R training

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Charts (Graph Mining)

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The goal of this course is to learn how to create the most common asked undergraduate or graduate level charts and plots in schools, organizations or corporate business for 2D, 3D, GIS (Geographic Information System), biostatistics or data mining representations thanks to this complete and powerful software that is R. No maths will be done or explained during this course (you can request the corresponding theoretical course).

Data Mining & Text Mining

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This course provides an introduction to R core fundamental data mining tools! No maths will be done or explained during this course (you can request the corresponding theoretical course).

Data Munging and Data Wrangling

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This training aims to deepen in details the import and the processing of data in R with mainly the basic packages, utils, RODBC, RMySQL, readr, stringr, lubrdiate, sqldf, dplyr, data.table (contrary to the training R Fundamentals where there are just quickle seen) to be able to understand and master the vast majority of cases of import, cleaning and data preparation (data.frame, tibble, lists, objects S3 / S4 or vectors objects types) for the statistical analysis or machine learning as well as to learn good practices and standards corresponding to the management and data storage. We strongly advise any person or organization interested in this training to contact us to target the topics and thus possibly to significantly reduce the duration of the training.

Foundations

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This course introduces the R software statistical by focusing only on the data management aspect of the software (input/output, clean/format variables), core mathematical analytics functions of undergraduate level and the various software parameters and system data management and the installation of packages. This course is the basis for next statistical course techniques on R. No maths will be done or explained during this course (you can request the corresponding theoretical course).

Inferential Statistics and Paramatric Hypothesis Tests

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The goal of this course is to practice with R Bachelor and Master level statistical tools for non-punctual and parametric inferential analysis or uni/multivariate data for all areas in the services, industry, R&D and sensory analysis. No maths will be done or explained during this course (you can request the corresponding theoretical course).

Non-Parametric Hypothesis Tests

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The goal of this course is to practice with R Bachelor and Master level statistical tools for non-parametric and robust inferential analysis on uni/multivariate data for all areas in the services, industry, R&D and sensory analysis. No maths will be done or explained during this course (you can request the corresponding theoretical course).

Quality Control

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In this course you will learn the elementary statistical tools (level TQ3/Green Belt) of quality analysis that are available in R for corporates applying statistical process control (SPC) in the area of factoring, administration (Lean Office), supply chain, engineering, human resources, marketing, management or R&D. No maths will be done or explained during this course (you can request the corresponding theoretical course).

Quantitative Finance

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This training introduce the major tools that can be used by any analyst or financial engineer to perform calculations and analysis of credit, valuation of financial assets, calibration, portfolio diversification, hedging risk and backtesting. The purpose of this training is to teach the different topics, avoiding as much as possible rewriting codes from scratch and maximizing the use of CRAN packages.

Regression Techniques

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The goal of this course is to practice with R Bachelor and Master level statistical parametric or non-parametric inferential techniques for regression on continuous or non-continuous univariate or multivariate data for all areas in the services, industry, R&D and sensory analysis. No maths will be done or explained during this course (you can request the corresponding theoretical course).

Time Series Analysis

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The goal of this course is to practice with R the use of various mathematical techniques for the analysis of times series data and do forecasting. Will be seen in the course the most known techniques in the world (not exceeding the level of a university Master) considered as a base in the field of business economics, governments investment strategies or actuarial. No maths will be done or explained during this course (you can request the corresponding theoretical course).


Trainings, Courses available in Chicago, Dallas, Geneva, Huston, Los Angeles, New York, San-Antonio, San Diego, San Francisco, Washington, Zurich and anywhere in Switzerland, USA, Great Britain and Germany.