[R-sig-genetics] Introduction to Machine Learning with R

[i@io m@iii@g oii phys@ii@-courses@org]

Dear all,
there are only a few seats remaining for our upcoming Introduction to Machine Learning with R (online) course. 
 
Dates: 3–7 March 2025
Course website:[ https://www.physalia-courses.org/courses-workshops/course43/ ]( https://www.physalia-courses.org/courses-workshops/course43/ ) 

This course provides a comprehensive introduction to machine learning for biological research, with a focus on the analysis of complex, multivariate ‘omics datasets. You’ll explore tools like tidymodels and techniques including regression, classification, random forests, and unsupervised learning, all within the R programming environment.
 
What You’ll Learn:
Understand the principles of data mining and machine learning in an ‘omics context.
Perform regression and classification tasks using machine learning.
Apply methods such as Random Forests, PCA, UMAP, and more to analyse biological datasets.
Identify and avoid overfitting using resampling techniques.
Who Should Attend?
This course is ideal for researchers and students seeking an intuitive introduction to machine learning. While no prior experience is required, a foundational understanding of statistics and basic R programming knowledge is recommended.
 
 
Why Join Us?
This course equips you with the tools and techniques to analyze complex biological data effectively, all while fostering discussions on real-world challenges and solutions.
 
Best regards,
Carlo
 
 
 
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Carlo Pecoraro, Ph.D


Physalia-courses DIRECTOR

info using physalia-courses.org

mobile: +49 17645230846




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