We’re back from the Christmas holidays, with a lot of news! We’ll start the New Year with a new edition of our most requested live courses: R for Data Science and Statistics for Data Science. There’s still some available seats, so be sure to be fast! Down below, you can find a quick description of the classes and a link to the official page of the event, to find out more about it and reserve a seat.
R for Data Science: January 23rd-24th
If you want to deepen your data analysis knowledge using the most modern R tools, or you want to figure out if R is the right solution for your needs, this course is made for you!
It’s the right class for people who are willing to learn about R and would like to get an overview of its capabilities for data science, or those who have very little knowledge of R.
Outline
– A bit of R history and online resources
– R and R-Studio installation and configuration
– Your first R session
– Your first R markdown document
– R objects: data and functions
– Data import from external sources: excel and database connection
– Data manipulation with tidyverse
– Tidy data with tidyr
– Data visualization using ggplot
– An overview of statistical models and data mining with R
Attendees
The course is for max 4 attendees (you’ll have to be fast if you want to reserve a seat!).
Language
The course itself is taught in Italian, while all the materials are in English.
Location
The course location is in Legnano (MI), Lombardia.
Reserve your ticket – R for Data Science
Statistics for Data Science: January 30th-31th
In this two-day course you will learn how to develop a broad variety of linear models with R. You will get a wide overview of the R capabilities to model and to make predictions, using a variety of examples.
This course fits especially for people involved in research, but it’s suitable for anyone who’s using R and wants to get an overview of statistical models with R. A background in theoretical statistics and probability is obviously required.
Outline
– t-test, ANOVA
– Linear, Polynomial and Multiple Regression
– More Complex Linear Models
– Generalized Linear Models
– Logistic Regression
– Poisson Dep. Var. Regression
– Gamma Dep. Var. Regression
– Check of models assumptions
– Brief outlines of GAM, Mixed Models. Neural Networks, Tree-based Modelling
Attendees
The course is for max 4 attendees (you’ll have to be fast if you want to reserve a seat!).
Language
The course itself is taught in Italian, while all the materials are in English.
Location
The course location is in Legnano (MI), Lombardia.
