Forecasting in Business and Economics
This microcredential introduces you to optimal forecasting models for common business problems and decisions.
Duration
6 weeksWeekly study
10 hours
Forecasting in Business and Economics
Learn about forecasting methods for use in business and economics.
This microcredential equips you with knowledge and skills for time series forecasting, by working with real-world data and industry-friendly software. You will learn how to analyse time series to detect patterns and apply forecasting models, which will enable you to forecast future values in the series. These skills can be used to help with decision-making, budgeting, price-setting, rostering, and more.
Syllabus
Week 1
Introduction to Forecasting
Let's get started
Meet your teaching team and other learners, and find key information about this course, including useful tips and links to help you get the most out of your learning.
What is Forecasting?
Basic concepts, applications and steps in time series forecasting.
Forecastability, Considerations and Methods
Conditions affecting forecasting, additional considerations, and basic forecasting methods.
Weekly Wrap
Reflect on the key ideas presented this week and find out what's coming up in Week 2.
Week 2
Visualisation and Forecasting with BigML
Projects, Sources, Datasets and Time Series
An overview of forecasting in BigML and its basic functions.
Forecasting Demonstration
Demonstration of a new forecasting task involving commodity prices.
Weekly Wrap
Reflect on the key ideas presented this week and find out what’s coming up in Week 3.
Week 3
Forecasting Models
Modelling Fundamentals
Model notation and components, naïve and average methods, and an introduction to exponential smoothing.
Simple Exponential Smoothing
Simple exponential smoothing in the weighted average and component forms.
Double Exponential Smoothing
Double exponential smoothing for additive and multiplicative trends.
Weekly Wrap
Reflect on the key ideas presented this week and find out what's coming up in Week 4.
Week 4
More Forecasting Models and Model Selection
Triple Exponential Smoothing
Triple exponential smoothing with additive and multiplicative seasonality.
Evaluation Metrics
AIC, BIC, MAE, MSE and R-squared.
Weekly Wrap
Reflect on the key ideas presented this week and find out what’s coming up in Week 5.
Week 5
Application
Yearly Forecasting
Yearly forecasting using the commodity prices dataset again.
Quarterly, Monthly and Weekly Forecasting
Case studies for quarterly, monthly and weekly forecasts.
Daily Forecasting
Daily forecasting using data about webpage visits.
Weekly Wrap
Reflect on your learning from this week as we prepare to focus on your assessment task, which we'll be looking at in more detail next week.
Week 6
Assessment, Summary, and Next Steps
Assessment Preparation and Submission
Learn practical tips and information about how to complete and submit your assessment. Reflect on what you've learnt throughout this course, and how you'll integrate this into your assessment task.
Course Wrap
Reflect on what you’ve learnt over the duration of this course, and find out more about how to use your credential before considering the next steps of your learning journey.
Learning on this course
On every step of the course you can meet other learners, share your ideas and join in with active discussions in the comments.
What will you achieve?
By the end of the course, you‘ll be able to...
- Recognise forecasting opportunities and potential benefits in various business and economics contexts.
- Identify level, trend, seasonality, and error components of a time series and distinguish between additive and multiplicative forecasting models.
- Differentiate popular forecasting models based on simple/ double/ triple exponential smoothing techniques and carry out their comparative performance evaluation.
- Propose and evaluate practical solutions for a given business and economics forecasting problem using a state-of-the-art cloud-based technology platform.
Who is the course for?
There is a rising demand for evidence-based decision-making in business and economics using newly available data and modern quantitative methods including time series forecasting. This microcredential aims to assist professionals, managers, consultants, public servants, research analysts, and other decision-makers with uplifting their skills to include data-driven insights in their decision-making.
What software or tools do you need?
In this microcredential, you will be using the machine learning software BigML. You be able to use it on a special licence by enrolling in this course.
Who will you learn with?
Mehmet Ulubasoglu is a Professor of Economics in the Department of Economics at Deakin Business School. Mehmet is currently the Head of the Department of Economics.
Hemant Pullabhotla is a Lecturer of Economics in the Department of Economics, Deakin Business School.
Dr. Shuddha is Senior Lecturer at Deakin Business School. He specialises in sustainability issues relevant to energy, environment & climate change.
Who developed the course?
Deakin University
Deakin University is one of Australia’s largest universities with more than 61,000 students and over 15,000 online.
Established
1974Location
Melbourne, AustraliaWorld ranking
Top 280Source: QS World University Rankings 2021
Learning on FutureLearn
Your learning, your rules
- Courses are split into weeks, activities, and steps to help you keep track of your learning
- Learn through a mix of bite-sized videos, long- and short-form articles, audio, and practical activities
- Stay motivated by using the Progress page to keep track of your step completion and assessment scores
Join a global classroom
- Experience the power of social learning, and get inspired by an international network of learners
- Share ideas with your peers and course educators on every step of the course
- Join the conversation by reading, @ing, liking, bookmarking, and replying to comments from others
Map your progress
- As you work through the course, use notifications and the Progress page to guide your learning
- Whenever you’re ready, mark each step as complete, you’re in control
- Complete 90% of course steps and all of the assessments to earn your certificate
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