Machine Learning for Investment Professionals
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Course overview
- Provider
- Coursera
- Course type
- Free online course
- Level
- Beginner
- Deadline
- Flexible
- Duration
- 17 hours
- Certificate
- Paid Certificate Available
- Course author
- Anastasia Diakaki
-
Describe how machine learning applications can address real-world investment problems
Explain machine learning concepts and techniques to a non-expert audience
Utilize the language of data science when working with data scientists and data engineers
Apply the CFA Institute Ethical Decision-Making Framework to machine learning dilemmas
Description
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.
