Who is this course for?
This course is designed for students, business analysts, and data scientists who want to apply statistical knowledge and techniques to business contexts. For example, it may be suited to experienced statisticians, analysts, engineers who want to move more into a business role.
You will find this course exciting and rewarding if you already have a background in statistics, can use R or another programming language and are familiar with databases and data analysis techniques such as regression, classification, and clustering.
However, it contains a number of recitals and R Studio tutorials which will consolidate your competences, enable you to play more freely with data and explore new features and statistical functions in R.
With this course, you’ll have a first overview on Strategic Business Analytics topics. We’ll discuss a wide variety of applications of Business Analytics. From Marketing to Supply Chain or Credit Scoring and HR Analytics, etc. We’ll cover many different data analytics techniques, each time explaining how to be relevant for your business.
We’ll pay special attention to how you can produce convincing, actionable, and efficient insights. We'll also present you with different data analytics tools to be applied to different types of issues.
By doing so, we’ll help you develop four sets of skills needed to leverage value from data: Analytics, IT, Business and Communication.
By the end of this MOOC, you should be able to approach a business issue using Analytics by (1) qualifying the issue at hand in quantitative terms, (2) conducting relevant data analyses, and (3) presenting your conclusions and recommendations in a business-oriented, actionable and efficient way.
Prerequisites : 1/ Be able to use R or to program 2/ To know the fundamentals of databases, data analysis (regression, classification, clustering)
We give credit to Pauline Glikman, Albane Gaubert, Elias Abou Khalil-Lanvin (Students at ESSEC BUSINESS SCHOOL) for their contribution to this course design.

從本節課中

Predictions and Forecasting

In this module you will learn more about the importance of forecasting the future.
You will learn through examples from various sectors: first, using the previous examples of credit scoring and HR Analytics, you will learn to predict what will happen. Then, you will be introduced to predictive maintenance using survival analysis via a case discussion. Finally, we’ll discuss seasonality in the context of the first example discussed in this MOOC: using analytics for managing your supply chain and logistics better.