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Anastasia Diakaki, Shreenivas Kunte, CFA, CIPM, and Neil Govier, CFA
This Specialization 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....
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This Specialization 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. Through the three courses, you will learn techniques for presenting data and importance of the “data story”, produce data visualizations using Python, assess and apply probability concepts to investing scenarios, compare simple time-series models and understand their limitations, discover how machine learning applications can address investment problems, and understand how to apply the CFA Institute Ethical Decision-Making Framework to machine learning dilemmas. All that you learn in this Specialization will give you the knowledge and confidence to explain clearly and “translate” machine learning concepts and their application to real-world investment problems to a non-expert audience and clients. Check out this short video overview.
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What's inside

Three courses

Machine Learning for Investment Professionals

(0 hours)
This course is for investment professionals who want to learn about machine learning techniques and how they are used in the investment process. You will learn how to distinguish between supervised and unsupervised machine learning and deep learning, describe how machine learning algorithm performance is evaluated, and describe supervised and unsupervised machine learning algorithms.

Statistics for Machine Learning for Investment Professionals

(0 hours)
One of the biggest changes in the past decade is the rapid adoption of machine learning, AI, and big data in investment decision making. This course introduces learners with knowledge of the investment industry to foundational statistical concepts underpinning machine learning as well as advanced AI techniques. This course demonstrates core modeling frameworks along with carefully selected real-world investment practice examples.

Data and Statistics Foundation for Investment Professionals

(0 hours)
Aimed at investment professionals, this course introduces basic data and statistical techniques for data analysis, big data, and machine learning. It covers statistical measures, distributions, data visualization, sampling theory, and hypothesis formulation for investment problems.

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