Learners are trained to evaluate health promotion and education programs with a strong emphasis on data-driven approaches. They can design and assess mental health initiatives, collect and analyze data, and provide evidence-based recommendations to improve organizational wellbeing strategies.

This experience is designed for junior-level learners with a focus on Industrial Psychology, equipping them with the skills to analyze and improve workplace behavior and performance. Learners will apply their knowledge of employee motivation, conflict resolution, and team building to real-world challenges faced by companies. By conducting interviews with company leaders and analyzing organizational data, they will develop evidence-based recommendations that align with company culture and enhance workplace dynamics.

Looking to elevate your organization, and bring it to the next level? Bring on students from Mercy University to be your student-consultants, in a project-based experience. Students will work on one main data analysis-visualization project over the course of a term, connecting with you as needed with virtual communication tools. Students in this program focus on the collection of, and analysis of, data. They learn how to objectively manipulate data into useable data sets, including visual data analytics to help make data backed decisions for more thorough analysis, and use predictive modelling to ascertain future patterns and trends.

Looking to elevate your organization, and bring it to the next level? Bring on learners from Mercy University to be your learner-consultants, in a project-based experience. Learners will work on one main project over the experience of the semester, connecting with you as needed with virtual communication tools. Learners in this program/experience will use practical application of Python libraries for storing, manipulating, and analyzing data. Students will become proficient in popular packages such as IPython, NumPy, Pandas, Matplotlib, and Scikit-Learn, among others. Through hands-on practice and projects, students will learn how to manipulate, transform, and clean data; visualize various types of data; and build basic statistical (Exploratory Data Analysis) or machine learning models (regression, etc.).