Introduction to Python

Duration: 12h / 3 days

Date: 27 February - 28 February - 2 March

Time: 9:30 - 14:00

Level: Beginner

Format: Presential

Available places: 15-20

Course Description

Introduction to Python programming language for statistical analysis and visualization. During the course, we will learn the basics of the python language, as well as some of the most useful packages for statistical analysis and biomedical applications. In addition, we will learn how to work with python from different environments and using different visualization tools.

Why should you attend the course?

Python is one of the most popular programming languages in the world, being used by hundreds of thousands of programmers around the world in all kinds of applications. A big influencing factor is that python is intuitive and easy to start with. The maturity of python has provided a very strong community, good documentation and cutting edge software using python as the backbone. Almost any tool that you can need has an implementation in python! By the end of the tutorial, you will have the tools to dig deeper into the python language and start performing analysis with your own data.

Prerequisites

No programming knowledge is required, although you should be familiar with how to install software (python) in your computer and some additional software. Instructions to set up your computer will be provided before the start of the course. You should bring your own laptop.

Schedule

Day 1:

• Python environments: Jupyter notebooks, Python files

• Basic Python structures: Variables, Lists and Dictionaries

• The basics of python code: conditionals, loops, functions and packages

Day 2:

• Libraries: matplotlib and seaborn 

• Libraries: numpy, scipy and skimage 

• Libraries: pandas

• Hands-on real data! Starting the projects

Day 3: 

• Libraries: Sklearn 

• How to structure code: good practises and reproducibility

• Hands-on real data! Solving doubts about the projects

• Where to go from here and final remarks

Class Pace 

We will provide almost self-contained lecture notes as well as code, so you are able to follow and return to any missed point during the lectures. We will provide hands-on examples to wrap up the sections as we go over them. 

References

• Lecture notes

• https://python.land/python-tutorial

• Alex Campbell (2021). Python for Beginners: Comprehensive Guide to the Basics of Programming, Machine Learning, Data Science and Analysis with Python. Ebook

Short biography 

Gabriel Torregrosa is a PhD candidate in the Dynamical Systems Biology laboratory at Universitat Pompeu Fabra. Previously, he did the Master in Theoretical and Mathematical Physics at Ludwig Maximilian University München (2017-2019) and Bachelor’s degree in Physics at Universitat de València (2013-2017). His research interests include developmental biology and biophysics.