The practice of investment management has been transformed in recent years by computational methods. This course provides an introduction to the underlying science, with the aim of giving you a thorough understanding of that scientific basis. However, instead of merely explaining the science, we help you build on that foundation in a practical manner, with an emphasis on the hands-on implementation of those ideas in the Python programming language.
- 5 stars85.33%
- 4 stars12.72%
- 3 stars1.13%
- 2 stars0.40%
- 1 star0.40%
来自INTRODUCTION TO PORTFOLIO CONSTRUCTION AND ANALYSIS WITH PYTHON的热门评论
Exceptional quality of instruction. The production and detail of supporting materials made this class very accessible. I learned much more than expected. Bravo on the effort of the instructors!
A well-balanced course between theory, applications and coding. If you are an intermediate finance student that is looking for a practical toolkit with python, this is the right course
Perfect Course to get started with the basics of Portfolio Construction. The python code with the guided lab sessions becomes easy and quick to grasp and the instructors are awesome!!
Well taught and really like the mix between practical and theoretical lectures. Explain in simple language and starts off simple but gets progressively harder. Highly recommended.
关于 Investment Management with Python and Machine Learning 专项课程
The Data Science and Machine Learning for Asset Management Specialization has been designed to deliver a broad and comprehensive introduction to modern methods in Investment Management, with a particular emphasis on the use of data science and machine learning techniques to improve investment decisions.By the end of this specialization, you will have acquired the tools required for making sound investment decisions, with an emphasis not only on the foundational theory and underlying concepts, but also on practical applications and implementation. Instead of merely explaining the science, we help you build on that foundation in a practical manner, with an emphasis on the hands-on implementation of those ideas in the Python programming language through a series of dedicated lab sessions.