Foundations of Data and Models: Regression Analytics

Available Dates

Venue

Dec-30-2024

Barcelona
Dec-30-2024

London
Feb-03-2025

Singapore
Feb-03-2025

Istanbul
Feb-03-2025

Paris
Feb-03-2025

Dubai
Feb-03-2025

Barcelona
Feb-03-2025

Kuala Lumpur
Feb-03-2025

Amsterdam
Feb-03-2025

London
Apr-14-2025

Dubai
Apr-14-2025

London
May-05-2025

Kuala Lumpur
May-05-2025

Istanbul
May-05-2025

Amsterdam
May-05-2025

Paris
May-05-2025

Barcelona
May-05-2025

Singapore
June-09-2025

Dubai
June-09-2025

London
Aug-04-2025

Barcelona
Aug-04-2025

Paris
Aug-04-2025

Dubai
Aug-04-2025

London
Aug-04-2025

Istanbul
Aug-04-2025

Amsterdam
Aug-04-2025

Kuala Lumpur
Aug-04-2025

Singapore
Sep-22-2025

Dubai
Sep-22-2025

London
Nov-03-2025

Barcelona
Nov-03-2025

Paris
Nov-03-2025

Singapore
Nov-03-2025

Istanbul
Nov-03-2025

Kuala Lumpur
Nov-03-2025

Amsterdam
Nov-17-2025

London
Nov-17-2025

Dubai

Course Details

This course aims to teach a suite of algorithms and concepts to a diverse set of participants interested in the general concept of fitting data to models. It starts with mostly simple linear algebra and computational methods, and introduces some more difficult mathematical concepts towards the end. This method also, by design, fits in with our approach of morning lectures and afternoon practice on personal computers. The combined teaching system provides opportunities for much hands-on learning and participants leave the course with practical knowledge of the basic algorithms.

Applied data science enjoys widespread application in nearly every industry today. It lies at the intersection of the quantitative (statistics and optimization), the computational (programming and IT), and the domanial (business knowledge).

Examining how to fit data to models
Defining linear least squares, non-linear least squares, singular value decomposition, sensitivity analysis, experiment design, and parameter error estimation
Appreciating grid search, random search, simulated annealing, genetic algorithms, neural networks, and large inverse systems
Investigating principles leading to rapid application of methods
Evaluating the results of pre-programmed computer exercises