ||||