Python programming for biologists

The course is a basic introductory 12 part course, with 1.5 hrs class work and about 1.5 hrs of practice work per class. The course will also include a self-assigned project which will be evaluated in addition to the weekly homework. It is geared at life scientists at any career stage that do not have any prior programming experience, but think that they can use some. Examples will be taken from a broad spectrum of topics such as behavior, electrophysiology, bioinformatics, immunostaining etc. The course will be hands on and will rely exclusively on examples from life sciences. The aim of this course is to the help you to develop code independently to solve tasks that you may encounter in your research. An example scenario would be something like 'it would be great if I could quickly count the number of cells in this slice.'

COURSE PLAN
1: Why programming/ writing scripts in python/ loading and manipulating data / variables / plotting-1
2: Functions / syntax / testing and documenting / function default / seeking help / plotting-2
3: Lists and loops
4: Conditionals / building a guessing game
5: Spare slot / solutions to the practice work / intuition for functions
6: Spreadsheets / reading .mat files
7: Grid cells example / plotting-3
8: String manipulation / mRNA -> protein and vice versa /python pickle
9: Tracking a mice in an open field
10: Counting cells in an immunostaining
11. Estimating the growth rate of a root from images.
12. Discussing self-assignments and feedback

Target group: - Anyone with a life sciences background keen to learn programming
- Low or no programming experience
NOT FOR
- Building software exclusively for your research
- 'I know programming language X and I want to learn Python'
- 'I already know python, I just want to see what this course is about'
- Auditing this course is discouraged.

Prerequisites: A working laptop

Evaluation: Homework assignments after each class (60%) and a self-assigned project (40%).

70% is pass. Auditing is discouraged.

a) The assignements are evaluated for their attempt and not for their accuracy.
b) A self-assigned project that utilizes python programming should be proposed before midterm of the course. This can be any project of your choice, preferably within the scope of scientific research. The proposal will be screened for its adequacy and feasibility in the time frame of this course and any further recommendations will be suggested. The grading for this is scaled based on individual skill level.

Teaching format: This is offered only as an in person training and will NOT be held on online.

Each participant works on their computers while following instructions, with assistance from TA’s.

ECTS: 3 Year: 2022

Track segment(s):
Service

Teacher(s):
Olga Petrova Chaitanya Chintaluri

Teaching assistant(s):
Eleonora Quiroli

If you want to enroll to this course, please click: REGISTER