Data Science-Forecasting/Time series Using XLMiner,R&Tableau
Forecasting Techniques-Linear,Exponential,Quadratic Seasonality models, Autoregression, Smooting, Holts, Winters Method
Ratings 4.46 / 5.00
What You Will Learn!
- Learn about different types of approaches using XLminer, R and Tableau
- Learn about the Forecasting Importance ,Forecasting Strategy which includes Defining goal, Data Collection, Exploratory Data Analysis, Partition Series, Pre-process Data, Forecast Methods, using various Plots.
- Learn about scatter diagram, correlation coefficient, confidence interval, which are all required for implementing forecasting techniques
- Learn about the various error measures such as ME, MAD, MSE, RMSE, MPE, MAPE, MASE
- Learn about Model based Forecasting Techniques such as Linear, Exponential, Quadratic, Additive Seasonality, Multiplicative Seasonality, etc.
- Learn about Auto Regressive Models for using errors to further strengthen the forecasting model used & also learn about Random walk & how to identify the same
- Learn about Data Driven approaches such as Moving Average, Simple Exponential Smoothing, Double Exponential Smoothing / Holts, Winters / HoltWinters
Description
Forecasting using XLminar,Tableau,R is designed to cover majority of the capabilities from Analytics & Data Science perspective, which includes the following
- Learn about scatter diagram, autocorrelation function, confidence interval, which are all required for understanding forecasting models
- Learn about the usage of XLminar,R,Tableau for building Forecasting models
- Learn about the science behind forecasting,forecasting strategy & accomplish the same using XLminar,R
- Learn about Forecasting models including AR, MA, ES, ARMA, ARIMA, etc., and how to accomplish the same using best tools
- Learn about Logistic Regression & how to accomplish the same using XLminar
- Learn about Forecasting Techniques-Linear,Exponential,Quadratic Seasonality models,Linear Regression,Autoregression,Smootings Method,seasonal Indexes,Moving Average etc,...
Who Should Attend!
- All the IT professionals, whose experience ranges from '0' onwards are eligible to take this session. Especially professionals from data analysis, data warehouse, data mining, business intelligence, reporting, data science, etc, will naturally fit in well to take this course.
Tags
- Forecasting Model
- R (programming language)
- Tableau
- Time Series Analysis
Subscribers
1353
Lectures
33
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