In this course, you will learn how to:
– Distinguish between supervised and unsupervised machine learning and deep learning
– Describe how machine learning algorithm performance is evaluated
– Describe supervised and unsupervised machine learning algorithms and determine the problems they are best suited for
– Describe neural networks, deep learning nets, and reinforcement learning
– Choose an appropriate machine learning algorithm
– Describe the value of integrating machine learning and data projects in the investment process
– Work with data scientists and investment teams to harness information and insights from within large and alternative data sets
– Apply the CFA Institute Ethical Decision-Making Framework to machine learning dilemmas
This course is part of the Data Science for Investment Professionals Specialization offered by CFA Institute.