The practice of investment management has been transformed in recent years by computational methods. 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. In this course, we cover the estimation, of risk and return parameters for meaningful portfolio decisions, and also introduce a variety of state-of-the-art portfolio construction techniques that have proven popular in investment management and portfolio construction due to their enhanced robustness.
- 5 stars81.85%
- 4 stars13.15%
- 3 stars3.85%
- 2 stars0.68%
- 1 star0.45%
来自ADVANCED PORTFOLIO CONSTRUCTION AND ANALYSIS WITH PYTHON的热门评论
The course is excellent, one of the best finance courses on coursera, but you should know in advance that you will not have any help from the staff, at least that was my experience.
Really a great course, instructors video then are a great resource. I'd have liked more mathematical analysis but I understand it could have gone beyond scope.
Very interesting course with a lot practice stuff. A very proficient mentors with strong theoretical background in finance and good Python skills.
Sometimes the material covering the python code is insufficient. Maybe provide additional learning resources just for the python portion.
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.