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Mathematical Finance with Python : Theory and Practice

A Holistic Course to Learn Financial Modelling , Mathematics for Finance and Machine Learning
4.8
4.8/5
(2 reviews)
27 students
Created by

9.8

CourseMarks Score®

10.0

Freshness

9.0

Feedback

9.8

Content

Platform: Udemy
Video: 12h 34m
Language: English
Next start: On Demand

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Detailed Analysis

CourseMarks Score®

9.8 / 10

CourseMarks Score® helps students to find the best classes. We aggregate 18 factors, including freshness, student feedback and content diversity.

Freshness Score

10.0 / 10
This course was last updated on 4/2022.

Course content can become outdated quite quickly. After analysing 71,530 courses, we found that the highest rated courses are updated every year. If a course has not been updated for more than 2 years, you should carefully evaluate the course before enrolling.

Student Feedback

9.0 / 10
We analyzed factors such as the rating (4.8/5) and the ratio between the number of reviews and the number of students, which is a great signal of student commitment.

New courses are hard to evaluate because there are no or just a few student ratings, but Student Feedback Score helps you find great courses even with fewer reviews.

Content Score

9.8 / 10
Video Score: 9.5 / 10
The course includes 12h 34m video content. Courses with more videos usually have a higher average rating. We have found that the sweet spot is 16 hours of video, which is long enough to teach a topic comprehensively, but not overwhelming. Courses over 16 hours of video gets the maximum score.
Detail Score: 9.9 / 10

The top online course contains a detailed description of the course, what you will learn and also a detailed description about the instructor.

Extra Content Score: 9.9 / 10

Tests, exercises, articles and other resources help students to better understand and deepen their understanding of the topic.

This course contains:

3 articles.
3 resources.
0 exercise.
0 test.

Table of contents

Description

This course combines the right mix of programming concepts with Python, Mathematical Modelling, Quantitative Finance and Machine Learning. This course is divided into four parts.
Part one covers the essentials of python programming. This includes basic printing, data types, branching and iteration. This part also covers key topics like tuples, mutability, functions, recursion, classes and concepts of  object oriented programming. This part culminates with a capstone project, wherein we would build a financial model to calculate mortgage payments.
Part two covers python and mathematics for finance. This part entails two capstone projects which would cover detailed modelling of options using the Black-Scholes Model and detailed modelling of valuation of bond instruments. This part clearly explain all the basic math concepts required for finance in a theoretical (white board fashion) and each concept session is followed by a hands-on lab session in python. The topics covered are exponential functions, logarithmic functions, Log-normal functions. There is also a special bonus session on modelling of options Greeks
Part three covers stochastic modelling for finance. This part is key for quantitative finance and we give a solid foundational understanding of the key concepts of stochastic finance. There is an exclusive and exhaustive coverage of Monte Carlo simulation techniques for Finance and its application by means of estimation of stock price and options price. Other topics covered are Random Walk Modelling, Geometric Brownian process simulation, Calculation of Pi using Monte Carlo Simulation.
Part four covers machine learning for finance . In this part , students would learn technical analysis of stocks with candlestick and  OHLC charts, prediction of stock prices using advanced machine learning algorithms and real time market research.
This course covers mathematics of finance in detail. The USP of the course is that each concept is explained in a theoretical fashion (using a digital white board) and is immediately followed by a hands-on lab session. This powerful combination would ensure that the students learn the concepts very well.
Important concepts of python programming , mathematics and finance are explained in a way with which the student would have absolute clarity. Hard core coding in Python is involved,  wherein the mathematical models are designed using user defined custom functions and not consumed from standard libraries. The student gets to learn the nuts and bolts of model creation in python.

You will learn

✓ Essentials of Python Programming : Printing, Data Types, Branching, Loops, Advanced Data Structures, Functions, Recursion, Classes & Object oriented programming
✓ Python for Finance : Statistics, Detailed modelling of Options using the Black-Scholes Model, Bond Valuation, Mathematical functions for finance(exp,log-normal)
✓ Stochastic Finance : Random Walk Modelling, Monte-Carlo simulation for finance (Estimation of stock and options price), Brownian process , Histogram generation.
✓ Machine Learning for Finance : Technical Analysis with Candlestick OHLC and other charts, Prediction of stock prices using advanced machine learning algorithms.
✓ Detailed Mathematical Modelling of Black-Scholes Equation with Python. Comparison techniques for different BS Options pricing models with respect to impact
✓ Special techniques for testing and debugging codes. Conceptual understanding of testing and debugging coupled with live debugging sessions in the virtual lab
✓ Building mathematical models for financial instruments using custom functions & classes. Converting mathematical expressions into concise pieces of python code
✓ Clear understanding of essential mathematical concepts required for financial modelling ( writing a mathematical expression in python language using functions)
✓ Theoretical understanding of programming concepts and Hands-on python lab for each concept to apply the theoretical learning immediately in coding environment
✓ Key model building techniques for Finance like Black-Scholes Options Pricing, Monte Carlo Simulation for Finance, Stock prediction using Machine Learning etc.,

Requirements

• No programming experience needed.
• No prior knowledge on mathematics / statistics needed.
• All you need is a computer with internet connection and loads of enthusiasm to learn.

This course is for

• Working Professionals who would want to upskill themselves, in order to meet the demands of the changing business landscape.
• University students from any background, who would want to strengthen their profile with job ready skills
• Academic professionals and Research scholars, who would want to add a new set of skills in their arsenal.

How much does the Mathematical Finance with Python : Theory and Practice course cost? Is it worth it?

The course costs $14.99. And currently there is a 25% discount on the original price of the course, which was $59. So you save $44 if you enroll the course now.

Does the Mathematical Finance with Python : Theory and Practice course have a money back guarantee or refund policy?

YES, Mathematical Finance with Python : Theory and Practice has a 30-day money back guarantee. The 30-day refund policy is designed to allow students to study without risk.

Are there any SCHOLARSHIPS for this course?

Currently we could not find a scholarship for the Mathematical Finance with Python : Theory and Practice course, but there is a $44 discount from the original price ($59). So the current price is just $14.99.

Who is the instructor? Is Institute of Mathematical Thinking a SCAM or a TRUSTED instructor?

Institute of Mathematical Thinking has created 1 courses that got 2 reviews which are generally positive. Institute of Mathematical Thinking has taught 27 students and received a 4.8 average review out of 2 reviews. Depending on the information available, Institute of Mathematical Thinking is a TRUSTED instructor.
Academy for Mastering Data Science and Financial Modelling
We are an academy committed to instill new-age technical skills to students and working professionals by means of offering unique state-of-the art courses on data science, machine learning, quantitative finance and financial modelling. The unique selling proposition of our courses are that each concept is covered by means of a combination of theory and lab. The underlying math of complex subjects like machine learning and quantitative modelling, would be explained in a simple and lucid way (over a digital white board). These theory session would be immediately followed by hands-on programming session (with Python / R). This proven method would ensure that the students would take away the contents of the course, with high levels of clarity and confidence. We have conducted many live and virtual sessions to students and working professionals. This is our foray into online training

9.8

CourseMarks Score®

10.0

Freshness

9.0

Feedback

9.8

Content

Platform: Udemy
Video: 12h 34m
Language: English
Next start: On Demand

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