We will introduce computational thinking using Python and lay the foundations of control flows with a focus on working with data, including loading, wrangling, visualizing and analysing in an automated way. By the end of the week you should be able to develop your own ideas independently.

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.

Please make your registration HERE.