Coursera

Machine Learning in Retail (Coursera)

Offered by Coursera Project Network,

Who are your customers? What are they like? How do they interact with your business? This Short Course was created to help analysts better understand their customer behaviour through the power of machine learning. In this course, you will apply two different machine learning techniques to segment customers according to their purchasing behaviour and provide actionable insights for each group. Along the way, you'll also examine some other retail case studies, including web visitor analysis for marketing and store clustering for logistics.

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

By the end, you'll be able to use customer purchase data to group customers using machine learning, analyse your results to extract business insights and apply multiple types of machine learning to generate business value.
This course is unique because it focuses strongly on interpreting your data within a retail context and supports you in identifying opportunities for machine learning in your workplace.
To be successful in this project, you should already be familiar with Python Pandas for data manipulation, filtering and aggregation. You should also have some experience with basic principles of data analysis, like histograms and summary statistics.

Syllabus

Machine learning for Retail

Go to Class

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

Related Courses

Coursera

Google Cloud

Attention Mechanism (Coursera)

CS: Information & Technology

This course will introduce you to the attention mechanism, a powerful technique that allows neural networks to focus on specific parts of an input sequence. You will learn how attention works, and how it can be used to improve the performance of a variety of machine learning tasks, including machine translation, text summarization, and question answering.

Nov 16th 2026

1 Week

Machine Learning Neural Networks Attention

Coursera

Duke University

Introduction to Machine Learning (Coursera)

Data Science

This course will provide you a foundational understanding of machine learning models (logistic regression, multilayer perceptrons, convolutional neural networks, natural language processing, etc.) as well as demonstrate how these models can solve complex problems in a variety of industries, from medical diagnostics to image recognition to text prediction.

Nov 16th 2026

5-12 Weeks

ML NLP Machine Learning

Coursera

Politecnico di Milano,EIT Digital

Data Science for Business Innovation (Coursera)

Statistics & Data Analysis Data Science

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.

Nov 16th 2026

4 Weeks

NoSQL Machine Learning Big Data

Coursera

Google Cloud

ML Pipelines on Google Cloud (Coursera)

Data Science

In this course, you will be learning from ML Engineers and Trainers who work with the state-of-the-art development of ML pipelines here at Google Cloud. The first few modules will cover about TensorFlow Extended (or TFX), which is Google’s production machine learning platform based on TensorFlow for management of ML pipelines and metadata. You will learn about pipeline components and pipeline orchestration with TFX. You will also learn how you can automate your pipeline through continuous integration and continuous deployment, and how to manage ML metadata.

Nov 9th 2026

4 Weeks

ML Machine Learning Google Cloud

Coursera

Nanjing University

Data Processing Using Python (Coursera)

CS: Software Engineering Statistics & Data Analysis

This course is mainly for non-computer majors. It starts with the basic syntax of Python, to how to acquire data in Python locally and from network, to how to present data, then to how to conduct basic and advanced statistic analysis and visualization of data, and finally to how to design a simple GUI to present and process data, advancing level by level.

Nov 23rd 2026

5-12 Weeks

Python Data Structures Data Analysis

Coursera

Illinois Tech

Statistical Learning (Coursera)

Statistics & Data Analysis Data Science

This course offers a deep dive into the world of statistical analysis, equipping learners with cutting-edge techniques to understand and interpret data effectively. We explore a range of methodologies, from regression and classification to advanced approaches like kernel methods and support vector machines, all designed to enhance your data analysis skills.

Nov 9th 2026

5-12 Weeks

Classification Linear Regression Logistic Regression

Coursera

IBM

Machine Learning Rapid Prototyping with IBM Watson Studio (Coursera)

Data Science

An emerging trend in AI is the availability of technologies in which automation is used to select a best-fit model, perform feature engineering and improve model performance via hyperparameter optimization. This automation will provide rapid-prototyping of models and allow the Data Scientist to focus their efforts on applying domain knowledge to fine-tune models. This course will take the learner through the creation of an end-to-end automated pipeline built by Watson Studio’s AutoAI experiment tool, explaining the underlying technology at work as developed by IBM Research.

Nov 9th 2026

4 Weeks

Python Artificial Intelligence Prototyping

Coursera

University of Chicago

Machine Learning: Concepts and Applications (Coursera)

Data Science

This course gives you a comprehensive introduction to both the theory and practice of machine learning. You will learn to use Python along with industry-standard libraries and tools, including Pandas, Scikit-learn, and Tensorflow, to ingest, explore, and prepare data for modeling and then train and evaluate models using a wide variety of techniques. Those techniques include linear regression with ordinary least squares, logistic regression, support vector machines, decision trees and ensembles, clustering, principal component analysis, hidden Markov models, and deep learning.

Nov 16th 2026

5-12 Weeks

Python Machine Learning Clustering

Coursera

University of London

Machine Learning for All (Coursera)

Data Science Computer Science

Machine Learning, often called Artificial Intelligence or AI, is one of the most exciting areas of technology at the moment. We see daily news stories that herald new breakthroughs in facial recognition technology, self driving cars or computers that can have a conversation just like a real person. Machine Learning technology is set to revolutionise almost any area of human life and work, and so will affect all our lives, and so you are likely to want to find out more about it.

Nov 16th 2026

4 Weeks

Artificial Intelligence Machine Learning AI Technology

Coursera

University of Michigan

Applied Text Mining in Python (Coursera)

Statistics & Data Analysis Data Science

This course will introduce the learner to text mining and text manipulation basics. The course begins with an understanding of how text is handled by python, the structure of text both to the machine and to humans, and an overview of the nltk framework for manipulating text. The second week focuses on common manipulation needs, including regular expressions (searching for text), cleaning text, and preparing text for use by machine learning processes. The third week will apply basic natural language processing methods to text, and demonstrate how text classification is accomplished. The final week will explore more advanced methods for detecting the topics in documents and grouping them by similarity (topic modelling).

Nov 9th 2026

4 Weeks

Programming Python Machine Learning

Coursera

Google Cloud

Preparing for the Google Cloud Professional Data Engineer Exam (Coursera)

CS: Information & Technology Computer Science

From the course: "The best way to prepare for the exam is to be competent in the skills required of the job." This course uses a top-down approach to recognize knowledge and skills already known, and to surface information and skill areas for additional preparation. You can use this course to help create your own custom preparation plan. It helps you distinguish what you know from what you don't know. And it helps you develop and practice skills required of practitioners who perform this job.

Nov 16th 2026

5-12 Weeks

Machine Learning Data Engineer Google Cloud

Coursera

University of Illinois at Urbana-Champaign

Machine Learning for Accounting with Python (Coursera)

Data Science

This course, Machine Learning for Accounting with Python, introduces machine learning algorithms (models) and their applications in accounting problems. It covers classification, regression, clustering, text analysis, time series analysis. It also discusses model evaluation and model optimization. This course provides an entry point for students to be able to apply proper machine learning models on business related datasets with Python to solve various problems.

Nov 16th 2026

5-12 Weeks

Algorithms Machine Learning Clustering