Market Basket Analysis
Market basket analysis is a data mining technique used by retailers to boost sales and analyze customers' purchasing patterns. In this project, you will perform a market basket analysis for "The Bread Basket," a bakery located in Edinburgh. The data set has 20507 entries, over 9000 transactions, and 4 columns.
4.3 (26 Reviews)

Language
- English
Topic
- Artificial Intelligence
Industries
- Retail
Enrollment Count
- 351
Skills You Will Learn
- Machine Learning, Artificial Intelligence, Data Science
Offered By
- IBM
Estimated Effort
- 2 hours
Platform
- SkillsNetwork
Last Update
- May 7, 2025
This basket can be used to create recommendations for shopping, product ranges, promotional offers, and placement on supermarket shelves.
Market basket analysis is a powerful tool for turning a huge number of customer transactions into simple, easy-to-visualize rules used to promote a product and build sales recommendations.
What you will learn
- Download and pre-preparation data - download and change of a DataSet structure necessary for market basket analysis.
- Data Visualizations - preliminary market basket analysis.
- Association Rule - construction and analysis of associative rules.
- Visualization of Association Rules - plotting a dynamic graph that reflects the associative rules.
Prerequisites

Language
- English
Topic
- Artificial Intelligence
Industries
- Retail
Enrollment Count
- 351
Skills You Will Learn
- Machine Learning, Artificial Intelligence, Data Science
Offered By
- IBM
Estimated Effort
- 2 hours
Platform
- SkillsNetwork
Last Update
- May 7, 2025
Instructors
Yaroslav Vyklyuk
Full Professor, Doctor of Computer Science, PhD
Dr. Yaroslav Vyklyuk is a full professor at the Lviv Polytechnic National University, Department of Artificial Intelligence Systems. He is an author of over 210 scientific works, 10 monographs, and books, a member of the Editorial Board of 6 international scientific journals, member of the Academic Councils on protection Ph.D. and DrSc thesis in "Mathematical modeling and computational methods". Research Interests: Data Science, Applied System Analysis, Mathematical Modeling, and Decision Making of Complex Dynamic Systems (socio-economic, geographical, tourist, and crisis systems) using Artificial Intelligence Technology, DataMining, Big Data, Parallel Calculations, Statistics, Econometrics, Econophysics and other Advanced Mathematical Methods with implementation into information, WEB, and geographic information systems.
Read moreOlha Vdovichena
Content Creator
Olha Vdovichena – associate professor Department of Management, Marketing and International logistics Chernivtsi Institute of Trade and Economic of State University of Trade and Economic. She is an author of over 93 scientific works, 17 monographs (sections of the monographs), and books, a member of the Editorial Board of scientific journal "Journal Chernivtsi Institute of Trade and Economic of State University of Trade and Economic. Economic sciences". She defended her doctoral dissertation on the topic "Exhibition and trade fair activity as a factor of socio-economic development of the region" and became an Associate Professor of the Department of Commodity Science and Marketing. Olha’s scientific interests focus on research of development of an exhibition activity as a factor of socio-economic growth of the region; retail, marketing, logistics; improving management processes of international investments, regional economy and tourism sphere; formation of mechanisms regulating macroeconomic imbalances in both national and global economies under the conditions of inclusive development and bio-economic orientation.
Read moreKateryna Hazdiuk
PhD of Software Engineering
I am an assistant professor at the Yuriy Fedcovych Chernivtsi National University, Software of Computer Systems Department; an author of over 40 scientific works and 10 training manuals. Research Interests: Mathematical Modeling of Complex Dynamic Systems (bio-like systems, socio-economic, geographical systems), Data Science, Decision Making using Artificial Intelligence Technology, DataMining, Big Data, Parallel Calculations, Statistics, and other methods.
Read more