New York University
Quant III (POLGA 2251)
(TA; Fall 2018, Fall 2017) 
Advanced graduatelevel methods course covering MLE theory and applications, Bayesian and nonparametric statistics

Data Teaching Assistant (POLUA.8000)
(TA; Spring 2016, Fall 2016) 
Advice and practical help to undergraduate students with data manipulation, research design and interpretation of their results.

Data Science and Social Science
(TA; January 2022, 2016) 
An NYU threeday short course prepared by Pablo Barbera, Dan Cervone, and Alex Hanna for IHDSC’s IESPIRT program and PRIISM.
Covered topics at the intersection of Data Science and Social Science. Data munging, visualization, basic descriptives, basic classification, network analysis, and Webscraping in R. 
Quantitative Methods in Political Science (POLUA.800 )
(recitations, 2015) 
An introductory course in statistical methods for undergraduate students majoring in Political Science.
Covers basic descriptive statistics, correlation and linear regression. Provides an introduction to the theory of hypothesis testing and confidence intervals. Computations in Stata. 
Higher School of Economics (Moscow, Russia)
An introduction to Comparative Politics. No prerequisites.
This course provides a gentle introduction to a broad range of topics in Comparative Politics (political regimes, regime change, political parties and party systems, political ideologies, political culture, electoral behavior). 
Introduction to Math in Political Science
(recitations, 2008 – 2012) in Russian 
An introductory course with no prerequisites.
This course illustrates a broad range of applications of math in the social sciences, including basics of opinion polls design and analysis, demographic models, Markov chains for modeling dynamics, visualization of statistical associations between variables, Simpson paradox, etc. 
A standard matrixbased course in econometrics covering OLS regression under Markov  Gauss assumptions and deviations from them (HAC standard errors, FGLS), diagnostics (functional form, heteroskedasticity, influential observations ), model selection (Rsquared and its criticisms, adjusted Rsquared, AIC, BIC, Davidson  MacKinnon J test for nonnested models, CrossValidation). Special attention devoted to endogeneity and the use of instrumental variables.
Computations and simulations in Stata. 
An introductory course. Topics in probability include basic probability rules, random variables (distribution functions, probability mass and density functions, expectation and variance, quantiles), distributions (binomial, Poisson, normal) and limit theorems (LLN and CLT) without proofs.
Topics in Statistics range from basic descriptive stats to statistical inference (Null Hypothesis Significance Testing and confidence intervals). A special focus on nonparametric tests including sign, Wilcoxon and chisquare tests. 
Data Analysis in SPSS
(recitations, 2008 – 2012) in Russian 
An applied stats course for undergrads majoring in Political Science.
Covers basics of SPSS interface, data manipulation, visualization, descriptive statistics. Methods of statistical analysis covered in this course include chisquare test for nominal variables, Pearson and Spearman correlation, ttest and ANOVA, Kolmogorov  Smirnov twosample test and Shapiro  Wilk normality test, Wilcoxon and Kruskal  Wallis tests, linear regression and general linear model. 
Multivariate Data Analysis
(lectures, recitations, 2010 – 2011) in Russian 
An intermediate stats course for undergraduate students.
The course is matrix algebra based and covers multiple regression, principal components and cluster analysis with a double focus on both theory and applications. Students analyze real data using Stata and write a substantive term paper based on their analysis. 