About Course
This diploma program equips learners with the skills and knowledge to harness the power of data in financial decision-making, covering the full spectrum of data analytics applied to financial contexts. The curriculum covers data science fundamentals, including data collection, cleaning, and visualization; financial analytics, including risk analysis, portfolio optimization, and performance measurement; machine learning applications in finance, including predictive modeling, anomaly detection, and algorithmic trading; and data governance, including data quality, data privacy, and regulatory compliance. Students explore the practical application of data analytics in areas such as credit scoring, fraud detection, customer segmentation, and financial forecasting. The program also examines the ethical and regulatory considerations of financial data analytics, including the challenges of algorithmic bias, data privacy, and the responsible use of AI in finance.