AI & Machine Learning in Finance: Certification Programme
- Introduce core AI/ML concepts and how they're transforming finance.
- Introduction to AI, ML, and Data Science
- Basics of Python for Finance
- Financial Data Types: Stocks, Bonds, Derivatives
- Time Series Analysis Basics
- Supervised vs Unsupervised Learning
- Introduction to Financial Modeling
- Ethics in AI & Finance
- Python
- Jupyter Notebooks
- Pandas, NumPy, Matplotlib
- Predicting Stock Price Trends (Linear Regression)
- Basic Portfolio Optimization
- Apply ML algorithms to real-world financial problems.
- Advanced Time Series Forecasting (ARIMA, LSTM)
- Natural Language Processing (NLP) for Sentiment Analysis
- Fraud Detection with ML
- Credit Risk Scoring
- Reinforcement Learning Basics in Trading
- Feature Engineering for Financial Models
- Scikit-learn, Keras/TensorFlow
- NLTK, spaCy, TextBlob
- Financial APIs (e.g., Yahoo Finance, Alpha Vantage)
- Build a Sentiment-Based Trading Strategy
- Credit Risk Classification Model
- Fraud Detection Dashboard
- Explore cutting-edge AI techniques in quantitative finance.
- Deep Learning for Financial Time Series
- Advanced Portfolio Management with AI
- Generative AI for Financial Simulations
- AI in Algorithmic & High-Frequency Trading
- Explainable AI (XAI) in Finance
- Regulatory and Risk Compliance using AI
- PyTorch, TensorFlow, XGBoost
- Deep Reinforcement Learning Libraries (e.g., OpenAI Gym, Stable Baselines)
- Docker, MLflow for model deployment
- Deep Reinforcement Learning Trading Bot
- XAI Credit Scoring Tool
- AI-Based Robo-Advisor System
Participants design and implement a comprehensive ML solution to a real-world financial problem. Examples:
- End-to-End AI-Powered Robo-Advisor
- AI System for ESG Investment Screening
- Deep Learning Model for Option Pricing
Upon successful completion of each level, participants receive a certificate:
- Level 1: Certified AI in Finance – Foundations
- Level 2: Certified ML Practitioner – Finance Applications
- Level 3: Certified AI Expert in Quantitative Finance
Graduates will be able to:
- Analyze financial data using ML
- Build and deploy finance ML models
- Integrate AI solutions into real-world financial systems
