
Advanced AI in Finance (Level 2)
This advanced course dives deep into cutting-edge AI techniques and their applications in finance. Participants will explore advanced machine learning methods, neural network architectures, and generative AI models, with a strong emphasis on large language models (LLMs). Through practical projects, learners will design sophisticated AI solutions for financial challenges such as risk management, time series forecasting, and algorithmic trading, while addressing ethical and regulatory considerations.
Add a Title
Add paragraph text. Click “Edit Text” to update the font, size and more. To change and reuse text themes, go to Site Styles.
Course Duration:
36 Hours
Level:
Intermediate to Advanced
Course Objectives
Master advanced machine learning techniques like ensemble methods and SVMs.
Develop expertise in deep learning architectures, including CNNs, RNNs, and LSTMs.
Fine-tune and deploy large language models for financial NLP tasks.
Build generative AI models for synthetic data creation and anomaly detection.
Apply reinforcement learning to algorithmic trading and portfolio management.
Address ethical and regulatory issues in deploying AI in finance.

Prerequisites
Solid programming skills in Python.
Strong understanding of machine learning fundamentals.
Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch).
Basic knowledge of financial concepts and statistical analysis.
