The CFA Institute has introduced a Data Science for Investment Professionals Certificate, which is aimed at investment professionals. The goal of the certificate programme is to offer present or future investment professionals practical knowledge of the principles of AI and machine learning techniques and how they are put into practice in the investment process.
The Certificate consists of five interactive courses that last about 100 hours of study time in total and can be completed at the participant’s own pace. The final 90-minute evaluation comes after the completion of the courses. The five courses are Data and Statistics Foundation, Machine Learning, Natural Language Processing, Mitigating Biases in the Data Science Pipeline, and Statistics for Machine Learning. In addition to educational videos, coding labs, and case studies from business professionals, the course’s material emphasises practical application.
Participants will gain knowledge of how to define and evaluate machine learning techniques, use machine learning to solve investment-related challenges, and select and develop data visualisations employing Python and R. The certificate programme will also assist learners in using natural language processing to make choices regarding investments and in teaching machine learning concepts to non-specialist audiences. Participants will also receive training in evaluating and minimising biases in machine learning.
No prior data science knowledge is necessary for those signing up for the Data Science for Investment Professionals Certificate, making it ideal for people from a variety of backgrounds. Investment professionals who are working in or planning to work in positions like investment analyst, portfolio manager, relationship manager, and trader are among those most likely to gain from the certificate.
Only one out of every four investment professionals who want to obtain the skills and knowledge they need is diligently doing so, according to Richard Fernand, Head of Certificate Management at CFA Institute. However, in order to close the skills gap, every individual in a role involving investments will need to be aware of how to use data science, machine learning, and AI techniques.
“It equips learners with the knowledge to understand the application of data science in the investment process, as well as the language to be able to explain and translate machine learning concepts and their application to real-world investment problems. These skills will be key for professionals wishing to position themselves for the growing number of jobs found at the intersection of data science and investment management,” Fernand
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