Advanced Data Analytics

With the advent of the emergence of the IoT, the consequential growth in Big Data, and the ever-increasing requirements to model and predict, many of the analytical opportunities and needs of a business now cannot be resolved only by using conventional statistical methods alone.

Organizations are turning to predictive analytics to help solve difficult problems and uncover new opportunities. Predictive models help businesses attract, retain, and grow their most profitable customers. This training course is designed to provide participants with advanced concepts of data analytics and techniques to create a variety of powerful modeling, simulation, and predictive analytical methods. This includes the Bayesian models, Newtonian and genetic optimization methods, Monte Carlo simulation, Markov models, advanced What If analysis, Time Series models, Linear Programming, and more.

• Gain a comprehensive understanding of how to unravel a wide range of business problems that require modeling, simulation, and predictive analytical approaches….
• Familiarize with and understand common modeling, simulation, and predictive analytical techniques, including Bayesian models, conventional and genetic optimization methods, Monte Carlo models, Markov models, What If analysis, Time Series models, Linear Programming, and more…
• Select which modeling, simulation, and predictive analysis methods are best suited to which types of problems….
• Apply modeling, simulation and predictive analytical methods using Microsoft Excel 2010 (or higher) and, in particular, the Solver tool.