This course is uniquely tailored to the needs of investment professionals or those with investment industry knowledge who want to develop a basic, practical understanding of machine learning techniques and how they are used in the investment process. Incorporating real-life case studies, this course covers both the technical and the “soft skills†necessary for investment professionals to stay relevant.
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.
