Certificate Program in AI for Finance (CPAIF)

Build your career in AI for Finance Applications

Live Online Instructor-led Weekend Program
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  • Program Schedule
  • Program Timing
  • Program Start Date

CPAIF Program | AI for Finance Course Highlights

IIQF integrated flagship program covering Data Science (DS) , Machine Learning (ML) & Artificial Intelligence (AI) for Financial Applications

  • Dedicated learning journey tracks for exhaustive coverage of Data Science (DS), Machine Learning (ML) & Artificial Intelligence (AI) methodology, techniques & toolsets
  • Deep-dive coverage of Big Data Analytics & Decision Science, Supervised Learning, Semi-Supervised Learning, Deep Learning, Reinforcement Learning, Natural Language Processing, Model Evaluation, Model Optimization, Model Validation, Model Benchmarking & Model Explainability
  • Focused on building skills & core competencies from scratch-up - Statistics, Probability, Mathematics, Programming, Analytics, Algorithmic Design & Modelling
  • Designed to deliver know-how on BFSI financial use-cases & applications across specialized areas of Risk, Trading, Pricing, Quants & Generative AI
  • Rigorous live classroom lectures from our expert faculty panel constituting BFSI industry subject matter experts & academic researchers
  • Practical hands-on learning through Python prototyping & implementation workshops on front-to-back model building & algorithmic training exercises
  • Renders technical know-how on BFSI industry adoption of AI & ML technology stack, business intelligence (BI) toolkit & deployment infrastructure
  • Coverage of evolving DS, AI & ML areas like Large Language Models, Generative AI, Fraud Risk, Climate & Sustainability Risk
  • BFSI industry mentor-led DS, AI & ML capstone projects and implementation white paper writing

About The Certificate Program in AI for Finance

AI BFSI Career Roles

  • BIG Data Scientist
  • BIG DATA Strategist
  • BIG Data Analytics Expert
  • Synthetic Data Expert
  • BIG Data Engineer
  • Big Data Platform Expert
  • Big Data Owner
  • AI & ML Researcher
  • AI & ML Domain Expert
  • AI & ML Model Validator
  • Explainable AI & ML Expert
  • AI & ML Project Manager
  • AI & ML Product Designer
  • AI & ML Product Owner

AI BFSI Core Competencies

  • Mathematical, statistical & probability skills
    – Differential & integral calculus
    - Linear algebra & matrix operations
    - Vectorized calculations
    – Descriptive & inferential statistics
    - Random events, experiments & expectations
  • Exploratory data analytics skills
    - Big Data merging, manipulating & mining
    - New Age unstructured data Mechanics
    - Data augmentation & visualization
  • Model development & validation skills
    - AI & ML methodology & Techniques
    - AI & ML model performance evaluation, validation & explainability
  • Programming Skills - Model building & deployment in Python
    - Ai & Ml Infrastructure, Architecture & Tech Stack

CPAIF - Key Learning Outcomes

  • Big Data Science
  • Structured & Unstructured Datasets
  • Data Diagnostics, Distribution & De-noising
  • Data Mining, Exploration, MANIPULATIONS & Transformations
  • Data Augmentation & Synthesizing
  • Data Visualization & Storytelling
  • Supervised learning techniques
  • Unsupervised learning techniques
  • Deep learning techniques
  • Reinforcement learning techniques
  • Large natural language learning
  • Model optimization techniques
  • Model performance evaluation
  • AI & ML expandability
  • Model validation testing
Also Available as
Individual Certificate Programs
CPAIF Integrated Learning Tracks

9 Months

  • CPDSF

    3 Months

  • CPMLF

    4 Months

  • + Elective*

    2 Months

+ Capstone Project Assignments (*You can take one or more electives)

CPAIF Track I (CPDSF)

Module 1 - Applied Programming in Python

3 Weeks
  • Python Toolsets & Libraries –
    - Pandas, Numpy, Scipy
    - Matplotlib, Seaborn, Bokeh, Plotly
  • Business Intelligence Tools & Software
    - Tableau, Power BI, Qlik

Module 2 - Applied Statistics & Probability

3 Weeks
  • Multivariate Statistics
  • Distribution Families – Discrete & Continuous
  • Sampling Estimation & Central Limit Theorems
  • Decision Theory & Science
  • Random Experimental & Probabilistic Framework
  • Bayesian Theory, Hypothesis Testing, Inference and Confidence Intervals

Module 3 - Big Data Mining & Manipulation

2 Weeks
  • 7 V’s of Big Data - Volume, Velocity, Variability, Variety, Veracity, Value, Visualization
  • Structured & Unstructured Datasets – Data Massaging & Manipulations
  • High Dimensional Data Handling
  • Financial Datasets - Risk, Treasury, Front Office Pricing & Valuation, Trading, Climate & Sustainability

Module 4 - Exploratory Data Analytics (EDA)

5 Weeks
  • Data Extraction, Exploration & Error Handling
  • Data Cleansing, Transformation & Aggregation
  • Data De-noising, Distribution Fitting & Descriptive Statistics
  • Data Augmentation, Generation & Synthetization
  • Data Statistical Inference & Insights
  • Data Visualization & Storytelling

CPAIF TRACK II (CPMLF)

Module 1 - Applied Mathematics for ML

2 Weeks
  • Statistical & Probability Theory & Applications
  • Linear Algebra & Matrix Vectorized Operations
  • Differential Calculus
  • Integral Calculus
  • Functional Estimation & Global Minima/Maxima Based Optimization
  • Mathematical Modelling & Formulation

Module 2 – ML Supervised Learning Methods

8 Weeks
  • Statistical & ML Driven Regression - OLS, MLE, LASSO, RIDGE, Elastic-Net
  • Statistical & ML Driven Classification - Linear Classifiers (Logistic Logit, Probit Regression), Bagging (CART Decision Tree, Random forest), Boosting (Ada-Boost, XG-Boost), Support Vector Machines (SVM)
  • ML Model Hyper-Parameter Tuning & K-Fold Cross Validation
  • Machine Learning Model Optimization, Performance Evaluation & Model Explainability
  • ML Quantitative Validation Tests

Module 3 - ML Un-Supervised Learning Methods

2 Weeks
  • Unsupervised & Semi-Supervised Learning
  • Statistical & ML Driven Clustering & Association - Hierarchal Clustering & Discriminant Analysis, K-Means Clustering, K-Nearest Neighbors (KNN)

Module 4 - ML Deep Learning Methods

5 Weeks
  • Deep Learning - Neural Network (DNN) Intro
  • Multi Layer Perceptron (MLP)
  • Artificial Neural Network (ANN)
  • Convolutional Neural Networks (CNNs)
  • Recurrent Neural Network (RNN)
  • RNN-Long Short Term Memory (LSTM)
  • RNN - Gated Recurrent Unit (GRU)
  • Deep Reinforcement Learning (DRL)

Module 5 - ML Natural Language Models (NLP)

3 Weeks
  • Unstructured Data Sets & Transformations
  • ML Driven Textual & Speech Processing
  • ML Driven Document Classification
  • ML Driven Image Classification
  • ML Driven Chat-bots

CPAIF TRACK III (Electives)

As part of CPAIF integrated program, IIQF offers any one out of multiple elective specialisation courses however candidates can register for any additional elective by enrolling separately as per the course pricing terms & conditions. At the time of enrolment, one has to choose any one elective from the given options. You can select any one elective from the list provided below:

AI & ML for Risk Management

10 Weeks
  • 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)
  • Financial (Un-) Constrained Optimization
    - Portfolio (CAPM) Optimization, RWA Optimization, Optimal & Effective Hedging
  • Financial Stress Loss Analytics
    - Synthetic Stress Scenarios & Shock-Sizing, Stress Testing & Reverse Stress Testing
  • Financial Unstructured Data Mining & Analytics
    - Image Processing & Classification, Risk Sentiment Indicators

AI & ML for Front Office Valuation & Pricing

10 Weeks
  • Financial Risk Prediction & Estimation
    - Financial Instrument Pricing (Equity, Fixed Income, Commodity, IR, FX, Alternative Asset Classes), Derivative Pricing & Linear Factor Models, Derivative Valuation Adjustments (XVAs – CVA, DVA, MVA, FVA), P&L Attribution
  • Financial Time Series Forecasting
    - Volatility, Correlations & Covariance, Dynamic Hedging Strategy
  • Financial Unstructured Data Mining & Analytics
    - Pricing Sensitivity & Sentiment Analysis

AI & ML for trading

10 Weeks
  • Automated Algorithmic Trading
    - Trade Execution Algorithms, Strategy Implementation Algorithms, Stealth/Gaming Algorithms, Arbitrage Exploitation Algorithms
  • High-frequency Trading

Generative AI for finance

10 Weeks
  • Financial Text Generation
  • Synthetic Data Generation
  • Large Language Models (LLM) based FinGPT

AI & ML for Climate Risk

10 Weeks
  • Climate Physical Risks - Climate Physical Hazards
  • Climate Transition Risks

Capstone Project

1 Month
  • BFSI industry application project supervised by a BFSI SME expert industry mentor

CPAIF Course Calendar

Batch Start Date Fee Mode Time

Why choose AI for Finance Course?

Faculty for AI for Finance

Admission Process in Artificial Intelligence for Finance Course

  • Send Your Application

  • Get on a call with a counsellor

  • Wait for Application Acceptance

  • Pay the fee & join the upcoming batch

Finance your Study

Educational Loans

We are very happy to help you progress to greater heights in your career in every way possible. Education loans available at 0% interest for full time Indian residents. Easy EMI plans available.

Student Aid

Encourages the full time students to enter this domain, benefits, if you are still pursuing formal education.

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