Learn how to build Predictive Models using Numerical Data using tools such as SAS
Description
Predictive modeling can be understood as the process of creation, test, and validation of a model. It uses concepts from statistics in predicting the outcomes. Predictive modeling contains a different set of methods like machine learning, statistics, artificial intelligence and so on. These models are made up of several predictors, also called attributes that are likely to impact future results. Predictive modeling is currently the most widely used in computer science, information technology, and information services domain.
This predictive modeling course targets to provide predictive modeling skills as mentioned above to business sectors/domains. Quantitative methods and predictive modeling concepts from this predictive modeling course could be extensively used in many fields to understand the current customer behavior, customer satisfaction, financial market trends, studying effects of medicine in pharma sectors after drugs are developed and administered.
Minitab or SAS and SPSS are among the leading developers in the world towards building statistical analysis software. Across the world, these software’s are used by thousands of companies. These are also used by over 10000 universities and colleges for research and teaching. Some major clients of Minitab, for example, consist of Pfizer, Royal Bank of Scotland, Nestle, Boeing, Toshiba, and DuPont.
Many independent studies conducted by companies like Mckinsey, Gartner, and others have predicted that data science, machine learning, and predictive modeling is going to be the biggest jobs of the 21st century and these professionals are going to be rewarded the best for it.
This course covers many tangible skills that students can count on for jobs and career switch. These skills are explained here to help students understand the value of this predictive modeling course.
- Skill to analyze data and see a complex pattern: data understanding and pattern extraction is a key skill for predictive modeling and a successful person in this domain should be able to make sense of data in no time. In this course, you will learn how to do that. You will be taught various types of data distribution, data patterns, and data understanding techniques. These skills will help you lifelong in making better and more intuitive decisions in all fields of work.
- Hands-on coding skill: – The predictive modeling course teaches three tools- Minitab, SAS, and SPSS. For that, this predictive modeling course is quite good. For predictive modeling and machine learning course one needs to be comfortable with coding, and hence having a sharp understanding of practical implementation is very important. This course teaches all these skills so that the student is industry ready and can comfortably work in real-life use cases.
- Strong understanding of concepts: – Machine learning concepts such as regression, classification, support vector machines, neural network, ROC curve, and many more concepts are taught which are frequently asked in interviews and which judges a candidate’s understanding of predictive modeling.
Who this course is for:
- Students from technical or computer science fields are highly welcome, similarly, those from mathematics or statistics background is highly suitable. Most commonly students have a degree in B. Tech / BCA/ B. Sc./ MCA/ M. Sc/ M. Tech or MBA degree. Entry-level working professionals from the software field, banking, insurance, share market, information technologies who want to migrate to data analysis are also very suitable and they comprise a major chunk of our class size. The predictive modeling course is also suitable for managers and seasoned industry professionals who want to be a consultant or data scientist.
