Data analysis course – PhD program

11 de November de 2022

"Introduction to scientific coding and data analysis"

Data analysis course given by Javier Alegre (IN researcher)

            15th November -15th December

            Tuesday and Thursday from 9:00 a.m. to 10:30 a.m. - Virtual curse

The course is planned to last 12 hours, distributed in one month, in two session of 1.5h per week, Tuesdays and Thursdays from 9am to 10:30 am, starting on November 15th. There will be 8 sessions distributed along 4 weeks (skipping the week starting December the 5th). You will receive the link to attend the session in advance.

Link: https://forms.gle/XaTc6bM8nCrwkCih8

The aim of this course is to improve the overall understanding and skill of young researchers that, without a solid base of coding and data analysis, do need to use these tools in their research. Previous coding skills or a strong mathematical knowledge are not required. In this context, the course has two main objectives:

First, to provide a solid understanding of the limitations and assumptions of statistical analysis to the students, allowing them to be more critical when reading literature and produce more robust results in their daily work.

Second, to provide the students with the basics of coding, and more important, the resources and documented libraries to be able to produce simple scripts that can improve their analysis pipeline, as well as presenting them new  tools, i.e. machine learning, that can be useful for their research.

Third, solving problems from 0: During different sessions, code a script to solve a typical lab problem, such as time series analysis, organising datasets, data regression, etc.

During the coding lessons, python will be the used programming language. Installing it through Anaconda and using Spyder as text editor is recommended (https://docs.anaconda.com/anaconda/install/). In addition, during the first class we will discuss the possibility to carry out other brief online courses in parallel as well as example datasets to reinforce the coding skills, following the resources at Kaggle . Therefore, I recommend creating an account at that website in advance.