Excel Time Series Models for Business Forecasting
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Course Summary
Learn how to use Excel for business forecasting and time series analysis in this comprehensive course. Gain practical skills and insights to make informed decisions and drive business success.Key Learning Points
- Learn to use Excel for time series forecasting and analysis
- Apply forecasting techniques to real-world business problems
- Develop skills to make informed decisions and drive business success
Job Positions & Salaries of people who have taken this course might have
- USA: $60,000 - $110,000
- India: ₹350,000 - ₹1,200,000
- Spain: €25,000 - €50,000
- USA: $60,000 - $110,000
- India: ₹350,000 - ₹1,200,000
- Spain: €25,000 - €50,000
- USA: $50,000 - $95,000
- India: ₹300,000 - ₹1,000,000
- Spain: €22,000 - €45,000
- USA: $60,000 - $110,000
- India: ₹350,000 - ₹1,200,000
- Spain: €25,000 - €50,000
- USA: $50,000 - $95,000
- India: ₹300,000 - ₹1,000,000
- Spain: €22,000 - €45,000
- USA: $70,000 - $125,000
- India: ₹450,000 - ₹1,500,000
- Spain: €30,000 - €60,000
Related Topics for further study
Learning Outcomes
- Apply forecasting techniques to real-world business problems
- Use Excel to analyze and interpret time series data
- Make informed decisions based on data insights
Prerequisites or good to have knowledge before taking this course
- Basic knowledge of Excel
- Familiarity with statistical concepts
Course Difficulty Level
IntermediateCourse Format
- Online self-paced
- Video lectures
- Hands-on exercises
- Quizzes and assessments
Similar Courses
- Data Visualization with Excel
- Excel Skills for Business: Essentials
- Data Analysis with Excel
Related Education Paths
Notable People in This Field
- Nate Silver
- Edward Tufte
Related Books
Description
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.
Outline
- Welcome and Critical Information
- Course introduction
- Welcome to Excel Time Series Models for Business Forecasting
- Course goals and weekly learning objectives
- Important information about versions and regions
- Time Series Models
- Time Series Models
- Components of Time Series Data
- Average Forecasts
- Errors and Error Criterion
- Read me before you start: Quizzes and Navigation
- Download the Week 1 workbooks
- Week 1 Toolbox
- Week 1 Practice Challenge
- Components of Time Series Data
- Average Forecasts
- Errors and Error Criterion
- Level Time Series
- Level Time Series
- Naïve Forecasts
- Moving Average Forecasts
- Simple Exponential Smoothing
- Solver for SES Forecasting
- Download the Week 2 workbooks
- Week 2 Toolbox
- Naïve Forecasts
- Moving Average Forecasts
- Simple Exponential Smoothing
- Solver for SES Forecasting
- Assessment — weeks 1 and 2
- Trending Time Series
- Trending Time Series
- Trend-fitting
- Holt's Exponential Smoothing
- Solver for HES Forecasting
- Download the Week 3 workbooks
- Week 3 Toolbox
- Week 3 Practice Challenge
- Trend-fitting
- Holt's Exponential Smoothing
- Solver for HES Forecasting
- Seasonal Time Series
- Seasonal Time Series
- Winters Exponential Smoothing — Seeds
- Winters Exponential Smoothing — Forecasts
- Solver for WES Forecasts
- Download the Week 4 workbooks
- Week 4 Toolbox
- Winters Exponential Smoothing — Seeds
- Winters Exponential Smoothing — Forecasts
- Solver for WES Forecasts
- Assessment — weeks 3 and 4
- Decomposition
- Decomposition
- Decomposition — De-seasonalising
- Decomposition — De-trending and Forecasting
- Autocorrelation Functions for Testing our Components
- Download the Week 5 workbooks
- Week 5 Toolbox
- Decomposition — De-seasonalising
- Decomposition — De-trending and Forecasting
- Autocorrelation Functions for Testing our Components
- Final assessment — all course content
Summary of User Reviews
Discover how to use Excel for business forecasting and time series analysis in this highly-rated course on Coursera. Students have praised the course for its practicality and real-world application, making it a great resource for professionals looking to improve their forecasting skills.Key Aspect Users Liked About This Course
Many users have praised the practicality and real-world application of the course content.Pros from User Reviews
- The course is well-structured and easy to follow.
- The instructors are knowledgeable and engaging.
- The course provides a good balance of theory and practical exercises.
- The course covers a wide range of forecasting techniques and models.
- The course includes plenty of examples and case studies to help students understand the material.
Cons from User Reviews
- Some users have found the course content to be too basic for their needs.
- The course may not be suitable for advanced users who are already familiar with forecasting techniques.
- Some users have experienced technical difficulties with the course platform.
- The course may require a significant time commitment to complete.
- The course does not provide much opportunity for interaction with other students.
Dr Prashan S. M. Karunaratne
5 Raiting
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Excel Time Series Models for Business Forecasting
- 5
-
![]()
![]()
![]()
![]()
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This course explores different time series business forecasting methods. We will learn about the theoretical methods and apply these methods to business data using Microsoft Excel....
