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Date
20.07.20 - 24.07.20

A Transmitting Science Course


Course outline

This course will cover basics of the Python programming language as well as the pandas and sklearn Python libraries for data wrangling and machine learning.

By the end of this course, participants will understand:
  • How to input and clean data in Python using the pandas library
  • How to perform exploratory data analysis in Python
  • How to use the sklearn library in Python for machine learning workflows
  • How to choose an appropriate machine learning model for the task
  • How to use supervised machine learning models (SVM, Decision Trees, Neural Networks, etc.) for classification tasks
  • How to use unsupervised machine learning models for clustering tasks
  • How to evaluate machine learning models and interpret their results
This course is intended to give participants a conceptual overview of machine learning algorithms and an intuition for the mathematics underlying them, equipping participants to be able to choose and implement appropriate models for biological datasets.

Requirements

Graduate or postgraduate degree in Life Sciences and basic knowledge of Statistics. While some Python knowledge is useful, the course will cover basic Python skills necessary to input, clean, and explore data as well as build and evaluate machine learning models.

All participants must have a personal laptop and a good internet connection (Windows, Macintosh, Linux).


Booking and cost

All RSB members are entitled to a 20% discount off course costs. To find out more about fees and book the event visit the transmitting science webpage.

Contact

For any course enquiries, please contact Transmitting Science at courses.greece@transmittingscience.com

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