Mathematics and programming training
Planning 2023-2024 :
Year : L3/M1
Semester: S1
ECTS: 0
Coordinator: Morgane Thomas-Chollier, Biology Department, ENS (MC ENS)
Hours: 30h (15h maths, 15h programming)
The course is accessible to L3/M1 with specific perimeter for each year (see below).
If you are arriving in L3, information concerning you is available in the French version of this course description
This training aims at providing the newly-arrived students the opportunity to
- get familiar with the computer working environment of the ENS (mandatory for all newly-arrived students in M1, not open to L3 students)
- update their knowledge in maths (L3 and M1) and programming (M1 only)
If you are newly-arriving in M1, this training (both maths and informatics) is a pre-requisite for the Data analysis course. The maths part, in the advanced level group, is a pre-requisite for the course Mathematics II : what biologists might like to know
This week will start on Monday 28th August 2023 . The teaching is done remotely, with the possibility to access the teaching rooms at ENS and meet fellow students. For students with important jet lag : you will have access to all pedagogic material and can ask your questions asynchronously on a forum.
Themes:
1. WORKING ENVIRONMENT (mandatory for all newly-arrived students in M1 or M2, not open to L3 students)
The computer room is equipped with machines running under the Linux environment (Ubuntu). The students will learn how to login on the machines, become familiar with the graphical environment and also use the command line.
The students will also learn how to use the remote access to machines (VPN, X2Go), usage of the cloud to share documents, email access, informatics security, and our Moodle platform.
This part is not directly included in the training, it must be done in autonomy, remotely, before the training or arrival at ENS. A Q&A session will take place on Monday 28th Morning for students having issues.
2. PROGRAMMING: (M1 only)
We chose to make the students work with Python, a simple and powerful programming language. For the start of new term, the aim would be to have understood the various types of data (especially lists and dictionaries), to be able to write a function (notion of local and global variables), be able to use modules, and understand how to read and to write in a file (module sys and os). The last session is devoted to the langage R.
3. MATHEMATICS: (L3 and M1)
overview :
This introductory course aims to provide students with basic mathematical tools necessary for most subsequent courses. The first half of the course will be an introduction to the study of dynamical systems, and will start with a review of linear algebra; we will then study the resolution of systems of linear differential equations, before generalising some results to non-linear equations (e.g., study of the fixed points in the Lotka–Volterra equations). The second half of the course will provide students with basic knowledge in probability and statistics—which is crucial to any biologist nowadays—and will cover the main theorems that give rise to common hypothesis tests broadly used the scientific community.
The course will be mostly self-contained; however, few pre-requisites include basic concepts in linear algebra (matrices, eigenvectors, eigenvalues, diagonalisation), analysis (derivatives, differential equations), and probability (basic combinatorics, probability density function, central limit theorem).
Lecture1 is considered as pre-requisite for the maths training. You are expected to study the document ("Lecture 1") and prepare the associated exercices before the training week.
Organization:
The teaching unit is organised over the first week of the semester. The organisation is online with the possibility to use the ENS rooms. It is possible to follow only one training (maths or informatics).
Further reading
Linux command-line:
– Interactive MOOC (English):https://www.codecademy.com/en/courses/learn-the-command-line/
– Other courses are listed on this page:http://freevideolectures.com/blog/2012/04/5-websites-learning-linux/
Python
– Python documentation : http://docs.python.org
– A good Python course, by a professor at Paris 7: http://www.dsimb.inserm.fr/~fuchs/python/cours_python.pdf
– For those wishing to go further: a free book in French : http://inforef.be/swi/python.htm
– Another book, in English:http://www.greenteapress.com/thinkpython/
R
– Various documentation in many languages on CRAN : https://cran.r-project.org/other-docs.html
– A resource in French :www.duclert.org/Aide-memoire-R/Le-langage/Introduction.php
