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 Singapore take place at the following location :
Once you register for this course, we will subsequently send the invoice and course information, including location, trainer, and other logistics.
Pay Attention, Please! The course location is subject to availability; the course time will be precise one week before the course start date! We may change the course location if there is no availability, and we will let you know about the location change once it happens.