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  • 01. Python Programming for Finance (PPF)

    3,000₹
    Prerequisites: No Prerequisites | Duration: ~30 hrs + 5 hrs for [CV Preparation, Profile Optimization] + 2.5 hrs for [Mock Interviews] | Mode: Live (Instructor-led) and Recorded (Self-Paced)
    Valid for 6 months
    • M101: Python Fundamentals and Data Structures
    • M102: Control Flow Statements and Exception Handling
    • M103: OOP Concepts for Advanced Programming
    • M104: Data Analytics, Automation, and Multi-Core Processing
    • M105: Python Integrated Mathematics, Statistics, and Finance
    • Interview Guide: Python for Quant Finance Professionals

  • 04. Fixed-Income Investments RM (FIIRM)

    15,000₹
    Prerequisites: Python Programming, Excel | Duration: ~50 hrs + 5 hrs for [CV Preparation, Profile Optimization] + 10 hrs for [Mock Interviews] | Mode: Live (Instructor-led) and Recorded (Self-Paced)
    Valid for 12 months
    • M401: Fixed-Income Market Fundamentals and Products
    • M402: Modeling Term-Structure of Interest Rates
    • M403: Modeling Rates Using Stochastic Interest Rates Models
    • M404: Pricing and Valuation of Fixed-Income Securities
    • M405: Bond Cashflow Mapping Procedures and Portfolio Risk
    • Interview Guide: Fixed-Income Investments and Risk Manage..

  • 07. Quant Market Risk Management (QMRM)

    20,000₹
    Prerequisites: Python Programming, Excel | Duration: ~85 hrs + 5 hrs for [CV Preparation, Profile Optimization] + 10 hrs for [Mock Interviews] | Mode: Live (Instructor-led) and Recorded (Self-Paced)
    Valid for 15 months
    • M701: Introduction to Market Risk Management Fundamentals
    • M702: Sensitivity Analysis and Hedging Techniques
    • M703: Scenario Analysis and Portfolio Stress Testing
    • M704: VaR Methodologies and Portfolio Risk Management
    • M705: Stressed VaR, Expected Shortfall, and Adv. Measures
    • M706: Basel and FRTB Regulatory Frameworks
    • M707: Model Validation, Backtesting, and Performance Assess
    • Interview Guide: Quant Market Risk Management

  • 08. Credit Risk Management (CRM)

    20,000₹
    Prerequisites: Python Programming, Excel | Duration: ~75 hrs + 5 hrs for [CV Preparation, Profile Optimization] + 10 hrs for [Mock Interviews] | Mode: Live (Instructor-led) and Recorded (Self-Paced)
    Valid for 12 months
    • M801: Introduction to Credit Risk Management
    • M802: CounterParty Credit Risk and Management Strategies
    • M803: Credit Risk Mitigation through Netting and Collateral
    • M804: Credit Risk Mitigation through Credit Derivatives
    • M805: Credit Risk Mitigation and Basel Regulations
    • M806: Advanced Risk Measures and Exposure Calculation
    • M807: Securitization in Credit Risk Management

  • InterviewGuide: Python for Quant Finance

    1,000₹
    This interview guide is designed to prepare finance professionals for technical Python questions asked in roles at investment banks, hedge funds, asset management firms, consulting firms, and fintech.
    Valid for 12 months
    • P101: Python Fundamentals and Data Structures (19 IGQ)
    • P102: Pandas for Financial Data Analysis (25 IGQ)
    • P103: NumPy for Numerical Computing in Finance (21 IGQ)
    • P104: Performance Optimization and Best Practices (14 IGQ)
    • P105: Object-Oriented Pr and Financial Applications (12 IGQ)

  • InterviewGuide: Fixed-Income Investments

    1,000₹
    This interview reference is designed to prepare you for technical discussions on fixed-income valuation roles at investment banks, asset management firms, and other financial institutions.
    Valid for 12 months
    • P401: Fixed-Income Markets and Products (25 IGQ)
    • P402: Fixed-Income Valuation and Risk Analytics (27 IGQ)
    • P403: Interest Rate Risk Measurement and Management (30 IGQ)
    • P404: Fixed-Income Derivatives and Structured Prod (22 IGQ)

  • Quant Finance and Risk Management Pro

    60,000₹
    Prerequisites: Excel | Duration: ~250+ hrs (5 Programs) + 5 hrs for [CV Preparation, Profile Optimization] + 10 hrs for [Mock Interviews] | Mode: Live (Instructor-led) and Recorded (Self-Paced)
    Valid for 24 months
    • M101: Python Fundamentals and Data Structures
    • M102: Control Flow Statements and Exception Handling
    • M103: OOP Concepts for Advanced Programming
    • M104: Data Analytics, Automation, and Multi-Core Processing
    • M105: Python Integrated Mathematics, Statistics, and Finance
    • Interview Guide: Python for Quant Finance Professionals
    • M301: Equity Market Fundamentals and Products
    • M302: Modeling Volatilities and Vol Surfaces
    • M303: Pricing and Valuation of Equity Derivative Instruments
    • M304: Portfolio Performance Measurement and Attribution
    • M305: Portfolio Risk Measurement and Decomposition
    • M401: Fixed-Income Market Fundamentals and Products
    • M402: Modeling Term-Structure of Interest Rates
    • M403: Modeling Rates Using Stochastic Interest Rates Models
    • M404: Pricing and Valuation of Fixed-Income Securities
    • M405: Bond Cashflow Mapping Procedures and Portfolio Risk
    • Interview Guide: Fixed-Income Investments and Risk Manage..
    • M701: Introduction to Market Risk Management Fundamentals
    • M702: Sensitivity Analysis and Hedging Techniques
    • M703: Scenario Analysis and Portfolio Stress Testing
    • M704: VaR Methodologies and Portfolio Risk Management
    • M705: Stressed VaR, Expected Shortfall, and Adv. Measures
    • M706: Basel and FRTB Regulatory Frameworks
    • M707: Model Validation, Backtesting, and Performance Assess
    • Interview Guide: Quant Market Risk Management
    • M801: Introduction to Credit Risk Management
    • M802: CounterParty Credit Risk and Management Strategies
    • M803: Credit Risk Mitigation through Netting and Collateral
    • M804: Credit Risk Mitigation through Credit Derivatives
    • M805: Credit Risk Mitigation and Basel Regulations
    • M806: Advanced Risk Measures and Exposure Calculation
    • M807: Securitization in Credit Risk Management

  • Quant Finance Mentorship Program 1:1

    3,50,000₹
    Prerequisites: Excel | Duration: ~400+ hrs (10 Programs) + 14 Projects + 1:1 Mentorship Sessions + Priority Support | Mode: Live (Instructor-led), Recorded (Self-Paced), and Personalized 1:1 Sessions
    Valid for 24 months
    • M101: Python Fundamentals and Data Structures
    • M102: Control Flow Statements and Exception Handling
    • M103: OOP Concepts for Advanced Programming
    • M104: Data Analytics, Automation, and Multi-Core Processing
    • M105: Python Integrated Mathematics, Statistics, and Finance
    • Interview Guide: Python for Quant Finance Professionals
    • M201: Basic Statistics
    • M202: Probability and Probability Distributions
    • M203: Regression Analysis
    • M204: Linear Algebra
    • M205: Deterministic and Stochastic Calculus (NA)
    • M206: Stochastic Processes and Simulations
    • M207: Time-Value of Money
    • M301: Equity Market Fundamentals and Products
    • M302: Modeling Volatilities and Vol Surfaces
    • M303: Pricing and Valuation of Equity Derivative Instruments
    • M304: Portfolio Performance Measurement and Attribution
    • M305: Portfolio Risk Measurement and Decomposition
    • M401: Fixed-Income Market Fundamentals and Products
    • M402: Modeling Term-Structure of Interest Rates
    • M403: Modeling Rates Using Stochastic Interest Rates Models
    • M404: Pricing and Valuation of Fixed-Income Securities
    • M405: Bond Cashflow Mapping Procedures and Portfolio Risk
    • Interview Guide: Fixed-Income Investments and Risk Manage..
    • M501: Introduction to Portfolio Management
    • M502: Portfolio Construction and Optimization Techniques
    • M503: Performance Evaluation Metrics and Attribution
    • M504: Portfolio Risk Management – Scenario and StressTesting
    • M505: Portfolio Hedging and Rebalancing
    • M601: Introduction to Derivatives Market and Products
    • M602: Pricing and Valuation of Derivative Instruments
    • M603: Option Sensitivities and Hedging Techniques
    • M604: Derivative Strategies - Trading and Risk Management
    • M605: Credit Derivatives and Structured Products
    • M701: Introduction to Market Risk Management Fundamentals
    • M702: Sensitivity Analysis and Hedging Techniques
    • M703: Scenario Analysis and Portfolio Stress Testing
    • M704: VaR Methodologies and Portfolio Risk Management
    • M705: Stressed VaR, Expected Shortfall, and Adv. Measures
    • M706: Basel and FRTB Regulatory Frameworks
    • M707: Model Validation, Backtesting, and Performance Assess
    • Interview Guide: Quant Market Risk Management
    • M801: Introduction to Credit Risk Management
    • M802: CounterParty Credit Risk and Management Strategies
    • M803: Credit Risk Mitigation through Netting and Collateral
    • M804: Credit Risk Mitigation through Credit Derivatives
    • M805: Credit Risk Mitigation and Basel Regulations
    • M806: Advanced Risk Measures and Exposure Calculation
    • M807: Securitization in Credit Risk Management
    • M901: Model Risk Management Foundations and Regulations
    • M902: Model Inventory, Classification, and Tiering
    • M903: Model Development Standards and Best Practices
    • M904: Independent Model Validation Framework
    • M905: Conceptual Soundness Validation
    • M906: Implementation Verification and Testing
    • M907: Ongoing Performance Monitoring and Backtesting
    • M908: Model Limitations, Assumptions, and Compensating Contr
    • M909: Model Change Management and Version Control
    • M910: Validation of Specific Model Types
    • M1001: Introduction and Pre-Machine Learning Essentials
    • M1002: Loss Function and Regularization Techniques
    • M1003: Supervised Learning: Regression Models
    • M1004: Supervised Learning: Classification Models
    • M1005: Unsupervised Learning: Clustering Models
    • M1006: Component Analysis and Dimensionality Reduction Techn
    • M1007: Ensemble Learning - Random Forests and Adaboost
    • M1008: Advanced Boosting Algorithms - Gradient Boosting
    • M1009: Introduction to Deep Neural Network (NA)
    • M1010: Introduction to Natural Language Processing (NA)
    • M1011: Introduction to Transformer Architecture (NA)
    • M1012: Generative AI - Retrieval-Augmented Generation (NA)
    • Unlimited Mock Interviews and Interview Preparation Support
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