Python for Life Sciences
We will introduce computational thinking using Python and lay the foundations of control flows with a focus on working with data, including loading, wrangling, visualising and analysing in an automated way. By the end of the week you should be able to develop your own ideas independently.
Register in here.
Prerequisites:
- Audience: Researchers, PhD students, Master students
- Free for students and researchers associated with CIMAR-LA (CCMAR and CIIMAR) and UAlg. If you are eligible for free participation, a letter of motivation for each of your chosen modules is required.
- Others: Module I €100, Module II €100. If you are a paying participant, a motivation letter is not required, but letting us know your aims and aspirations will help us to tailor the course to your needs.
Module I
3-5 June | 24 places
We will introduce computational thinking with the help of Python and lay the foundations of control flows with a focus on working with data, including loading, wrangling, visualizing and analysing in an automated fashion. By the end of the week you should be able to develop your own ideas independently.
Monday, 3 June
11:30 – 12:30 optional. Help with Python setup for those wishing to run code locally on their machines.
14:00 – 17:30, algorithmic thinking, variables, data types
Tuesday, 4 June
10:00 – 12:30, data structures, conditionals, operators.
14:00 – 17:30, Loops, Functions, NumPy.
Wednesday, 5 June
10:00 – 12:30, modules, class attributes/methods, scripts, matplotlib.
14:00 – 17:30, pandas
Module II:
6-7 June | 15 places
Module II will provide personalised guidance on the dataset, problem, or project specified in your registration form. This might include data cleaning, exploratory analysis, predictive model development, and training. Important note: If you are only taking Module II, you should be familiar with the topics covered in Module I, and it is highly recommended that you run Python locally.
Thursday, 6 June
10:00 – 12:30, pandas, exploratory analysis, data cleaning.
14:00 – 17:30, GitHub, PyPi, identify and use existing repositories and packages.
Friday, 7 June
10:00 – 12:30, Scripting with your own and public code.
14:00 – 17:30, Statistical analysis, fitting, introduction to machine learning in sci-kit learn, etc.
Instructors:
Paulo Martel (CINTESIS, UAlg): Computational biologist focusing on protein dynamics and lecturer at UAlg.
David Palecek (QBI, CCMAR): Experimental physicist and Python practitioner with an interest in automation and data science.