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There are 6 modules in this course
This course explores different time series business forecasting methods. The course covers a variety of business forecasting methods for different types of components present in time series data — level, trending, and seasonal. We will learn about the theoretical methods and apply these methods to business data using Microsoft Excel. These forecasting methods will be programmed into Microsoft Excel, displayed graphically, and we will optimise these models to produce accurate forecasts. We will compare different models and their forecasts to decide which model best suits our business' needs.
Business Forecasting is part of any and every organisation. Organisations need to forecast so that they can plan for the organisation’s needs. Business forecasts are the inputs to every organisation’s planning – without business forecasts we cannot plan for our resources, our production, our supply chains – and ultimately our costs, revenues and profits. The current state of the world makes business forecasting even more fundamental to the operation of institutions. In this course we focus on Excel Skills for Business Forecasting using Time Series Models. We will be looking at how your business can utilise time series data sets to understand the different components underlying this data, and then apply the relevant model depending on these components. We will look at a range of business forecasting methods, and sometimes, more than one method may be needed! The models we look at are: Naïve Forecasting, Moving Averages, Trend-fitting, Simple Exponential Smoothing, Holt’s Exponential Smoothing, Winters Exponential Smoothing, and Decomposition. This course then continues in our second course in this specialisation which looks at Regression Models, and our third course in this specialisation which looks at Judgmental Forecasting. #EveryoneSayWow
What's included
2 videos3 readings
Show info about module content
2 videos•Total 2 minutes
Excel Skills for Business Forecasting Introduction•1 minute
Course introduction•2 minutes
3 readings•Total 30 minutes
Welcome to Excel Time Series Models for Business Forecasting•10 minutes
Course goals and weekly learning objectives•10 minutes
Important information about versions and regions•10 minutes
Time Series Models
Module 2•2 hours to complete
Module details
In this module, we explore the context and purpose of business forecasting and the three types of business forecasting — time series, regression, and judgmental. This course focuses on time series models. We will learn about time series models, as well as the component of time series data. We will then look at a preliminary forecasting method — Average Forecasts. Once we have a forecast, we need a tool to judge the accuracy of the forecasts — which are the forecasts and the error criterion calculated from these.
What's included
4 videos4 readings3 assignments
Show info about module content
4 videos•Total 43 minutes
Time Series Models•11 minutes
Components of Time Series Data•11 minutes
Average Forecasts•9 minutes
Errors and Error Criterion•12 minutes
4 readings•Total 55 minutes
Read me before you start: Quizzes and Navigation•10 minutes
Download the Week 1 workbooks•5 minutes
Week 1 Toolbox•10 minutes
Week 1 Practice Challenge•30 minutes
3 assignments•Total 30 minutes
Components of Time Series Data•10 minutes
Average Forecasts•10 minutes
Errors and Error Criterion•10 minutes
Level Time Series
Module 3•2 hours to complete
Module details
In this module, we explore different time series forecasting methods available for data that is level.
What's included
5 videos2 readings5 assignments
Show info about module content
5 videos•Total 45 minutes
Level Time Series•8 minutes
Naïve Forecasts•9 minutes
Moving Average Forecasts•8 minutes
Simple Exponential Smoothing•11 minutes
Solver for SES Forecasting•9 minutes
2 readings•Total 15 minutes
Download the Week 2 workbooks•5 minutes
Week 2 Toolbox•10 minutes
5 assignments•Total 80 minutes
Naïve Forecasts•10 minutes
Moving Average Forecasts•10 minutes
Simple Exponential Smoothing•10 minutes
Solver for SES Forecasting•10 minutes
Assessment — weeks 1 and 2•40 minutes
Trending Time Series
Module 4•2 hours to complete
Module details
In this module, we explore different time series forecasting methods available for data that is trending.
What's included
4 videos3 readings3 assignments
Show info about module content
4 videos•Total 38 minutes
Trending Time Series•7 minutes
Trend-fitting•10 minutes
Holt's Exponential Smoothing•11 minutes
Solver for HES Forecasting•10 minutes
3 readings•Total 45 minutes
Download the Week 3 workbooks•5 minutes
Week 3 Toolbox•10 minutes
Week 3 Practice Challenge•30 minutes
3 assignments•Total 30 minutes
Trend-fitting•10 minutes
Holt's Exponential Smoothing•10 minutes
Solver for HES Forecasting•10 minutes
Seasonal Time Series
Module 5•2 hours to complete
Module details
In this module, we explore a time series forecasting method (Winters Exponential Smoothing) available for data that is seasonal.
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What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.
Is financial aid available?
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