Short Course in Predictive Analytics in ITS


Course Description

This course presents basic concepts on SupervisedLearning which are devoted to both develop and deploy real-world Predictive Analytics frameworks envisaging applications in the area of Intelligent Transportation Systems. It includes both relevant slides, key references and a guided practical exercise where the source code is provided.


Course Format

Powerpoint lectures visual together with supporting publications.


Teaching Concepts

Regression from structured and time series data


Prerequisites

To accomplish this short course in Predictive Analytics in ITS, the students must possess an awareness on basic concepts of Descriptive Statistics, DiscreteMathematics, Algebra and Numerical Optimization.


Course Content

  • Introduction To Predictive Analytics in ITS
  • Basics on Supervised Learning problems
  • ITS Applications of Predictive Analytics
  • Basics in Regression Analysis
  • Simple Linear Regression
  • Numerical Example with Least Squares
  • Basics on Time Series Analysis
  • Time-dependent Predictive Analytics
  • Ensemble Learning and Beyond
  • Introduction to R for Predictive Analytics
  • Guided Practical Exercise to predict short-term demanding Bike sharing systems(Source Code provided!)

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