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
- Software engineers and developers
- Machine learning scientists and other technical professionals
- Financial analysts
- Government and military officials
- Business executives and leaders
Our courses in London are held at the LPC office located at:
Once you register, we will subsequently send you the course details, including the location, trainer, and other logistical information.
Pay Attention, Please! The course location at our offices is subject to availability. Should our office be unavailable, we will secure an alternative nearby venue and promptly inform you of the change. The exact time and location will be confirmed one week prior to the course commencement.