Analyze important data
As a data analytics major, you will learn how to find, gather and analyze data to find the trends and information. You'll also learn how to use the data you find to make informed business decisions. Lynn's data analytic's program is unique and uses a project-based approach to analyze complex, real-world problems. Here, you will learn to think analytically, develop creative problem-solving skills and leverage business intelligence to encourage data-driven decision making.
What you'll learn as a data analytics major
- Data analytics fundamentals
- Data mining, visualization and programming
- Advanced business intelligence
Learning doesn’t get more innovative than this.
At Lynn University, we embrace technology by encouraging our students to engage with course content through iPads, and our professors can develop custom course materials.
Data analytics curriculum
This program uses a project-based approach. Students in this program will learn how to gather and analyze data, which can then be used to inform best practices and move the organization toward its strategic vision.
ISM 320 Data Visualization
ISM 420 Data Programming
In this course students will learn how to program for data science using the most up-to-date software. In addition to learning the basics of syntax, variables and operations, students will learn how to handle complex data structures such as vectors, matrices, data frames and lists. Students will dive deeper into the graphical capabilities of the software to create stunning visualizations. Additionally, students will continuously practice their new skills through interactive coding challenges to solve real-world data problems.
ISM 421 Advanced Business Intelligence
In this course students will learn how to use business applications involving explanatory and response variables requiring advanced statistical models that go beyond inferential tools such as confidence intervals and hypothesis testing. Students will learn to use advanced multivariate regression analysis and residual diagnostics, logistic regression, analysis of variance (ANOVA) and multiple analysis of variance (MANOVA), time series modeling and analysis of categorical variables. Students will use advanced statistical packages such Excel, Python, R and/or SPSS to complete various projects including computation and graphing. It is assumed that students have mastery of introductory statistics topics including descriptive tools, inference and ordinary least squares.
Data analytics jobs
The skills you learn can help place you with local and regional companies for internships and job opportunities. In fact, many of our alumni have gone on to intern and work in a variety of successful companies, including:
- Jarden Consumer Solutions
- Modernizing Medicine
- JM Lexus