An Introduction to Machine Learning in Quantitative Finance
Discover how machine learning can be used to solve financial data problems and create informative insights and predictions with this online course from University College London.
Who is the course for?
This course is designed for anyone interested in machine learning and quantitative finance with a basic background in probability and Python programming.
It will be of particular interest to final-year undergraduate students or MSc students in financial mathematics or related subjects, pursuing a career in quantitative finance or data science.
It will also be suited to practitioners in quantitative finance.
What will you achieve?
By the end of the course, you‘ll be able to…
Describe a high-level picture of machine learning techniques in quantitative finance.
Identify the main categories of machine learning tasks, i.e. supervised learning, unsupervised learning and reinforcement learning.
Apply a general framework of supervised learning to acquire new supervised learning algorithms in a systematic manner.
Describe the mathematics foundation of linear regression with/without regularization and neural networks.
Apply linear regression and neural networks models to solve real-world financial data problems.
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