About the course
This course will introduce you to some of the most widely used predictive modeling techniques and their core principles. Predictive modelling is emerging as a competitive strategy across many business sectors and can set apart high performing companies. Models such as multiple linear regression, logistic regression, auto-regressive integrated moving average (ARIMA), decision trees, and neural networks are frequently used in solving predictive analytics problems. Regression models help us understand the relationships among these variables and how their relationships can be exploited to make decisions
What are the objectives of this course?
After the completion of this training, you will be able to:
- Understand Basics of Statistics using R
- Explain Regression
- Understand Simple, Multiple, Advanced and Logistic Regression
- Perform model fitting using Linear Regression
- Explain What is Heteroscedasticity?
- Understand Binary Response Variable and Linear Probability Model
- Explain Imputation
- Understand Forecasting
- Learn Neural Networks
- Explain Dimensionality Reduction
- Understands the algorithms associated with Dimensionality Reduction
- Understand Survival Analysis
Why Learn Advance Predictive Modeling using R?
This course will introduce you to some of the most widely used predictive modelling techniques and their core principles which is designed for anyone who is interested in using data to gain insights and make better business decisions. The techniques discussed in this course are applied throughout all functional areas within business organizations such as accounting, finance, human resource management, marketing, operations, strategic planning etc.
Who should go for this course?
The following professionals can take up this course:
- Developers aspiring to be a ‘Data Scientist’
- Analytics Managers who are leading a team of analysts
- ‘R’ professionals who want to capture and analyze Big Data
- Business Analysts who want to understand Machine Learning (ML) Techniques
What are the pre-requisites for this course?
Basic Understanding of R will be necessary in order to take up this course