This module provides financial professionals with a solid grounding in AI, machine learning (ML), and deep learning, covering key concepts like supervised, unsupervised, and reinforcement learning. Participants will explore real-world financial applications, such as fraud detection and algorithmic trading, while learning the end-to-end process of developing ML models. The module also introduces advanced architectures like neural networks, transformers, and multi-modal models, highlighting their use in finance. Additionally, it raises awareness of ethical challenges—including bias, fairness, and governance—ensuring responsible AI adoption in financial decision-making. This foundational knowledge equips learners to harness AI’s potential while mitigating risks in a regulated industry.
Topic:
Understanding Artificial Intelligence / Machine Learning
Machine Learning Process
Neural Networks, Deep Learning,,DNNs & CNNs
General AI & Narrow AI vs General AI
Bias in AI Systems
Impacts of AI Systems
AI Governance
