Machine Learning for Predictive Analytics in Business

About

Machine learning has gained widespread recognition for its significant contributions to various facets of business operations, including tasks such as fraud detection, sales forecasting, inventory pricing, and consumer segmentation. This course is tailored to introduce business students to the world of machine learning. It places a strong emphasis on predictive analytics, empowering students to address business challenges using data-driven machine learning algorithms. The course is comprehensive, offering a balanced blend of theory and practical application. It covers essential mathematical and statistical concepts and guides students in mastering Python programming from scratch. Each class comprises both theoretical lectures and practical workshops. To ensure active participation, students are required to bring their own laptops to class.

Preliminary assignment: Several questions and tasks related to mathematical fundamentals and the installation of Python.

Class 1: Introduction and getting started with Python

Class 2: Data manipulation using Python

Class 3: Data visualization in Python

Class 4: Linear regression

Class 5: Logistic regression

Class 6: Artificial neural networks

Feedback activity: A small assignment (with several questions)

Class 7: K-nearest neighbors and naive Bayes

Class 8: Tree-based models

Class 9: Support-vector machines

Class 10: Cluster analysis

Class 11: Course review and Q&A for the exam

Course leader

Raghava Rao Mukkamala - Department of Digitalisation

Target group

This is a graduate level course. CBS Summer University courses at Copenhagen Business School is open to all and welcomes domestic and international students as well as professionals.

Course aim

Have a good understanding of the fundamental issues and challenges of machine learning

Appropriately choose and appraise machine learning algorithms for predictive analytics in business

Effectively use Python to process, summarize and visualize business data

Effectively use Python to develop machine learning algorithms to solve business problems

Fee info