Certificate Program in AI for Finance (CPAIF)
- Offered byIndian Institute of Quantitative Finance
Certificate Program in AI for Finance (CPAIF) at Indian Institute of Quantitative Finance Overview
Duration | 9 months |
Start from | Start Now |
Total fee | ₹1.78 Lakh |
Mode of learning | Online |
Official Website | Go to Website |
Credential | Certificate |
Certificate Program in AI for Finance (CPAIF) at Indian Institute of Quantitative Finance Highlights
- Earn a certificate after completion of course from Indian Institute of Quantitative Finance
Certificate Program in AI for Finance (CPAIF) at Indian Institute of Quantitative Finance Course details
Individuals working in investment banking, asset management, or financial services who wish to integrate AI technologies into their workflows
Professionals seeking to enhance their skills in applying AI and machine learning to financial datasets and problems
Overview of AI concepts and machine learning fundamentals
Exploration of how AI technologies are transforming the finance industry
Understanding financial datasets and their unique characteristics
Developing models for forecasting market trends, asset prices, and customer behavior
The Certificate Program in AI for Finance (CPAIF) is designed to equip participants with the knowledge and skills to harness artificial intelligence and machine learning techniques in the financial sector
This program combines theoretical foundations with practical applications, enabling learners to implement AI-driven solutions for various financial challenges
Program Schedule
Saturdays and Sundays
Program Timing
4:00 PM to 8:00 PM
Certificate Program in AI for Finance (CPAIF) at Indian Institute of Quantitative Finance Curriculum
Applied Programming in Python
Python Toolsets & Libraries –
Pandas, Numpy, Scipy
Matplotlib, Seaborn, Bokeh, Plotly
Applied Statistics & Probability
Multivariate Statistics
Distribution Families – Discrete & Continuous
Sampling Estimation & Central Limit Theorems
Decision Theory & Science
Big Data Mining & Manipulation
7 V’s of Big Data - Volume, Velocity, Variability, Variety, Veracity, Value, Visualization
Structured & Unstructured Datasets – Data Massaging & Manipulations
Exploratory Data Analytics (EDA)
Data Extraction, Exploration & Error Handling
Data Cleansing, Transformation & Aggregation
Applied Mathematics for ML
Statistical & Probability Theory & Applications
Linear Algebra & Matrix Vectorized Operations
ML Supervised Learning Methods
Statistical & ML Driven Regression - OLS, MLE, LASSO, RIDGE, Elastic-Net
ML Model Hyper-Parameter Tuning & K-Fold Cross Validation
ML Un-Supervised Learning Methods
Unsupervised & Semi-Supervised Learning
Statistical & ML Driven Clustering & Association - Hierarchal Clustering & Discriminant Analysis, K-Means Clustering, K-Nearest Neighbors (KNN)
ML Deep Learning Methods
Deep Learning - Neural Network (DNN) Intro
Multi Layer Perceptron (MLP)
Artificial Neural Network (ANN)
ML Natural Language Models (NLP)
Unstructured Data Sets & Transformations
ML Driven Textual & Speech Processing
ML Driven Document Classification
AI for Risk Management
Financial Risk Prediction & Estimation
- PD, LGD, EAD, IFRS9 ECL Provisions, Fraud Detection & Forensic Audit
Financial Time Series Forecasting
- Loss (Value-at-Risk/Expected Shortfall), Pre-Provision Net Revenue (PPNR)
AI for Derivative Valuation
Financial Time Series Forecasting
Volatility, Correlations & Covariance, Dynamic Hedging Strategy
Financial Unstructured Data Mining & Analytics
Pricing Sensitivity & Sentiment Analysis
AI for Trading
Automated Algorithmic Trading
Trade Execution Algorithms, Strategy Implementation Algorithms, Stealth/Gaming Algorithms, Arbitrage Exploitation Algorithms
Generative AI for Finance
Financial Text Generation
Synthetic Data Generation
Capstone Project
BFSI industry application project supervised by a BFSI SME expert industry mentor