Online Course – Certified Professional Internship in Excel Skills for Business Forecasting from Macquarie University

Discover insights with business forecasts – Improve your strategic decisions with accurate data and advanced analytics.

Suggested by: Coursera (What is Coursera?)

Professional Certificate

Intermediate level

No prior knowledge required

Time to complete the course

7-day free trial

No unnecessary risks

Skills you will acquire in the course

  • Excel skills in business forecasting
  • Understanding the components of time series data
  • Applying relevant models to data
  • Building causal models for time series data
  • Developing strategic understandings by controlling inputs
  • Researching judicial predictions
  • Methodologies for creating judgmental business forecasts
  • Using Excel to make business judgments
  • Working with business data systems
  • Quantitative and qualitative forecasting techniques
  • Create graphs to visualize data and forecasts
  • Calculating model errors
  • Optimization techniques to minimize errors

What you will learn in the course

Courses for which the course is suitable

  • Data Analyst
  • Strategic planner
  • Project Manager
  • economist
  • Marketing Manager
  • Sales Manager
  • Business consultant
  • Operations Manager
  • Information Systems Analyst
  • Business Forecasting Manager

Internship – 3-part course series

The current situation in the world makes business forecasting a central element for the functioning of institutions. In this specialization, we will focus on Excel skills in business forecasting in three courses:

  • Time series models
  • Regression models
  • Judicial predictions

Course 1: Time Series Models

We will look at how your business can use time series data to understand the different components behind that data, and then implement the relevant model based on those components.

Course 2: Regression Models

We will build causal models for time series data as well as cross-categorical data. Causal models allow us to develop additional strategic understandings by controlling for inputs.

Course 3: Judicial Predictions

We will explore the role of judgmental forecasts when quantitative forecasting methods encounter limitations. We will explore methodologies for creating judgmental business forecasts and see how Excel can help us make these judgments.

Applied Learning Project

Working with data sets similar to those typically found in business, you will use quantitative and qualitative forecasting techniques to produce business forecasts. Create graphs to simulate data and forecasts, calculate model errors, and use optimization techniques to minimize these errors.

Details of the courses that make up the specialization

Time series models in Excel for business forecasting

Course 1
11 hours
4.9 (211 ratings)

What will you learn?

This course explores different methods for business forecasting in time series. The course includes a variety of business forecasting methods for different types of components found in time series data—levels, trends, and seasonality. We will learn about theoretical methods and apply them to business data using Microsoft Excel.

Skills you will gain

  • Microsoft Excel
  • Time series models
  • Business forecasting

Regression Models in Excel for Business Forecasting

Course 2
9 hours
4.9 (100 ratings)

What will you learn?

This course allows you to learn regression models in order to use these models for business forecasting. We will explore simple regression models, multiple regression models, regressions with dummy variables, regressions with seasonal variables, and autoregressions.

Skills you will gain

  • Microsoft Excel
  • Business forecasting
  • Regression models

Judgmental Business Forecasting in Excel

Course 3
10 hours
4.5 (53 ratings)

What will you learn?

In this course, we will expand your expertise in business forecasting from the first two. We will examine several structured methodologies for creating judgmental business forecasts, using business metrics, subjective assessment methods, and exploratory methodologies.