Last Updated on by admin

What Is Predictive Modeling? What Skills Are Required To Build A Predictive Model?

Data Science is an umbrella term that makes use of techniques from different fields like Statistics, Machine Learning, Artificial Intelligence, Natural Language Processing, and more. With the association of these technologies, Data Science sets its focus towards extracting useful information from large amounts of unstructured, structured, and semistructured data sets. The recent advancements in Data Science have led to the integration of Artificial Intelligence and probabilistic reasoning techniques to provide high quality, reliable, and accurate results.

Nowadays, as data is being generated across industry verticals, this means not only high-end IT enterprises & large scale business enterprises are benefitting from Data Science but also Healthcare, Banking, Telecom, Insurance, Education, Automobile and other sectors are also relying on Data Science to help their business scale and grow. Build real-world skills & hands-on expertise in handling the techniques that are associated with data analytical process in Data Science through our Data Science Training in Hyderabad program.

What Is Predictive Modeling?

Predictive modeling, also called predictive analytics is the process of predicting the future events by applying a mathematical process & by analyzing the data patterns. Predictive models make use of present & historical data to come up with accurate predictions about the occurrence of any event.

Essential Skills To Build A Predictive Model:

In order to build predictive models, you will need to study statistics and how to apply mathematics in different fields. This involves studying the basic algorithms which have been developed in various fields such as programming languages, programming theory, artificial intelligence, economics, optimization and probability. It is important to be aware that when you build these models they are also based on statistical principles.

There are other analytical techniques which can be used in Data Science. These techniques include but are not limited to, Bayesian and conditional independence, least squares, mixed effects modeling, and multivariate analysis. You can master these techniques & become a full-fledged Data Science expert with our advanced Data Science Course In Hyderabad program.