## Courses

**PSYC 2030 - Methods and Statistics in Psychology**

An introductory course for students for students just starting to learn about statistics. The course takes an applied approach where we learn about data collection, management, visualization, before jumping into using statistics to describe and learn from data. By then end of the course we'll know how to answer questions using linear regression.

**PSYC 3400 - Advanced Research Design and Data Analysis**

An advanced course for students looking to build statistical models to answer questions with data. In this course we'll learn Bayesian statistics that gives us the flexibility to build a wide range of regression models. By the end of the course we'll know how to use a causal analysis framework to build generalized linear regressions.

**DASC 5010 - Introduction to Data Science and Analytics in Python I**

An introductory course for students for students looking to learn about data science. This course assumes no knowledge of python or statistics, and will guide students through the typical workflow in a data science project. While learning this workflow we'll develop skills in Python, as well as different machine learning models. This course takes a very hands-on providing students with lots of opportunity to work with datasets that interest them.

**DASC 5011 - Introduction to Data Science and Analytics in Python II**

An advanced course for students looking to learn about how to build deep learning models, and when these models are most effective. This course assumes some background in python and statistics, and will introduce how deep learning models can be used with traditional and non-traditional datasets: e.g., image, and text data.