BIG DATA COURSE
Applications of techniques and analyzes "Big Data" for railway maintenance.
Technological advances allow for ever greater data collection. The technical challenge is how best to take advantage of the benefits and capitalize on the opportunities presented by Big Data. The application of emerging data techniques in railway maintenance, a two-day professional development course, is focused on data analysis techniques and practical case studies that are directly applicable to professionals working in Railway Engineering.
Instructor: Nii Attoh-Okine
Investment per person: R $ 1,800.00
Way of payment: Via Credit Card online (link to be made available on August 10th).
If you prefer to pay by bank transfer, please send an email to
Discounts applicable to students.
Date: October 17 and 18
Duration: 15 hours
Topics covered include:
BASIC CONCEPTS OF DATA ANALYSIS:
Introduction to data
Univariate and multivariate analysis
Correlation and Covariance
TECHNIQUES OF DATA ANALYSIS "BIG DATA" (I):
Supervised / Unsupervised Learning
Support Vector Machines (SVM)
"BIG DATA" (II) DATA ANALYSIS TECHNIQUES:
Multivariate Adaptive Regression Splines (MARS)
"BIG DATA" (IV) DATA ANALYSIS TECHNIQUES:
Metropolis Hastings Algorithm
Markov Chain Monte Carlo Application (MCMC)
CASE STUDIES APPLIED TO RAILWAY
Information and monitoring of geometry and ballast conditions
Condition information for sleepers
Software Implementations - Examples Using R-Software and Ipython
Defects vs. Geometry defect relationships
Geometry Degradation Forecast
Stress failure analysis