Quantitative Risk Management in Python
Course Report
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Course Features
Duration
4 hours
Delivery Method
Online
Available on
Limited Access
Accessibility
Mobile, Desktop, Laptop
Language
English
Subtitles
English
Level
Intermediate
Teaching Type
Self Paced
Video Content
4 hours
Course Description
Highlights
Pedagogy
Top 20 Percentile
Rating & Reviews
Top 30 Percentile
Parameters
Pedagogy
Acquire all major Python Programming for Data Science skills in this course for seamless integration into your daily life. Develop a versatile skill set, allowing you to confidently apply what you've learned in various practical scenarios, enhancing your daily experiences and overall proficiency. An exceptional course in Python Programming for Data Science, this stands out for its Self Paced learning approach. Learners have the flexibility to progress at their own speed, tailoring the experience to their individual needs.
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Rating & Reviews
This highly acclaimed course is among the top-rated in Python Programming for Data Science, boasting a rating greater than 4 and an overall rating of 5.0. Its exceptional quality sets it apart, making it an excellent choice for individuals seeking top-notch learning experience in Python Programming for Data Science.
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Course Overview
Virtual Labs
International Faculty
Post Course Interactions
Hands-On Training,Instructor-Moderated Discussions
Skills You Will Gain
Prerequisites/Requirements
Introduction to Portfolio Analysis in Python
What You Will Learn
Learn about risk management, value at risk and more applied to the 2008 financial crisis using Python
You’ll learn how to use Python to calculate and mitigate risk exposure using the Value at Risk and Conditional Value at Risk measures, estimate risk with techniques like Monte Carlo simulation, and use cutting-edge technologies such as neural networks to
You’ll also learn how to mitigate risk exposure using the Black-Scholes model to hedge an options portfolio
You’ll also discover how neural networks can be implemented to approximate loss distributions and conduct real-time portfolio optimization
Course Instructors
Course Reviews
Average Rating Based on 3 reviews
100%