Mediaspace scheduled maintenance: Aug 25, 2026 07:00 - 12:00 AM. During this time, videos will be temporarily unavailable. Check status updates.

Graph
Search

Course

BIOENG-210: Biological data science I: statistical learning

Summary

Processing, analyzing, and interpreting large biological datasets is an essential skill for modern biologists. This course aims to provide the theoretical foundations, analytical techniques, and software tools necessary to effectively manage and derive insights from biological data.

Lectures

Instructor

Gioele La Manno

Official source

https://edu.epfl.ch/coursebook/en/biological-data-science-i-statistical-learning-BIOENG-210

Moodle Page

http://go.epfl.ch/BIOENG-210

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Summary

Lectures

Instructor

Gioele La Manno

Official source

https://edu.epfl.ch/coursebook/en/biological-data-science-i-statistical-learning-BIOENG-210

Moodle Page

http://go.epfl.ch/BIOENG-210

About this result

Ontological neighbourhood

Statistics

Statistical inference: Mathematical statistics, Statistical hypothesis testing

Data analysis: Regression analysis

Information engineering

Machine learning: Unsupervised learning

Mathematics

Probability theory: Topics in probability theory

Related courses (31)

PHYS-467: Machine learning for physicists

Machine learning and data analysis are becoming increasingly central in sciences including physics. In this course, fundamental principles and methods of machine learning will be introduced and practised. ...

DH-406: Machine learning for DH

This course aims to introduce the basic principles of machine learning in the context of the digital humanities. We will cover both supervised and unsupervised learning techniques, and study and implement methods to analyze diverse data types, such as imag ...

CS-401: Applied data analysis

This course teaches the basic techniques, methodologies, and practical skills required to draw meaningful insights from a variety of data, with the help of the most acclaimed software tools in the data science world (pandas, scikit-learn, Spark, etc.) ...

CS-433: Machine learning

Machine learning methods are becoming increasingly central in many sciences and applications. In this course, fundamental principles and methods of machine learning will be introduced, analyzed and practically implemented. ...

EE-411: Fundamentals of inference and learning

This is an introductory course in the theory of statistics, inference, and machine learning, with an emphasis on theoretical understanding & practical exercises. The course will combine, and alternate, between mathematical theoretical foundations and prac ...