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Guided Tour of Machine Learning in Finance, New York University Tandon School of Engineering

3.6
243 ratings
90 reviews

About this Course

This course aims at providing an introductory and broad overview of the field of ML with the focus on applications on Finance. Supervised Machine Learning methods are used in the capstone project to predict bank closures. Simultaneously, while this course can be taken as a separate course, it serves as a preview of topics that are covered in more details in subsequent modules of the specialization Machine Learning and Reinforcement Learning in Finance. The goal of Guided Tour of Machine Learning in Finance is to get a sense of what Machine Learning is, what it is for and in how many different financial problems it can be applied to. The course is designed for three categories of students: Practitioners working at financial institutions such as banks, asset management firms or hedge funds Individuals interested in applications of ML for personal day trading Current full-time students pursuing a degree in Finance, Statistics, Computer Science, Mathematics, Physics, Engineering or other related disciplines who want to learn about practical applications of ML in Finance Experience with Python (including numpy, pandas, and IPython/Jupyter notebooks), linear algebra, basic probability theory and basic calculus is necessary to complete assignments in this course....

Top reviews

By AB

May 28, 2018

Exceptional disposition and lucid explanations! Ideal for a Risk Management professional to sharpen machine learning skills!

By LB

Aug 19, 2018

Audio could be better. Low recording volume makes it difficult to listen sometimes.

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78 Reviews

By Dawid Laszuk

Jan 27, 2019

Terrible. For the first time in long time I felt such abandoned. No support. Notebooks written sloppy with plenty of copy-paste and no fixing. Thought more of the lecturer as well but videos feel like he's just coming up with the material. Having strong mathematical background I felt that the lecturer is intentionally making simple things sound hard. I'm left with deep sense of wasted time. Leaving Coursera and never coming back.

By Takayuki Kaisen

Jan 18, 2019

One of assignments was hard. Explanation by lecturer was very easy to understand and appropriate long.

By Juan Andrés Serur

Jan 18, 2019

This course is a perfect introduction to machine learning applied to finance, which covers the essentialtopics that students must know to deepen their knowledge in this fascinating field.

By Walter O. Augenstein

Jan 05, 2019

I learned much and got good practice in Python and Tensorflow as well as good exposure to the literature. I was able to download the course materials from the course system and work out homework on my own system for which I was pleased. The automatic grading system worked without incident once I figured it out and did not crash on me. On the other hand, some of the homeworks were less than fully explained and/or motivated by the course material and did contain errors and omissions in the supplied code that I had to track down in order to get them correct. The feedback from the grader was of no use beyond stating whether the answer was correct, but this is pretty standard. The course was frustrating at times and I would recommend it only for students who are highly motivated, but for those who are, it is definitely worth the effort.

By Yergali Berdibayev

Jan 04, 2019

Thank you, for this very useful course!

By Mihails Sinickis

Jan 01, 2019

Despite all the problems with the assignments and the grader this course provides really good overview ML tools and their application to finance. It's definitely worth the effort

By Hashim Mazhar

Dec 29, 2018

A much needed course by a very seasoned expert in the field, bringing the right blend of backgrounds in finance and tech. The course is well designed for finance professionals with some coding background and for technology professionals with some finance background - which is unique in that sense. Some bridging between lectures and assignments is needed but that kind of fine tuning is inevitable and as more students enroll, the discussion rooms and feedback will provide that sharpening at the edges organically. All in all, I enjoyed the course a lot and look forward to the next three in the specialization!

By Vicente Izquierdo

Dec 20, 2018

It lacks information on how to proceed on NN coding.

By Vitalii Antoniuk

Dec 10, 2018

Not very related to finance plus most of the tasks are easy to complete, but hard to understand what needs to be done.

By Pedro Manuel Herrero Vidal

Dec 06, 2018

Potentially great course with bridges technology (machine learning methods) and application (finance), but as for now it is really rough around the edges. Still needs to improve in terms of video lectures, resources and assignments; but once polished it could be a great course/specialization.