Porto, Portugal

Python Porto

when 22 July 2024 - 26 July 2024
language English
duration 1 week
credits 3 EC
fee EUR 450

Python is the most popular language for data science, and it is becoming a common job requirement in the financial services industry. This Python Summer School (PSS) aims at providing participants with basic Python skills with a short and Intensive course that requires participants to adopt a hands-on approach, focusing on a significant number of exercises and case studies. The main focus will be the use of Python in financial research and cover topics ranging such as structuring a program, importing data, data handling, data visualization, web scraping and an introduction to unstructured data in a Natural Language Processing approach.

Target group

This Summer School targets postgraduate students (MSc and PhD) with an interest in finance, but it can be extended to final-year undergraduate students.

Course aim

The workshop seeks to equip PhD and MSc students and undergraduate students (advanced level) with the fundamental skills to use Python in a research context. The course is intended for learners who have not yet worked with Python and covers both a general introduction as well as more advanced approaches on data retrieval and processing.

After first reviewing the basics of Python, especially how to set up the development environment and how to implement simple tasks, we focus on tools commonly utilised by researchers (e.g., NumPy, Pandas and Matplotlib). The workshop is comprised of a combination of guided introductions and more independent in-depth exploration. Thus, students have the opportunity to apply the learned concepts to a relevant case study chosen for their scientific breadth and their coverage of different Python features.

We place particular focus on the use of online resources such as the documentation of the utilised Python packages to equip students with the ability to independently handle even more complex issues that are beyond the scope of this workshop.ith the ability to independently handle even more complex issues that are beyond the scope of this workshop.

Learning objectives

Set up Python and manage virtual environments;
Develop replicable data processing workflows and modular “chunks” of code that can be reused in other contexts/projects;
Use online resources to solve issues that are not part of the workshop independently;
Match data sets from different data sources and save the output (packages: NumPy and Pandas);
Web scrapping; and
Conduct text mining tasks (an NLP approach).

Credits info

3 EC
The course is structured in 5 practical sessions where students will learn using a combination of teaching sessions and practical exercises. The focus will be on learning through experience in which participants will have a set of tasks to complete.

The first two days (4 sessions) will be fully dedicated to learning the Python language in a generic financial-oriented research environment. And the last day (1 session) will apply Python to unstructured data using a Natural Language Processing problem.

Fee info

EUR 450: Accommodation is not included
EUR 430: Partner Universities students: 430
Accommodation is not included