What Does MVP Stand For? It’s Not What You Think.
October 7, 2024
Article
Generate Insights with Business Forecasting
Instructor: Assoc Prof Prashan S. M. Karunaratne
9,236 already enrolled
Included with
(245 reviews)
Recommended experience
Intermediate level
You should have familiarity with the Excel user interface, moving around an Excel workbook, and creating basic formulas.
(245 reviews)
Recommended experience
Intermediate level
You should have familiarity with the Excel user interface, moving around an Excel workbook, and creating basic formulas.
Add to your LinkedIn profile
Add this credential to your LinkedIn profile, resume, or CV
Share it on social media and in your performance review
The current state of the world makes business forecasting even more fundamental to the operation of institutions. In this Specialization we focus on Excel Skills for Business Forecasting in three courses — Time Series Models, Regression Models, and Judgmental Forecasting.
In the first course on 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 to forecast for your business' needs.
We then continue in our second course in this specialisation which looks at Regression Models, building causal models for both time series data as well as cross-sectional data. Causal models allow us to develop further business insights and strategy by controlling the inputs to generate the output we desire.
In the third and final course, we explore the role of Judgmental Forecasting, when more quantitative forecasting methods have limitations, and we need to generate further business insights. We will be exploring some structured methodologies to create judgmental business forecasts and explore how Excel can assist us in these judgments. We will bring all these forecasting methods together in a final case study, giving you the opportunity to generate forecasts, which are the inputs to any organisation's planning.
Applied Learning Project
Working with datasets similar to those typically found in a business, you will use quantitative and qualitative forecasting techniques to generate business forecasts. Create charts to visualise data and forecasts. Calculate model errors and use optimisation techniques to minimise these errors and choose the best model parameters. Combine different models and expert judgment to incorporate uncertainty.
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.
This course allows learners to explore Regression Models in order to utilise these models for business forecasting. Unlike Time Series Models, Regression Models are causal models, where we identify certain variables in our business that influence other variables. Regressions model this causality, and then we can use these models in order to forecast, and then plan for our business' needs. We will explore simple regression models, multiple regression models, dummy variable regressions, seasonal variable regressions, as well as autoregressions. Each of these are different forms of regression models, tailored to unique business scenarios, in order to forecast and generate business intelligence for organisations.
In this course, we extend your business forecasting expertise from the first two courses of our Business Forecasting Specialisation on Time Series Models and Regression Models. We will explore the role of judgmental forecasting, when more quantitative forecasting methods have limitations, and we need to generate further business insights. We will be exploring some structured methodologies to create judgmental business forecasts using Business Indicators, Subjective Assessment Methods, and Exploratory Methods. For each of these methods, we will look at how we can use Excel to help us in achieving these judgmental forecasts and how Excel can help us visualising our forecast findings. Being judgmental forecasting methods, we will also look at the role of biases in Business Forecasting,
Macquarie is ranked among the top one per cent of universities in the world, and with a 5-star QS rating, we are recognised for producing graduates who are among the most sought-after professionals in the world. Since our foundation 54 years ago, we have aspired to be a different type of university: one focused on fostering collaboration between students, academics, industry and society.
Unlimited access to 10,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription
Earn a degree from world-class universities - 100% online
Upskill your employees to excel in the digital economy
Over the 3 courses there are 13 modules of content in total. Each module should take 2-5 hours to complete, including watching the videos, doing the quizzes, and working through the assessment.
You should have familiarity with the Excel user interface, moving around an Excel workbook, and creating basic formulas. If you need a refresher, you could do our course Excel Fundamentals for Data Analysis.
Time Series Models and Regression Models can be taken in any order, but you should do both before attempting Judgmental Forecasting as it uses techniques from these courses.
You will be able to transform Time Series and Cross-Sectional data sets into components that produce business insights and forecasts. You will understand how Time Series and Regression Models work and how to create these models to produce robust forecasts. You will learn how to critically analyse the data and the business context to apply structured Judgmental Forecasting methodologies to augment these forecasts.
This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.
If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.
Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate, or you can audit it to view the course materials for free. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.
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. If you only want to read and view the course content, you can audit the course for free. If you cannot afford the fee, you can apply for financial aid.
This Specialization doesn't carry university credit, but some universities may choose to accept Specialization Certificates for credit. Check with your institution to learn more.
These cookies are necessary for the website to function and cannot be switched off in our systems. They are usually only set in response to actions made by you which amount to a request for services, such as setting your privacy preferences, logging in or filling in forms. You can set your browser to block or alert you about these cookies, but some parts of the site will not then work.
These cookies may be set through our site by our advertising partners. They may be used by those companies to build a profile of your interests and show you relevant adverts on other sites. They are based on uniquely identifying your browser and internet device. If you do not allow these cookies, you will experience less targeted advertising.
These cookies allow us to count visits and traffic sources so we can measure and improve the performance of our site. They help us to know which pages are the most and least popular and see how visitors move around the site. If you do not allow these cookies we will not know when you have visited our site, and will not be able to monitor its performance.
These cookies enable the website to provide enhanced functionality and personalization. They may be set by us or by third party providers whose services we have added to our pages. If you do not allow these cookies then some or all of these services may not function properly.