Participants will attend various data science workshops throughout the 10-week program. Each workshop will include preparatory activities and some didactic material, but will primarily entail active learning through problem solving, simulation, case studies, and small and large group discussion. The common goal of all of the workshops is two-fold: to provide basic, useful skills for the students’ summer research and further academic studies, and to open the student’s eyes to the value of data science in biological and diverse non-biological applications.
Current Workshops
- Data Management. Students will be introduced into the basic data management skills and later will explore the basics of documentation, cloud-based storage, and preservation/backup along with modern data plan management expectations through this workshop.
- R Programming. This workshop will enable students to learn R through R Studio and to recognize the broader value and applications of R; R will then be used in subsequent workshops and students may additionally use R in their research.
- Big Data and Publicly Accessible Datasets. Students will be introduced in to examples of big data in biological science and bioinformatics, such as genomics and bio-geographic information systems and will be taught how these big data being analyzed and used in their research projects.
- Data Analytics – Traditional and Contemporary. These workshops are to teach the concepts of traditional statistics as well as modern approaches in data analytics, including machine learning and artificial intelligence.
- Data Analytics – Image Processing. Students will learn modern image processing software tools, algorithms and applications, many of which they will incorporate into their research.
- Data visualization – Traditional and Cognitive practices. This workshop will review the central concepts of graphing, such as error bars, bar vs whisker-plot, and scatterplot with trend fitting using modern software tools. This workshop will also provide an overview of the cognitive and perceptual processes involved in using these displays, with an applied focus on graph design and interpretation for biological inquiry.
- Careers in Data Science. A couple of workshops will be conducted to explore the various career options in data science, in both biological and non-biological fields as well as non-scientific examples of data analytics and visualization to demonstrate the widespread value of data science methods.
Biology Department
