TOPIC
Machine learning
SUBTOPIC
Deep Learning
LANGUAGE
English
ENROLL
On Demand
DURATION
5 (40 h)
TRAINER
Cineca
The increasing amount of data collected through sensors or computational simulations can take advantage of new techniques for being processed in order to extract new insights out of raw data. The purpose of this course is to present researchers with data science methods and techniques. The course includes theoretical lectures followed by practical sessions on data manipulation, visualisation, machine learning and deep learning. A specific session on how to use HPC resources is included.
Keywords:
Data Science, Deep Learning, Machine Learning, Predictive analytics
LEARNING OUTCOMES
At the end of the course, the student will be expected to have acquired:the ability to perform basic operations on matrices and dataframes; the ability to manage packages; the ability to navigate in the RStudio interface; a general knowledge of Machine and Deep Learning and packages methods.
PRE-REQUISITES
Basic knowledge of statisticcs
TARGET AUDIENCE
Student
COURSE TYPE
Hands-on
MATERIALS
Scripts, Slides
