About Python

Python is one of the most popular programming languages and provides an excellent tool for practitioners and academics to analyse, manipulate and visualise data. It is simple, versatile, and, best of all, it’s for free!

About this course

The course starts by giving an overview of how programming languages such as Python, R, Java, Fortran and tools like Excel are used for data analysis. It presents the different use cases, similarities and major differences and sets out how data analysis is changing with use of Artificial Intelligence (AI).

The course then introduces Python programming as a tool for data analysis. The course discusses 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 accessing various further application programming interfaces (API) through Python. The course will also cover using AI to support coding in Python.

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 not require any prior programming experience. Course participants will need to bring their own laptops and install Python ahead of the course - full instructions will be given. All standard operating systems (Windows, MAC OS and Linux) are supported.

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;
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
Use AI in Python.

Course delivery

The course will be delivered in person over two days on 9th and 10th July 2024, from 9.30am to 4:30pm at Mary Sumner House, 24 Tufton Street London SW1P 3RB.

The course will be presented by Dr Paul Wohlfarth. Paul holds a PhD in Finance and Economics from the University of London and is Assistant Professor at SolBridge International School of Business in Korea. Paul specialises in Monetary Economics, Financial Economics, Econometrics, and Chinese Development. A copy of the slides will be circulated after the course.

Full joining instructions will be sent ahead of the course.

Course participants will need to install Python on their laptop prior to the course. Instructions on how to do that will be provided prior to the course.

Price

The price for the course is £500 + 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 specourses@economicsense.co.uk for more information.

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

Email: specourses@economicsense.co.uk

SPE Courses: Introduction to Python