#### Overview

### About the course

“Quantum Computing for Finance” is an emerging multidisciplinary field of quantum physics, finance, mathematics, and computer science, in which quantum computations are applied to solve complex problems.

“Introduction to Quantitative and Computational Finance” provides a basis to step into the world of Quantum Computing for Finance. This introductory course will develop fundamental concepts required for an understanding of quantum algorithms and more advanced topics in computational finance. Through this course, you will learn the basics of derivative products, the Black-Scholes-Merton model for pricing vanilla derivatives, and how to compute the price of exotic options with a computer. This course is designed for all those who wish to develop their skills and start a career in quantitative finance.

This course is the first part of the specialised training program: “Quantum Computing for Finance”.

**What Skills you will learn**

- The fundamentals of derivative products, their types – forwards and options, and their pricing.
- An understanding of the Black-Scholes-Merton model, hedging and volatility modelling.
- The computational and modelling techniques for pricing options such as Monte-Carlo simulations and the Finite Difference method.
- A strong foundation in quantitative and computational skills for modelling and solving complex financial problems using Python programming language.
- The skills for a career in the finance industry, including quantitative asset management and trading, financial engineering, risk management, and applied research.

### Course Prerequisites

All potential learners should have prior knowledge of the following content areas, either through completion of academic studies or relative professional preparation:

- Basic calculus (partial derivatives)
- Probability theory (with an exposure to measure theory if possible)
- Basic linear algebra (matrix operations)
- Numerical Python (NumPy essentially)

The course contains several Python based programming exercises. We recommend that you install Python on your local system to practice and implement the programs explained throughout the course. For instructions and tutorials for beginners, please click on the following link:

Python installation instructions and tutorials for beginners

### Duration

The estimated duration to complete this course is approximately 4 weeks (~3hrs/week).

### Course assessment

To complete the course and earn certification, you must pass all the quizzes at the end of each lesson by scoring 80% or more.