Courses

Introduction to Stata (CEST Time)

25 October 2019 Warsaw University, Department of Economics, ul.Długa 44/50, Warszawa Half day (25th October 2019 - 25th October 2019) Stata

This course provides basic concepts of data management and how to do it efficiently using Stata. We provide several examples and use learning by doing techniques. The course focuses on available Stata commands and additional resources provided by the Stata-users community.

Advances in Causal Inference using Stata

28 - 29 October 2019 Cass Business School, 106 Bunhill Row, London 2 days (28th October 2019 - 29th October 2019) Stata

Econometric modelling for causal inference and program evaluation have witnessed a tremendous development in the last decade, with new approaches and methods addressing an expanding set of challenging problems, both in medical and the social sciences. This course covers some recent developments in causal inference and program evaluation using Stata.

An Introduction to Machine Learning using Stata (EST Time)

9 - 11 December 2019 New Horizons, Computer Learning Centre, New York City, USA 3 days (9th December 2019 - 11th December 2019) Stata

This course is a primer to machine learning techniques using Stata. Stata owns today various packages to perform machine learning which are however poorly known to many Stata users. This course fills this gap by making participants familiar with (and knowledgeable of) Stata potential to draw knowledge and value form row, large, and possibly noisy data. The teaching approach will be based on the graphical language and intuition more than on algebra. The training will make use of instructional as well as real-world examples, and will balance evenly theory and practical sessions.

Introduction to Time Series Analysis with Stata (Online Course - EST Time)

1 March & 24 May 2019 Online Half day (1st March 2019 - 24th May 2019) Stata

Our web based Introduction to Time Series Analysis with Stata course provides an introduction to most important Stata’s Time Series Commands. The course is ideal for beginner/intermediate level user who wants to learn how to analyse time-series data and estimate univariate time-series models.

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