Our trainings


Statistics for Data Science and Business Analysis


Topics covered in this training are basic frequency distribution, measures of central tendency, measures of variation, covariance and correlation, permutations and combinations, basic set theory, condictional probability and Bayes' rule, discrete and continuous random variables, Binomial distribution, Poisson distribution, Uniform distribution, Normal distribution, sampling and sampling distributions, Central Limit Theorem, interval estimation, hypothesis testing, simple and multiple regression analysis, ANOVA and some other topics.

Duration: 20 hours (10 classes, 2 hours each)
Time slots: 19:00-21:00 (weekdays), 11:00-13:00 (weekends)
Group size: 10-12 people
Assessment: 1 individual project and 1 individual exam

Probability for Actuarial Science


This training is mainly for the people working or seeking job as a risk analyst in an insurance company or a bank; as an insurance and social security analyst; as a public and private fund analysit.

Topics covered in this training are basic set theory, basic probability theory, permutation and combinations, conditional probability and Bayes' rule, discrete and continuous random variables and probability distributions, moment generating functions, joint and marginal probability distributions, expectation and deviation, covariance and correlation analysis, Central Limit Theorem. All these topics will be explained on real life examples.

Duration: 20 hours (10 classes, 2 hours each)
Time slots: 19:00-21:00 (weekdays), 11:00-13:00 (weekends)
Group size: 10-12 people
Assessment: 2 individual exams

Data Analysis with MS Excel


Microsoft Excel is one of the most widely used solutions for analyzing and visualizing data. Many underestimate the potential of this program, while in reality it can do so much.

In this training you will learn to clean and prepare data; most commonly used statistical and financial functions; Pivot tables; What-if analysis; lookup and merging techniques; charts and visualization techniques; statistical analysis including descriptive statistics, correlation analysis, hypothesis testing; simple and multiple regression analysis .

Duration: 20 hours (10 classes, 2 hours each)
Time slots: 19:00-21:00 (weekdays), 11:00-13:00 (weekends)
Group size: 10 people

Python for Data Science


Python is a powerful programming language widely used in machine learning and data science.

This training will help you to understand core programming principles, learn different types of variables, understand "while" and "for" loops and "if" statements; to learn fundamentals of Python, understand and use lists, loops, tuples, functions, arrays, dictionaries, matrices in Python; understand data frames and data modelling in Python .

Duration: 60 hours (25 classes, 2-3 hours each)
Time slots: 19:00-21:00 (weekdays), 11:00-13:00 (weekends)
Group size: 10 people

R for Data Analysis


R is a widely used statistical programming language in academia and industry. It is a great language for anyone interested in data analysis and data science

This training will help you to understand core programming principles, learn different types of variables, understand "while" and "for" loops and "if" statements; to learn fundamentals of R, understand and use functions, packages and matrices in R; understand data frames and data modelling in R; to perform descriptive analysis in R; to perform comparative analysis with t-tests, ANOVA and multivariate ANOVA; to perform correlation analysis and to test simple and multiple linear regression models.

Duration: 30 hours (15 classes, 2 hours each)
Time slots: 19:00-21:00 (weekdays), 11:00-13:00 (weekends)
Group size: 10 people
Assessment: 2 individual projects

Data Analysis with STATA


This training will help to understand the syntax structure of STATA, create new variables, replace and recode existing variables; perform and interpret descriptive analysis in STATA; to perform comparative analysis with t-tests and ANOVA; to perform correlation analysis and to test simple and multiple linear regression models.

Duration: 24 hours (12 classes, 2 hours each)
Time slots: 19:00-21:00 (weekdays), 11:00-13:00 (weekends)
Group size: 10 people
Assessment projects: 2 individual projects

Data Analysis with SPSS


SPSS is one of the best statistical software for social science, medical and many other research fields. It has very interacitve and user-friendly interface.

This training will help you to define, transform, recode, reverse variables in SPSS; to perform descriptive analysis in SPSS; to perform comparative analysis with t-tests, ANOVA and multivariate ANOVA; to perform correlation analysis and to test simple and multiple linear regression models.

Duration: 20 hours (10 classes, 2 hours each)
Time slots: 19:00-21:00 (weekdays), 11:00-13:00 (weekends)
Group size: 10 people
Assessment: 2 individual projects

Data Visualization with Power BI


Power BI is one of the popular data visualization tools used by most of the corporations. This training will help you to understand Power BI and its components; connect Power BI to variety of datasets, learn data transformation with the query editor; understand and work with Data Model; create reports with different interactive visualization types;.

Duration: 20 hours (10 classes, 2 hours each)
Time slots: 19:00-21:00 (weekdays), 11:00-13:00 (weekends)
Group size: 10 people
Assessment: 2 individual projects

Data Visualization with Tableau


This training will help you to learn Tableau basics; connect various data sets to Tableau; data preparation tools; create maps, various tables, scatterplots and basic/advanced dashboards; joining and blending data; understand and work with Data Model; understand and work with clusters, custom territories and various design features.

Duration: 30 hours (15 classes, 2 hours each)
Time slots: 19:00-21:00 (weekdays), 11:00-13:00 (weekends)
Group size: 10 people
Assessment projects: 2 individual projects

Fundamentals of Data Modeling and Database Design


This training will help you to build data models for your organization; create Entity Relationship Diagrams (ERD) by identifying entities, attributes, relationships and constraints; using data modeling techniques develop database designs.

Duration: 20 hours (10 classes, 2 hours each)
Time slots: 19:00-21:00 (weekdays), 11:00-13:00 (weekends)
Group size: 10-12 people
Assessment: 2 individual and 1 group projects

Research Methods


This training is essential for PhD candidates and young researchers in any field in order to properly conduct any research project. Topics covered in this training will help to formulate research topic and research problem/question; providing evidence; collect and summarize existing literature; define research gap and presenting research contributions; formulate research design; conduct research interviews and questionnaire surveys; identify proper sampling methodology; collect and (de)code data. Trainer will also provide comments and feedbacks on current ongoing research projects of the students, if any.

Duration: 15 hours (5 classes over 2 weeks, 3 hours each)
Time slots: 10:00-13:00 and 14:00-17:00
Group size: 10 students

Academic Writing


This training is essential for PhD candidates and young researchers in any field in order to write their research project in academically proper way. In this training students will learn to properly state research questions/problems; summarizing and properly citing findings in existing literature; preparing interview and survey questions; properly presenting research findings; developing parts of an academic paper including abstract, introduction, literature review and so on; properly stating bibliography. Trainer will also provide comments and feedbacks on current ongoing research projects of the students, if any.

Duration: 15 hours (5 classes over 2 weeks, 3 hours each)
Time slots: 10:00-13:00 and 14:00-17:00
Group size: 10 students

Quantitative Analysis


This training will provide essential skills for data analysis for PhD candidates and young researchers. In this training students will learn to conduct descriptive and inferential analysis; understand measures of central tendency and variation; various discrete and continuous probability distributions; state and test various hypothesis; conduct correlation analysis; run simple and multiple regression analysis.

Duration: 15 hours (5 classes over 2 weeks, 3 hours each)
Time slots: 10:00-13:00 and 14:00-17:00
Group size: 10 students

SAT Quantitative


Our instructors, who have more than 10 years of tutoring experience, offer two type of programs to help you prepare for SAT Exam: regular (8 month) and boot camp (6 week). Detailed information for both is provided below.

Regular

Duration: 96 hours (64 classes, twice a week, 1.5 hours each)
Time slots: 15:00-16:30 or 16:30-18:00 (weekdays)

Boot camp

Duration: 60 hours (20 classes, four times a week, 2.5 hours each)
Time slots: 15:00-17:30 (weekdays)
Group size: 12 students

IB Mathematics


Our instructors, who have more than 10 years of tutoring experience, will help you prepare IB Mathematics, both High and Low level exams. Detailed information is provided below.

High level

Duration: 80 hours (40 classes, twice a week, 2 hours each)
Time slots: 16:00-18:00 (weekdays), 10:00-12:00 (weekends)
Group size: 10 students

Standard level

Duration: 48 hours (32 classes, twice a week, 1.5 hours each)
Time slots: 16:30-18:00 (weekdays), 10:00-11:30 (weekends)
Group size: 12 students

IB Economics


Our instructors, who have more than 10 years of tutoring experience, will help you prepare IB Economics, both High and Low level exams. Detailed information is provided below.

High level

Duration: 80 hours (40 classes, twice a week, 2 hours each)
Time slots: 16:00-18:00 (weekdays), 10:00-12:00 (weekends)
Group size: 10 students

Standard level

Duration: 48 hours (32 classes, twice a week, 1.5 hours each)
Time slots: 16:30-18:00 (weekdays), 10:00-11:30 (weekends)
Group size: 12 students

GRE Quantitative Reasoning


Most of the graduate programs require GRE at admission. We will help you prepare and obtain required scores in GRE Quantitative Reasoning exam. Our instructors are experienced tutors with more than 10 years of experience.

Duration: 80 hours (40 classes, twice a week, 2 hours each)
Time slots: 16:00-18:00 (weekdays), 12:00-14:00 (weekends)
Group size: 10-12 students

GMAT Quantitative Reasoning


If you want to pursue graduate degree in Business programs (MBA/EMBA/PhD) at prestigious universities, high score on GMAT is a must. We will help you prepare and obtain required scores in GMAT Quantitative Reasoning exam. Our instructor aisre experienced GMAT tutor with more than 10 years of experience.

Duration: 80 hours (40 classes, twice a week, 2 hours each)
Time slots: 16:00-18:00 (weekdays), 12:00-14:00 (weekends)
Group size: 10-12 students

CONTACT US
English