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.
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來自INTRODUCTION TO PORTFOLIO CONSTRUCTION AND ANALYSIS WITH PYTHON的熱門評論
I am self taught in Python and have an industry background in Finance. This course was a good connector/provided additional insight on using Python to process portfolio performance and data analysis.
Awesome Course, Great instructors that give a nice balance of theory and practice, the practice is very hands-on and will help you understand the theory and give you useful tools from the first week.
Enjoyable course. One has to be conversant with basic Phyton to follow this course. What I learnt the most is the ability to use Phyton coding to demonstrate the concept of portfolio investment.
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!
關於 Investment Management with Python and Machine Learning 專項課程
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.