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Learn how to use data to create powerful business forecasts
Organisations currently collect a vast quantity of data about suppliers, clients, employees, citizens, transactions, and much more. However, many are unaware of the predictive power this ‘big data’ has if anaylsed correctly.
On this course, you’ll learn about forecasting using big data, exploring how it’s used by business as an important component of decision making.
You’ll examine how to define a forecasting task and workflow. You’ll understand how to evaluate forecasting performance, analysing different forecasting methods. Ultimately, you’ll be able to implement your own practical forecasting process.
This course is for anyone who wants to understand how big data can help their business or organisation’s decision-making process. You will need to be familiar with basic statistical methods, including linear regression, as well as have basic knowledge of Excel and R software.
Overview
Syllabus
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- Approaching forecasting
- Introduction
- Forecasting applications
- Forecasting language & notation
- Exploring time series data
- Software
- Data visualization
- Data at time of prediction
- Performance evaluation
- Data partitioning
- Naïve forecasts
- Performance charts and metrics
- Practical performance
- Smoothing-based methods
- Moving average
- Differencing
- Exponential smoothing
- PIs, automation, and big data
- Regression-based methods: Part 1
- Regression for forecasting
- Regression trend models
- Regression trend and seasonality models
- Regression-based methods: Part 2
- Autocorrelation
- AR and ARIMA Models
- Forecasting and Big Data
- Including external information
- Conclusion
