Introduction to Python

Introduction to Python

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University of Westminster Marylebone Hall

35 Marylebone Road



United Kingdom

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This in-person and on-demand course provides an introduction to Python, one of the world's most versatile programming languages.

About this event

Data analysis is becoming increasingly computational. This is true for empirical and theoretical research both in, and outside academia. The command of programming languages is gaining importance. Python provides an excellent tool for practitioners and academics to tackle this. It is simple, versatile, and, best of all, it’s for free!

This course is designed to introduce Python programming as a tool for data analysis. It is aimed at professionals using data analysis as part of their work, be it economists, financial professionals or statisticians. It gives an overview of what Python is and how it can be used. The course introduces basic programming techniques and the most useful tools that data analysts can use in their day-to-day work such as directly downloading data from online sources; managing, combining and describing datasets; and managing projects with gantt charts. The focus is on data-science applications, in particular data management, analysis and visualisation. The course shows how using Python rather than other spreadsheet or econometric packages can save you time in your daily work.

Who should come?

This course provides an accessible introduction to Python. Some basic knowledge of statistics and/or econometrics would be useful but is not required to follow the course.

The course does also not require any prior programming experience. Course participants will need to bring their own laptops (Windows, MAC OS and Linux).

The course includes interactive exercises and case studies to help illustrate key concepts and ensure the course is engaging and relevant.

Key learning outcomes

At the end of this course, you will be able to:

  • Setup Python and use different tools to write python scripts and interactive notebook files;
  • Understand and apply main objects and structures in Python and basic programming techniques that are useful across many applications in Python and other languages;
  • Understand how to integrate Python into your established workflows;
  • Use Python for data handling in one-, two-, and multi-dimensional settings;
  • Use Python for data analysis and visualisation;
  • Use Python to download data from different databases; and
  • Deepen your learning outcomes by following the complementary on-demand course Introduction to Python offered by SPE Courses.

Course delivery

The course is delivered in person over one day 09.30am – 5pm Tuesday 5th July 2022 at the University of Westminster, Marylebone Campus, 35 Marylebone Road, London NW1 5LS. It will be presented by Paul Wohlfarth.

In addition to the one-day course, all participants will be given access to the SPE Courses' on-demand Introduction to Python course also presented by Paul Wohlfarth.

A copy of the slides will be circulated after the course.

Full joining instructions will be sent ahead of the course, including on how to install Python on your laptop prior to the course.


The price for the course is £400 + VAT. SPE Courses are delivered by Economicsense Ltd. Your invoice will state the VAT paid and Economicsense Ltd's VAT Registration Number of 376550278.

You can also invoice directly - please email for more information.

The tutor

Paul Wohlfarth is Assistant Professor at Solbridge International School of Business (South Korea) and holds a PhD from Birkbeck College, University of London. Paul specialises in Monetary Economics, Financial Economics, Econometrics, and Chinese Development.

SPE Courses

The Society of Professional Economists is collaborating with Economicsense to deliver courses to professional economists - SPE Courses. The Society of Professional Economists is the leading organisation serving professional economists in the UK and Europe.

Further information

Please feel free to contact us directly for more information.

Telephone: +44 7910 384755


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