Kursy Szkoleniowe

Join us for the 2025 Stata Summer School, a dynamic, four-day online training series designed to equip researchers, data analysts, and students with the skills to manage, visualise, and analyse data effectively using Stata. Whether you're brand new to Stata or looking to refine your statistical analysis skills, this summer school offers flexible learning opportunities tailored to your needs.

Learn the fundamentals of EViews, a leading econometric software, and gain an introduction to data handling, programming, and regression modelling. This hands-on course covers Classical Linear Regression Model (CLRM) analysis, diagnostic tests, and model refinement techniques.

Learn how to analyse panel data using EViews in this comprehensive two-day online course. Covering both static and dynamic linear models with exogenous and endogenous variables, you'll explore core econometric techniques such as fixed effects, random effects, GMM, and GLS. The course emphasizes applied learning through hands-on sessions using real-world macro and micro datasets. By the end, you’ll be able to prepare panel datasets, test for serial correlation, select suitable models, and interpret results confidently using EViews.

Don't miss our in-person summer school at the University of Cambridge, hosted at the scenic and modern Churchill College, featuring courses on Difference in Differences, Machine Learning and Causal Inference

Learn how to analyse longitudinal data with Stata in this comprehensive two-day online course. Covering static and dynamic linear models, you'll explore key methodologies, interpret results, and gain hands-on experience through practical examples and exercises. By the end, you'll be equipped to prepare panel data, select appropriate models, and obtain parameter estimates with confidence.

This course provides a foundational understanding of statistics essential for studying econometrics. It covers data collection, analysis, probability, hypothesis testing, and the use of statistical software for real-world applications.

Learn to create clear, impactful graphs in Stata in this two-day workshop. From univariate plots to advanced animations, gain practical skills to visualise and present your data effectively using Stata’s built-in and advanced graphing tools.

This two-day online course introduces participants to web data scraping using Python within Stata. It covers the basics of Python and HTML, and teaches how to retrieve and analyse online data through practical, hands-on exercises. By the end, attendees will be equipped to write basic Python code and apply it to their own data scraping tasks in Stata.

Theory and Practice of Modelling Stationary Data in EViews is a one-day advanced course on time series analysis, with a focus on ARMA and VAR models. Participants will explore stationarity, unit root testing, and the practical implementation of univariate and multivariate forecasting models in EViews. From the Box-Jenkins methodology to forecasting with stationary VARs, this hands-on course equips attendees with the skills needed to model and predict macroeconomic variables—such as inflation—using atheoretical models. Ideal for analysts and researchers working with macroeconomic time series data.

This comprehensive introductory mathematics course is designed to equip students with the foundational knowledge and skills necessary to excel in econometrics courses, including calculus and linear algebra. Through rigorous instruction, students will develop a deep understanding of mathematical concepts and their applications.

Modelling Non-Stationary Data in EViews is a one-day advanced course on time series analysis, focusing on unit roots, cointegration, and the Vector Error Correction Model (VECM). Through hands-on sessions, participants will learn to apply key econometric techniques in EViews for real-world data analysis.

Discover recent developments in causal inference and program evaluation using Stata. This course equips participants with the latest econometric methods, including difference-in-differences, synthetic control methods, and dose-response models. Learn to design, implement, and interpret robust policy evaluations through hands-on practical sessions.