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 simple illustrative 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 immunostaining, colocalization
11. Spare slot / solutions to practice work / resources and libraries
12. (Image classifier?) 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 know python, I just want to see what this course is about'

Prerequisites: – A working laptop that you can bring to the course
- Any level of qualification but basic mathematics is expected

Evaluation: Attendance (20%) (<6 classes 0; 6-12 classes 20%)<%2%1%>Assignments (30%) (submit all assignments or none)
Self-assigned project (50%) (graded)

A self-assigned project that utilizes python programming should be proposed before midterm. 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.

Course pass 70%

Teaching format: Hands-on, in person training. Each participant works on their computers while following instructions, with assistance from TA’s

ECTS: 6 Year: 2021

Teacher(s):
Chaitanya Chintaluri

Teaching assistant(s):

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