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Madrid - Chamartín Business Area

NobleProg Madrid, Street Bausá 27, Madrid, spain, 28033

Madrid is a municipality and city of Spain is the most populated city of the country, with 3 165 235 inhabitants. On the economic level, it is the fourth richest city in Europe, after London, Paris and Moscow. It is an influential cultural center and has museums of international reference, among which stand out the Prado Museum, the National Museum of Art Reina Sofia, Thyssen-Bornemisza and CaixaForum Madrid. Being one of the largest cities in all of Spain and one of the most populated, it is characterized by having an extensive transport network consisting of rail, metro and bus lines, in addition to its airport. Located in the business area of ​​Chanmartin five minutes from Plaza Castilla and less than ten minutes from the airport Madrid Barajas and Madrid downtown area.

Subcategories (3)

Explore Our Courses

Design for Six Sigma (DFSS)

21 Hours

Six Sigma DMAIC Black Belt

21 Hours

R Markdown for Dynamic Documents and Reproducible Reporting

14 Hours

Six Sigma DMAIC Green Belt

21 Hours

Six Sigma LEAN Yellow Belt

14 Hours

Six Sigma LEAN Green Belt

21 Hours

Data Analytics with Tableau, Python, R, and SQL

35 Hours

Data Analysis with Python, R, Power Query, and Power BI

21 Hours

Six Sigma LEAN Black Belt

21 Hours

Six Sigma Yellow Belt

14 Hours

Shiny App Web Development with R

14 Hours

Six Sigma White Belt

14 Hours

Design of Experiments (DoE)

7 Hours

Econometrics: Eviews and Risk Simulator

21 Hours

Statistical Analysis with Stata and Integration with R

35 Hours

Data Analytics With R

21 Hours

Excel For Statistical Data Analysis

14 Hours

Data and Analytics - from the ground up

42 Hours

NLP: Natural Language Processing with R

21 Hours

Analysing Financial Data in Excel

14 Hours

R Programming for Finance

28 Hours

Advanced R

14 Hours

Advanced Statistics using SPSS Predictive Analytics Software

28 Hours

Algorithmic Trading with Python and R

14 Hours

Programming with Big Data in R

21 Hours

Introductory R (Basic to Intermediate)

14 Hours

Cluster Analysis with R and SAS

14 Hours

Statistics and Probabilistic Programming in Julia

21 Hours

KNIME with Python and R for Machine Learning

14 Hours

Minitab for Statistical Data Analysis

14 Hours

Advanced Machine Learning with R

21 Hours

Introductory R for Biologists

28 Hours

Shiny, R and HTML: Merging Data Science and Web Development

7 Hours

Practical Six Sigma and BPM Process Improvement for Operations Teams

21 Hours

Statistics with SPSS Predictive Analytics Software

14 Hours

Statistical Thinking for Decision Makers

7 Hours

Statistics Level 1

14 Hours

Statistics for Researchers

35 Hours

Statistical Analysis with Stata and R

35 Hours

Data Science with Tableau and R Programming

14 Hours

Tableau Advanced

14 Hours

Building Web Applications in R with Shiny

7 Hours

Forecasting with R

14 Hours

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