News:Online course- Advanced Python for Life Sciences
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Online course: ADVANCED PYTHON FOR LIFE SCIENCES


Dates: 9-11 September 2024

To foster international participation, this course will be held online


Course website: https://www.physalia-courses.org/courses-workshops/advanced-python/


COURSE OVERVIEW

This three-day course is designed to provide the foundations and typical workflow of data science, with a particular focus on biology and life sciences, using the Python programming language. Throughout the course, participants will learn intermediate to more advanced concepts of Python programming and engage in hands-on coding exercises.


TARGET AUDIENCE AND ASSUMED BACKGROUND

The course is intended for biologists and life scientists at all levels with some prior programming experience and basic knowledge of Python (general syntax, variables, lists, dictionaries, conditionals, loops, functions).


LEARNING OUTCOMES

By the end of the course, participants will be able to:

  • understand the different steps of a data science workflow in biology
  • write Python code for data wrangling and interaction with common bioinformatics formats
  • understand the basics of machine learning using Python
  • understand the principles of data visualization with applications in Python

PROGRAM

Monday – Classes from 2-6 PM Berlin time

  • Intro to data science and its applications in biology
  • Python refresher
  • Intermediate Python: functions, classes, modules, tips & tricks
  • Data preprocessing and wrangling

Tuesday – Classes from 2-6 PM Berlin time

Machine learning:

  • Intro and theoretical foundations
  • Supervised, unsupervised, and reinforcement learning
  • Commonly used algorithms
  • Feature engineering and selection
  • Train-test split and cross-validation
  • Hands-on with scikit-learn

Wednesday – Classes from 2-6 PM Berlin time

Data visualization:

  • introduction and theoretical concepts
  • principles and common errors
  • Hands-on with Python plotting libraries such as matplotlib and seaborn
Python-Programming Data-Visualisation Machine-Learning • 206 views
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