FINANCIAL DATA SCIENCE
OVERVIEW
This unit introduces the basic processes of data science as they apply to finance, aimed at students interested in the expanding FinTech industry. Emphasis is placed on building computational, statistical, and analytical abilities essential for data-driven financial analysis within FinTech. Learners will apply their skills through hands-on case studies covering areas like financial data management, visualization, risk analysis, prediction, consumer analytics, and trading.
Financial Data Science offers applied learning grounded in theory. Lectures discuss data science topics such as regression, classification, data management, visualization, clustering, and machine learning, supported by real-world examples. Students work with tools including Excel, SQL, R, and Python, and access industry-standard financial databases.
FINANCIAL DATA SCIENCE
LEARNING OUTCOMES
On successful completion of the following units, you will be able to:
- Identify fundamental economic and psychological issues in the current financial system.
- Explore fundamental techniques in blockchain, machine learning and artificial intelligence
- Work productively in a group to evaluate how major advances in blockchain, machine learning and artificial intelligence are applicable to finance problems.
- Analyse recent developments in FinTech and its impact in transforming the finance industry.
- Discover the risks arising from FinTech and understand the dynamics between the innovations and regulations.