Machine Learning for Decision Making

Imperial College Business School

Imperial College Business School

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Who should attend

This international programme is designed for data and technology professionals & students interested in learning more about the field of machine learning. The programme content is applicable across industries from banking and financial services, consulting, education, and energy to healthcare, IT products and services, and retail.

About the course

Imperial Machine Learning for Decision Making is an immersive and interactive online programme which will expand your understanding of machine learning and teach you the tools and techniques used for applying machine learning to business scenarios.

The ten week online programme draws on expertise from Imperial College Business School faculty, industry experts and case studies. You will have the opportunity to apply your learning to real life business problems, using analytical techniques such as clustering, classification and regression. You will also draw on the expertise of your peers to enable you to communicate credibly with those who have deep technical knowledge in the field, having a greater impact within your organisation.

You will experience live online teaching sessions, video lectures, interactive activities and assignments whilst receiving personal support from a dedicated Learning Team.

You will finish the programme prepared to implement your learnings, and with a verified Digital Certificate from Imperial College Business School Executive Education.

Learning objectives

Characterise the fundamental machine learning problem and outline the steps in a machine learning project

Outline the steps to selecting a machine learning model and explain why we may not be able to draw meaningful conclusions from experience

Differentiate between ranking and prediction problems

Understand and apply technical tools and methods such as k-nearest neighbours and the Naive Bayes Theorem to real life problems

Define proximity for clustering methods and understand the steps involved in applying them

What you will learn

Module 1: Introduction to Machine Learning

Module 2: The Fundamental Limits of Machine Learning

Module 3: Evaluating Predictive Performance (I)

Module 4: Evaluating Predictive Performance (II)

Module 5: Evaluating Predictive Performance (III)

Module 6: K-Nearest Neighbours

Module 7: Naive Bayes

Module 8: Classification and Regression Trees

Module 9: Cluster Analysis

Module 10: Final Assignment

Experts

Wolfram Wiesemann

Summary Dr Wolfram Wiesemann joined Imperial College Business School as an assistant professor in January 2013. His research focuses on the development of tractable computational methods for the solution of stochastic and robust optimisation problems, as well as applications in operations managem...

Videos and materials

Machine Learning for Decision Making at Imperial College Business School

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Disclaimer

Coursalytics is an independent platform to find, compare, and book executive courses. Coursalytics is not endorsed by, sponsored by, or otherwise affiliated with any business school or university.

Full disclaimer.

Read more about Business Analytics

What will you learn from Business Analytics courses? First of all, you will learn about the profession of a business analyst, his duties, and what such a specialist does. You will get various soft skills, such as organizing teamwork, for example, acc...

Read more about Information Technology

A large part of the courses provides basic information so the students are not required to have any IT qualifications before enrolling. Most of the IT learning programs are also broken down into specific areas of interest, such as systems analysis, a...

Because of COVID-19, many providers are cancelling or postponing in-person programs or providing online participation options.

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