The GRE Program is an intensive hybrid learning program for eligible citizens of Turkmenistan. The program is designed to help you improve necessary skills to get you ready for the Graduate Record Examination (GRE), graduate school application process, and graduate-level coursework. This course includes preparation aimed at all components of GRE (Analytical Writing, Verbal Reasoning, Quantitative Reasoning), Academic Reading and Writing, and applying for admission to a U.S. graduate school. The course is taught via a hybrid model which combines online and in-person learning.

There are two rounds of application process per year: December-January for spring intake and June-July for fall intake. Announcements about applications are posted here.
If you’d like to apply, please be sure to check our website to see the announcements.

For more information contact us at:
Gorogly street 48A, Ashgabat, Turkmenistan

If you’d like to prepare before applying to the next intake, here are some tips and recommendations on improving your skills for GRE program and graduate-level studies:

Verbal Reasoning and Academic Reading and Writing:

  • Read non-fiction and science in English
  • Improve your English language skills to Advanced level (writing, speaking, reading, listening)

Math: Khan Academy (source: (ets website does not always open, so it might be a good idea to try to keep this table below)

GRE Math Review Topic Relevant Section on Khan Academy Site
1.1 Integers
1.2 Fractions
1.3 Exponents and Roots
1.4 Decimals
1.5 Real Numbers
1.6 Ratio
1.7 Percent
Sections 2.1 through 2.9
2.1 Operations with Algebraic Expressions
2.2 Rules of Exponents
2.3 Solving Linear Equations
2.4 Solving Quadratic Equations
2.5 Solving Linear Inequalities
2.6 Functions
2.7 Applications
2.8 Coordinate Geometry
2.9 Graphs of Functions
3.1 Lines and Angles
3.2 Polygons
3.3 Triangles
3.4 Quadrilaterals
3.5 Circles
3.6 Three-Dimensional Figures
4.1 Graphical Methods for Describing Data
4.2 Numerical Methods for Describing Data
4.3 Counting Methods
4.4 Probability
4.5 Distributions of Data, Random Variables, and Probability Distributions
4.6 Data Interpretation Examples