Bachelor’s Degree in Data Science
Data Science is a dynamic and rapidly changing field where new approaches, content, and techniques for manipulating data are constantly being introduced. It uses tools from Computer Science and Statistics to analyze large amounts of raw data to discover patterns, relationships, and insights, and inform decisions in multiple industries, domains, and contexts.
You will have unmatched opportunities at Arcadia to deliberate data-driven analysis and decision-making processes.
You are taught to think quantitatively, analytically, and independently through a highly customizable program and stand out from others with these unique opportunities:
- Master statistics, R, and Python for data science applications.
- Get involved in AI, machine learning, and data mining experiences.
- Apply modern data science techniques to drive business decisions.
- Conduct research and participate in competitions.
- Prepare for interviews and research experiences.
What’s the Difference Between a BA and a BS?
The Bachelor’s of Arts in Data Science has fewer required mathematics courses and requirements, which provides the opportunity for students to add minors or even a second major in another field.
The Bachelor’s of Science in Data Science is more extensive and prepares students to pursue data science jobs in the industry, as well as graduate studies in data science.
Both programs include opportunities to select major electives from a number of disciplines where students can enhance their skills in the application of data science tools and techniques to a specific domain.
Learn basic statistical techniques and their applications to the sciences, social sciences and business administration. It includes the collection and presentation of data, measures of central tendency and variability, probability, sampling distributions, confidence intervals, hypothesis testing, correlation and regression, and introduction to analysis of variance.
Introduction to Data Science with R
Study data science and analytics techniques using R. Students will learn the essential concepts of R programming. They will use tools and various packages in R to perform data cleaning, processing and visualization. They will also learn basic statistics and machine learning techniques to conduct data analysis. Students from non-computer science majors are welcome.
Introduction to Data Science with Python
Study data science and analytics techniques using Python. Students will learn the essential concepts of python programming. They will use python tools to perform data exploration, cleaning, manipulation and visualization. They will also learn basic statistics and machine learning techniques to conduct data analysis. Students from non-computer Science majors are welcome.
Introduction to Data Mining
Explore the key concepts, tasks, and techniques of data mining. It focuses on providing students with the knowledge needed to manipulate and extract new information from large amounts of data. Topics will include data preprocessing and feature selection, classification, cluster analysis, association analysis, evaluation and validation of data mining results, as well as scalability.