Learn to produce dynamic dashboards with RShiny during our R Expert course
R EXPERT
Advanced Data Analytics
R PREDICTIVE ANALYTICS
& Data Science
Introduction to R / RStudio / RMarkdown environments.
Data preprocessing for predictive analytics, variables imputation, managing train/test data sets, unbalanced classes, dummies variables and more...
Data manipulation operations (filter, sort, aggregate, transform, etc.) as an organized processing flow.
Advanced modeling techniques : Logistic Regression, KNN, GLM, Random Forests, Gradient Boosting, Neural Network,…
Introduction to Data Viz
Model validation techniques
Learn how to efficiently process and manipulate your data in R
Learn the essential Python skills you need for your daily tasks, including data manipulation, visualization, geospatial analysis and handling Big Data with PySpark
Understand and handle different types of data and data structures
Efficiently preprocess data for advanced analysis.
Master advanced data manipulation techniques and establish a structured preprocessing workflow.
Conduct exploratory data analysis on a real use case and insurance portfolio.
Create interactive and visually appealing graphs (advanced Data Viz)
Produce interactive dashboards
Build your first RShiny App
Understand and process different data types
Perform advanced data manipulation techniques and establish a structured preprocessing workflow
Create interactive and visually appealing graphs
Perform geospatial analysis
Develop basic dashboards and web apps
Learn how to handle Big Data using PySpark
Dynamic reporting with RMarkdown
R Syntax, functions, ifelse statements, loops…
Implementation under R with a real use case – producing a ratemaking for an auto-insurance portfolio
Full overview of Predictive Modelling and Machine Learning algorithms for Insurance purposes