Foundations of strategic business analytics (Coursera)

Offered by ESSEC Business School,
Foundations of strategic business analytics (Coursera)

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.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

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.
Course 1 of 4 in the Strategic Business Analytics Specialization.

Syllabus

WEEK 1
Introduction to Strategic Business Analytics
In this module, we will introduce you to the course and instructional approach. You will learn that Strategic Business Analytics relies on four distinct skills: IT, Analytics, Business and Communication.
Finding groups within Data
In this module, you will learn how identifying groups of observations enables you to improve business efficiency. You will then learn to create those groups in a business-oriented and actionable way. We will use examples to illustrate various concepts. The assessments will also provide you with opportunities to replicate these examples.

WEEK 2
Factors leading to events
In this module, you will learn why using rigorous statistical methods to understand the relationship between different events is crucial.
We’ll cover two examples: first, using a credit scoring example, you will learn how to derive information about what makes an individual more or less likely to have a strong credit score? Then, in a second example drawn from HR Analytics, you will learn to estimate what makes an employee more or less likely to leave the company. As usual, we invite you to replicate those examples thanks to the recital and to use the assessments provided at the end of the module to strengthen your understanding of these concepts.

WEEK 3
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.

WEEK 4
Recommendation production and prioritization
So far, you’ve learnt to use Business Analytics to glean important information relevant to the success of your business. In this module, you’ll learn more about how to present your Business Analytics work to a business audience. This module is also important for your final capstone project presentation.You’ll learn that it is important to find an angle, and tell a story.Instead of presenting a list of results that are not connected to each other, you will learn to take your audience by the hand and steer it to the recommendations you want to conclude on.You’ll learn to structure your story and your slides, and master the most used visualization tips and tricks. The assessment at the end of this module will provide an opportunity for you to practice these methods and to prepare the first step of the capstone project.

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Data Science for Business Innovation (Coursera) Coursera
Politecnico di Milano,EIT Digital

Data Science for Business Innovation (Coursera)

The course is a compendium of the must-have expertise in data science for executive and middle-management to foster data-driven innovation. It consists of introductory lectures spanning big data, machine learning, data valorization and communication. Topics cover the essential concepts and intuitions on data needs, data analysis, machine learning methods, respective pros and cons, and practical applicability issues.

Sep 21st 2026
4 Weeks
Mathematical Biostatistics Boot Camp 1 (Coursera) Coursera
Johns Hopkins University

Mathematical Biostatistics Boot Camp 1 (Coursera)

This class presents the fundamental probability and statistical concepts used in elementary data analysis. It will be taught at an introductory level for students with junior or senior college-level mathematical training including a working knowledge of calculus. A small amount of linear algebra and programming are useful for the class, but not required.

Sep 14th 2026
4 Weeks
Using R for Regression and Machine Learning in Investment (Coursera) Coursera
Sungkyunkwan University - SKKU

Using R for Regression and Machine Learning in Investment (Coursera)

In this course, the instructor will discuss various uses of regression in investment problems, and she will extend the discussion to logistic, Lasso, and Ridge regressions. At the same time, the instructor will introduce various concepts of machine learning. You can consider this course as the first step toward using machine learning methodologies in solving investment problems. The course will cover investment analysis topics, but at the same time, make you practice it using R programming. This course's focus is to train you to use various regression methodologies for investment management that you might need to do in your job every day and make you ready for more advanced topics in machine learning.

Sep 21st 2026
2 Weeks
Fundamental Skills in Bioinformatics (Coursera) Coursera
King Abdullah University of Science and Technology (KAUST)

Fundamental Skills in Bioinformatics (Coursera)

The course provides a broad and mainly practical overview of fundamental skills for bioinformatics (and, in general, data analysis). The aim is to support the simultaneous development of quantitative and programming skills for biological and biomedical students with little or no background in programming or quantitative analysis.

Sep 21st 2026
4 Weeks
Oral Communication for Engineering Leaders (Coursera) Coursera
Rice University

Oral Communication for Engineering Leaders (Coursera)

Taught by Rice University communication faculty from the Rice Center for Engineering Leadership (RCEL). This course covers core topics in oral communication: Communication strategy, content, data visualization, and delivery. You’ll learn key principles in: Creating a communication strategy; Developing a clear message and organizing persuasive content; Creating strong visual support; Presenting data effectively; Presenting professionally and confidently; Handling formal presentations, giving pitches, speaking extemporaneously, managing online presentations, and lowering public speaking anxiety.

Sep 21st 2026
5-12 Weeks
Advanced Linear Models for Data Science 1: Least Squares (Coursera) Coursera
Johns Hopkins University

Advanced Linear Models for Data Science 1: Least Squares (Coursera)

Welcome to the Advanced Linear Models for Data Science Class 1: Least Squares. This class is an introduction to least squares from a linear algebraic and mathematical perspective. Before beginning the class make sure that you have the following: a basic understanding of linear algebra and multivariate calculus; a basic understanding of statistics and regression models; at least a little familiarity with proof based mathematics; basic knowledge of the R programming language.

Sep 21st 2026
5-12 Weeks
Analysis and Interpretation of Large-Scale Programs (Coursera) Coursera
Johns Hopkins University

Analysis and Interpretation of Large-Scale Programs (Coursera)

This course is for implementers, managers, funders, and evaluators of health programs targeting women and children in low- and middle-income countries as well as undergraduate and graduate students in health-related fields. Course participants will learn how to 1) transform quantitative components of an evaluation measurement plan into a sound analysis plan to address the evaluation questions, 2) conduct quantitative analyses of primary or secondary surveys or other available data, 3) interpret the meaning of the analysis results and their implications, and 4) disseminate the evaluation findings to program implementers, local and global stakeholders.

Sep 21st 2026
5-12 Weeks
Operations Research (3): Theory (Coursera) Coursera
National Taiwan University

Operations Research (3): Theory (Coursera)

Operations Research (OR) is a field in which people use mathematical and engineering methods to study optimization problems in Business and Management, Economics, Computer Science, Civil Engineering, Electrical Engineering, etc. The series of courses consists of three parts, we focus on deterministic optimization techniques, which is a major part of the field of OR. As the third part of the series, we study mathematical properties of linear programs, integer programs, and nonlinear programs.

Sep 21st 2026
5-12 Weeks
Supply Chain Analytics (Coursera) Coursera
IIT Roorkee

Supply Chain Analytics (Coursera)

Welcome to Supply Chain Analytics! In this course you will learn about advanced decision problems in Supply Chain Management and the application of optimisation formulations and their solutions to address them. The course has been designed to help you advance your career as business analysts, supply chain managers, and other similar roles by learning in-demand skills to increase efficiency, drive organisational growth, and make a positive business impact. The course also offers a good starting point to those with purely academic and research interests.

Sep 21st 2026
5-12 Weeks
Hands-on Text Mining and Analytics (Coursera) Coursera
Yonsei University

Hands-on Text Mining and Analytics (Coursera)

This course provides an unique opportunity for you to learn key components of text mining and analytics aided by the real world datasets and the text mining toolkit written in Java. Hands-on experience in core text mining techniques including text preprocessing, sentiment analysis, and topic modeling help learners be trained to be a competent data scientists.

Sep 21st 2026
5-12 Weeks