This programme empowers you with the skills and confidence to exploit opportunities and accelerate data-driven investing decisions. Through lectures, real-world case studies, discussions, and hands-on exercises you will gain insights into various real-world applications.
DurationThis programme empowers you with the skills and confidence to exploit opportunities and accelerate data-driven investing decisions. Through lectures, real-world case studies, discussions, and hands-on exercises you will gain insights into various real-world applications of alternative data and machine learning in investing decisions.
Learning Objectives:
Core Focus:
The Asian Institute of Digital Finance (AIDF) is a university-level institute in the National University of Singapore (NUS), jointly founded by The Monetary Authority of Singapore (MAS), the National Research Foundation (NRF) and NUS.
AIDF aspires to be a thought leader, a FinTech knowledge hub, and an experimental site for developing digital financial technologies as well as for nurturing current and future FinTech researchers and practitioners in Asia.
Studying machine learning is beneficial due to the high demand for these skills across various industries, the ability to solve complex problems, automate processes, and provide personalised recommendations.
This course focus on the Artificial Intelligence (AI) and Machine Learning in Risk Assessment utilize advanced algorithms and data-driven tools to analyse workplace data, identify potential hazards, and predict safety risks.
Machine learning techniques have revolutionized the financial services industry by enabling the automatic extraction of features from data to solve various predictive tasks.
The AWS Certified SysOps Administrator – Associate validates technical skills and experience in designing and implementing AWS services to derive value from data
In this four-week course, you will dive into the basics of machine learning using python; a well-known programming language. Get introduced to data exploration and discover the various machine learning approaches like supervised and unsupervised learning, regression, and classifications and more.
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