Summer Research Experience

Cross-disciplinary principles of data science and academic writing for research purposes

International students in a classroom

Program Dates: July 1 - August 10, 2018


 

This hands-on program is designed for international students who are English language learners to introduce them to concepts in cross-disciplinary research in a U.S. university. Students will engage with professionals to help solve problems in science and technology disciplines, as well as gain skills in research and writing techniques. In this program students will:

  • Connect with professionals in research-focused institutions.

  • Develop skills in problem analysis, literature research, teamwork, communication, and presentation.

  • Develop research-based writing skills including vocabulary, source evaluation, documentation, and cohesiveness.

  • Work in cross-disciplinary teams, using research methodologies to address issues and solve problems in areas such as statistics, computer science, mathematics, bioinformatics and more.

Flyers in Other Languages

Download the Summer Research Experience flyer in one of our available translations:

Courses

Two courses will be offered as part of the program:

INTRODUCTION TO DATA SCIENCE

This class covers the basic techniques of data science, algorithms for data mining and introductory statistical modeling. Students learn to apply data science principles to disciplines from the natural sciences to social sciences that are characterized by the need to manage and analyze big data sets.

Field professionals will provide real-world problems they are working to solve and students will work in groups to develop solutions. Typical areas of natural science include astrophysics, bioinformatics and mathematics. In social sciences, examples include economic forecasting, political campaign analytics and geographic information systems (GIS). As a result of the course, students will gain skills in problem analysis, research, team work and communication.

ENGLISH FOR ACADEMIC PURPOSES: ACADEMIC WRITING & RESEARCH

Intended for non-native English speakers, this course teaches students the principles and practices associated with academic writing in U.S. higher education and supports the development of a specialized skill set for the interdisciplinary field of data science.

The premise of this course is that writing and communication are key for success in both academic and professional life because they always occur with specific problems in mind. Through class activities and materials, students will be able to understand and analyze how writing and communication support typical problems and rhetorical situations in statistics and data science. Students will also learn how to assess and respond to communicative expectations of standard data science tasks, such as asking and documenting questions, describing and explaining data and discussing/presenting research on topics of their choice.

This course is taught by experienced faculty in the English for Academic Purposes (EAP) program, and the small class size offers many opportunities for students to interact with classmates and the professor in a supportive classroom environment.

Pre-Requisites: Students should have taken a course in introductory statistics. Programming experience is desirable, ideally with R. STEM courses are a plus.

Tuition and fees

Tuition & Fees

International Summer at GW students are billed by credit hour for tuition, with additional program-related fees to cover the costs of supplemental aspects of the program.

See all associated tuition and fees
Visa sponsorship

Visa Requirements

Visiting international students not currently studying or working in the U.S. can apply for visa sponsorship to study at GW over the summer.

Learn more about visa requirements
Chat with us via Skype

Skype Chat Hours

We are eager to get to know you and answer your questions about summer courses, visa processing, campus life and more. Add gwsummer to your contact list and instant message us during our Skype chat hours: Mondays, 2:30-3:30pm & Wednesdays, 9:00-10:00am EST. Please note that we follow the university's holiday schedule (PDF).