Essential Linear Regressions for Management Consultants

This course contains the use of artificial intelligence.

What is the aim of this course?

During some consulting projects, you may be asked to predict things like sales or the number of customers. You may also be asked to find the relations between different variables and estimate their impact on a specific goal. In such situations, you may use linear regression models. They may prove extremely helpful in projects requiring data analysis and forecasting. In this course, I will teach you how to use essential linear regression models in Excel during consulting projects.

In the course, you will learn the following things:

What are linear regression models, and how can you use them in practice

This course is based on my 15 years of experience as a consultant in top consulting firms and as a Board Member responsible for strategy, performance improvement, and turn-arounds in the biggest firms from the Retail, FMCG, SMG, B2B, and services sectors that I worked for. I have carried out or supervised over 100 different performance improvement projects in different industries that generated a total of 2 billion additional EBITDA. On the basis of what you will find in this course, I have trained in person over 100 consultants, business analysts, and managers who are now Partners in PE and VC funds, Investment Directors and Business Analysts in PE and VC, Operational Directors, COO, CRO, CEO, Directors in Consulting Companies, Board Members, etc. On top of that, my courses on Udemy were already taken by more than 350 000 students, including people working in EY, McKinsey, Walmart, Booz Allen Hamilton, Adidas, Naspers, Alvarez & Marsal, PwC, Dell, Walgreens, Orange, and many others.

I teach through case studies, so you will have a lot of lectures showing examples of analyses and tools that we use. To every lecture, you will find attached (in additional resources) the Excel files as well as additional presentations, materials shown in the lectures, so as a part of this course, you will also get a library of ready-made analyses that can, with certain modifications, be applied by you or your team in your work.

Why have I decided to create this course?

During many consulting projects, you have to analyze data to find the link between different variables and do simple forecasting. Most firms don’t give you the full toolbox that you need to do that. This may lead to huge frustration during consulting projects and a lot of inefficiencies.

Therefore, I have decided to create this course that will help students understand and apply linear regression models. The course will give you the knowledge and insight into real-life case studies that will make your life during a consulting project much easier. Thanks to this course, you will know what and how to do during consulting projects. You will master how to analyze data and draw conclusions from the analyses. On top of that, you will also see how you can fix the most often occurring problems in linear regression models.

To sum it up, I believe that if you want to become a world-class Management Consultant or Business Analyst, you have to have a pretty decent understanding of linear regression models. That is why I highly recommend this course to Management Consultants or Business Analysts, especially those who did not finish business school. The course will help you become an expert in linear regression models at the level of McKinsey, BCG, Bain, and other top consulting firms.

In what way will you benefit from this course?

The course is a practical, step-by-step guide loaded with tons of analyses, tricks, and hints that will significantly improve the speed with which you understand and analyze businesses. There is little theory – mainly examples, a lot of tips from my own experience, as well as other notable examples worth mentioning. Our intention is that, thanks to the course, you will learn:

What are linear regression models, and how can you use them in practice

1. How to create a linear regression model in Excel

2. How to use them for forecasting

3. How to identify potential problems that may occur in the model

4. How to fix the problems

You can also ask me any questions either through the discussion field or by messaging me directly.

How is the course organized?

The course is currently divided into the following sections:

• Introduction. We begin with a little introduction to the course, as well as some general info on how the course is organized

• Essential concepts. In this section, we will discuss the essential concepts that we will use to build and interpret linear regression models. You will also learn how to build a regression model in Excel.

• Potential Problems. In this section, we will discuss potential problems that may occur when you use regression models. Linear Regression only works when certain assumptions are met. If one of those assumptions is not met, your model may give you distorted estimations. That’s why in the section devoted to potential problems, we will discuss the assumptions, how to check them in practice, and what to do if they are not met.

• Case Studies. In the last section, we will go through a series of case studies that will help you master how to use linear regression models in practice.

You will also be able to download many additional resources

1. Useful frameworks and techniques

2. Analyses shown in the course

3. Additional resources

4. Links to additional presentations, articles, and movies

5. Links to books worth reading

At the end of my course, students will be able to…

• What are linear regression models

• How to use them in practice

• How to create a linear regression model in Excel

• How to use linear regression models for forecasting

• How to find the link between different variables

• How to identify potential problems that may occur in the model

• How to fix the problems

Who should take this course? Who should not?

• Management Consultants

• Business Analysts

• Financial Controllers

What will students need to know or do before starting this course?

• Basic or intermediate Excel

• Basic knowledge of economics

• Basic or intermediate knowledge of finance & accounting