This course is designed to fulfil the needs of a modern day Quant professional. It takes you through a systematic journey of financial engineering concepts starting with the famous Black scholes model all the way to using artificial intelligence for valuation and risk modelling. The foundation of the course rests on three legs: mastering the martingale and numeraire based approach to derivative pricing (with tree or monte carlo simulation), mastering the PDE journey to pricing (involving finite difference schemes), and quantitative portfolio management (using statistical models to build portfolios). The course covers these topics in a structured manner with increasing difficulty, visuals, practice problems, and building python routines from scratch. It also covers the use of Machine learning as an overlay to traditional models in finance. The hallmark of this course is a structured learning roadmap, reusable artifacts (spreadsheets and python routines), and empowerment to be an independent and complete Quant professional.
Every Sunday Live Session
6:00 PM - 8:00 PM IST
2 hours per intensive session
Regular live classes on topics not covered in self-paced sessions.
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Includes 175 hours of self-paced and live learning with excel + python labs, D forum, quizzes, python codes, primers & more
Systematic journey from Black-Scholes to AI in valuation and risk modelling.
Martingale and numeraire based derivative pricing, PDE approach to pricing, and quantitative portfolio management.
Build python routines from scratch in a reusable and scalable fashion.
Covers the use of Machine learning as an overlay to traditional models in finance.
Structured learning roadmap with visuals, practice problems, and reusable artifacts (spreadsheets, python routines).
Taught by an experienced professional with extensive experience in Capital Markets and Risk.
Setting up Python Infrastructure
Arithmetic operations
Data Structure
Object Oriented Programming
Numerical computing with NumPy
Data Analysis with Pandas
Data Visualization with Matplotlib, Seaborn & Cufflinks
Calculus
Numerical Integration
Probability & Statistics with SciPy
Univariate Financial Time Series Analysis with Statsmodels
Multivariate Financial Time Series Analysis by Statsmodels
Conditional Volatility Models
Monte Carlo Methods
Copula Models
Stochastic process
Change of Measure
Binomial Asset Pricing Model
Jump Process
Finite Difference Methods for Option pricing
Black Scholes
Monte Carlo methods for Option pricing
Volatility Surface
Rates and Rate Instruments
Term Structure Models
Options on rates
FX Instruments
Portfolio Theory & Optimization
FX Instruments
Traditional Unsupervised algorithms using Scikit Learn
Deep Learning with Tensorflow
Secure your spot in our upcoming batch (Batch - 2025 Cohort). Fill out the form and our team will contact you with enrollment details.
Every Sunday Live Session
2 hours per session
6:00 PM - 8:00 PM IST
Recordings are also available for self paced learning
A Step-by-Step Path with the Deep Quant Finance Course, designed to make you an independent and complete Quant professional.
Build a strong foundation covering Python, data analysis, numerical methods, statistics, and time series analysis (Module 1).
Build a strong foundation covering Python, data analysis, numerical methods, statistics, and time series analysis (Module 1).
Understand stochastic processes, Ito's Calculus, and Change of Measure crucial for financial modeling (Module 2).
Understand stochastic processes, Ito's Calculus, and Change of Measure crucial for financial modeling (Module 2).
Explore Equity Derivatives, Interest Rate & FX Derivatives, and Quantitative Portfolio Management techniques (Modules 3, 4, 5).
Explore Equity Derivatives, Interest Rate & FX Derivatives, and Quantitative Portfolio Management techniques (Modules 3, 4, 5).
Learn to use traditional ML algorithms and Deep Learning with Tensorflow in finance (Module 6). Obtain your certificate upon successful completion of assignments and exams[cite: 46].
Learn to use traditional ML algorithms and Deep Learning with Tensorflow in finance (Module 6). Obtain your certificate upon successful completion of assignments and exams[cite: 46].
Build a strong foundation covering Python, data analysis, numerical methods, statistics, and time series analysis (Module 1).
Build a strong foundation covering Python, data analysis, numerical methods, statistics, and time series analysis (Module 1).
Understand stochastic processes, Ito's Calculus, and Change of Measure crucial for financial modeling (Module 2).
Understand stochastic processes, Ito's Calculus, and Change of Measure crucial for financial modeling (Module 2).
Explore Equity Derivatives, Interest Rate & FX Derivatives, and Quantitative Portfolio Management techniques (Modules 3, 4, 5).
Explore Equity Derivatives, Interest Rate & FX Derivatives, and Quantitative Portfolio Management techniques (Modules 3, 4, 5).
Learn to use traditional ML algorithms and Deep Learning with Tensorflow in finance (Module 6). Obtain your certificate upon successful completion of assignments and exams[cite: 46].
Learn to use traditional ML algorithms and Deep Learning with Tensorflow in finance (Module 6). Obtain your certificate upon successful completion of assignments and exams[cite: 46].
Certificate of Completion
This certificate is proudly presented to
For successfully completing the course“Deep Quant Finance (DQF) Certificate”by Risk Inn.
Satyapriya Ojha
Chief Faculty
January 6, 2026
Date Issued
Founder & CEO, IIT, Tulane, USA
Ripul is the Founder of Risk Inn and has an academic background from the Indian Institute of Technology (IIT) Roorkee and Tulane University, USA, with over 150 research citations. He has extensive experience in management, business, research, and consulting, with a career spanning India, the USA, and Europe. He is passionate about teamwork and empowering individuals to maximize their talents, drive growth, and foster innovation at Risk Inn.
The future of risk management lies in the intelligent application of data.
FRM, CQF (Distinction), IIT Kharagpur, Market Risk Upskilling Expert
Satyapriya Ojha is a highly skilled Capital Markets and Risk professional with 12+ years of experience in Regulatory Capital, Valuation and Analytics. He is an IIT & IIM graduate and holds FRM charter (top quartile in all subjects of part I & part II) and a distinction from CQF institute. He is an expert in quantitative models used in valuation and risk management. He has worked as a consultant in several regulatory projects for some of the top banks in the US in BASEL III and FRTB space. Currently, he serves as a product owner for a top wealth management firm engaged in quantitative portfolio management for institutional clients.
The future of risk management lies in the intelligent application of data.
Mentor, Risk Management Upskilling Award Winner
Karan Aggarwal is one of India’s leading trainers in Financial Modelling, Risk Modelling, Data Analytics, Actuarial Science. He has spearheaded several solution accelerators and spreadsheet-based prototypes in Risk and Analytics space. Karan has also authored a number of papers on Basel Modelling, IFRS 9 Modelling, Stress Testing & Machine Learning. He is widely regarded for his problem solving, thought leadership and intrapreneurship skills. His analytical mindset, solid fundamentals & the thirst to keep learning set him apart as a true authority in this field. Karan has also been awarded the Young Indian Entrepreneur Award by the Confederation Of Indian Industries in the year 2017.
The future of risk management lies in the intelligent application of data.