Machine Learning - a hands-on introduction

Dates

13-16 July 2020

WHERE

Due to the COVID-19 outbreak, this course will be held online

Course Overview

The use of modern quantitative technologies to characterize complex phenomena represents the standard procedure in almost every research domain. Biology makes no exception and the use of multi-omics techniques (metabolomics, transcriptomics, genomics and proteomics) is pervasive in every facets of life sciences. The resulting multivariate datasets are highly complex and advanced data analysis approaches have to be applied in order to optimize the information retrieved. For relatively large scales investigations, machine learning represents a valid tool to complement classical multivariate statistical methods.

The objective of the course is to highlight advantages and limitations of these type of approaches in the context of biological research, providing a broad hands-on introduction to the use of multivariate methods and machine learning for the analysis of complex datasets.

 

Targeted audience & ASSUMED BACKGROUND

The syllabus has been planned for people with zero or very basic knowledge of machine learning. Students are assumed to have basic familiarity with R programming language.

 

 

TEACHING FORMAT

The course is delivered over 8 half-day sessions (see details below). Each session consists of a lecture of two hours followed by one hour of practical exercises/demonstration. There will also be plenty of time for students to discuss their own problems and data.

Program

 Monday- 09:30- 17:30

 

 

       General Introduction

 

       Data mining, -omics and machine learning

 

       Experimental Design

 

 

       Jupyter for R 

 

       Introduction

 

       Data structures

 

       Reading and Writing data

 

       Data visualization

 

Instructors

 
Dr. Pietro Franceschi

 

 

COst overview

Package 1

 COURSE

 

 

 

 

400 €


Please click HERE to get all the information about our packages.

 

 

Registration deadline: 20th June 2020

Cancellation Policy:

 

 

 

> 30  days before the start date = 30% cancellation fee

 

< 30 days before the start date= No Refund.

 

 

 

Physalia-courses cannot be held responsible for any travel fees, accommodation or other expenses incurred to you as a result of the cancellation.