Source of Image: George Washingto$α♦n University
Program Dates and Courses
Students applying for the→ 2019 GW Summer Progr☆≠ams may select two t ↕↓ypes of programs: General Study Program or Summer Research Experience.
›› General ∑¥Study Program
Dates: July 1 – Augu₹£♥βst 10, 2019
GW offers more than 650 cour©ε ses from over 100 academic £♥areas for students admitted 'in its summer program. Undergraduate s↔×tudents are required to choose 2 courses forφ÷€β 6 credits, and graduate students may choose 1 ×™σor 2 courses for 3 to 6 credits.
Certain courses may not be availab©∞le to visiting students, such as courses in the M∑≥"₽ilken School of Public Health, φ$and GW’s nursing, medi'§cal and law programs. Other ↕≥★courses may be restricted by major.
Students may choose courses from a wide rang₩£φ↑e of academic areas such as Government, Histo πry and Politics, International Rel®↕©↕ations, Public Policy, Law, Physic₹₹s, Bio-medical Engineering, Arts,↑<± Business, Economics, Data Science, Englishφ≠ for Academic Purposes (EAP) etc.
Note: EAP are credit courses aimed at developing γ¶ critical thinking, academic writing↕± and research skills for both undergr®<aduate and graduate students. They are intend<₩ed for non-native EngΩ∞¶lish speakers.
Entry Requirements
›› Undergradua₹♠te and graduate stude∞nts with excellent academic performance f≤∏✘♠rom USIEA’s partner universities
›› TOEFL 8×♠0 or IELTS 6.0

Source of Image: George Washington Uni§εversity
›› Summer Res$λ✔earch Experience
Dates: July 1 – August 10, •↓€2019
This hands-on program is design€αed for international st™÷∏udents who are non-natiβve English speakers to introduce them to conce λpts in cross-disciplinary research in a U.S. univ>™ersity. Students will engage with profβ®≤♥essionals to help solve problems in science and tλ→echnology disciplines, as well as gain skil<≤ls in research and writing techniques. In thi↓↔®s program students will:
- Connect with profe∑¶ssionals in research-focused instit¥♥÷utions.
- Develop skills in problem an☆×←alysis, literature research, teamwork, communicat♠§ion, and presentation.
- Develop research-based writing ski←☆lls including vocabul'€£→ary, source evaluation, docum©entation, and cohesiveness.
- Work in cross-discipli∏♣↑nary teams, using research methodologies to addre₽©ss issues and solve problems"×↓ in areas such as statistics, computer sci≠✘♥ence, mathematics, bioinforα↓matics and more.
Two courses will be offered as part of the ≈↓program:
Course One: Introduc₽₽♥tion to Data Science (3 credits)
This class covers the basic techniques of data sc€σλ'ience, algorithms fo☆♣r data mining and introductory stati♦←stical modeling. Students learn to a€™pply data science principle€÷↓s to disciplines from the →←>natural sciences to social sciences that are δ characterized by the need to man≠♦↓₽age and analyze big data sets.
Field professionals will provide real-←•world problems they are working to solve and↔∑ students will work in groups to d©evelop solutions. Typical areas of natura¶≥l science include astrophys •ics, bioinformatics and mathematic✘γπs. In social sciences, examples include ec™∞onomic forecasting, political campa÷↓©γign analytics and geographicγ$♠< information systems (GIS). As a res♠♠>ult of the course, students w♣γ≥ill gain skills in proble™€m analysis, research, team w↔≥ork and communication.
Course Two: English for Academic ε•σ"Purposes: Academic Wr ₩£iting & Research (3 credits)
This course teaches students the γ♣λprinciples and practices associated with ac∑¶σademic writing in U.S. higher education and suppo♦≥φ₩rts the development "λ÷∏of a specialized skill set for the inteδ™♥ rdisciplinary field of da€• ta science.
The premise of this course is that writing an€★d communication are ke®λ×ys for success in both academic and professi < onal life because they always occur wi™λth specific problems in mind. Through class ac♦ ↔λtivities and materials, st×≠πudents will be able to understand✔♦π↕ and analyze how writing and communα∞ication support typical probl♥$ems and rhetorical situations in ¶≠statistics and data science. Students wil§÷λ>l also learn how to assess and respon←™d to communicative expectations of standard daσ→♥ta science tasks, su↓ ch as asking and documenti™§±ng questions, describing an<✘d explaining data and discussin• g/presenting research on topics of their choice.
This course is taught by experienced facult©♠y in the English for Acade✘>σmic Purposes (EAP) p★&rogram, and the small clasλ♠☆∏s size offers many opportunities for stude λ∑nts to interact with classλαmates and the professor in a φ<βπsupportive classroom environment.
Entry Requirements
›› Und ©ergraduate and graduate students with "¥excellent academic p¶≤₹erformance from USIEA’ s partner universities.
›› ¶↑€↓;Pre-Requisites: Students should have taken a course in"♥∏ introductory statistics. Progr≈★amming experience is desirable, ideally with R.↑®& STEM courses are a plus∞↑".
›› TOEFL 80, orλ↓ IELTS 6.0, or CET-4 493
›› Pre-Requisites: Students ™₩↕∑should have taken a course in introductory st≥₽atistics. Programmingε experience is desirable, ideally with R. STEM§φ∑ courses are a plus.
›› TOEFγ'↕←L 80, or IELTS 6.0, or CET-4 493