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Georgia Institute of Technology

Machine Learning for Trading

Georgia Institute of Technology via Udacity

Overview

This course introduces students to the real world challenges of implementing machine learning based trading strategies including the algorithmic steps from information gathering to market orders. The focus is on how to apply probabilistic machine learning approaches to trading decisions. We consider statistical approaches like linear regression, KNN and regression trees and how to apply them to actual stock trading situations.

Syllabus

  • Manipulating Financial Data in Python
  • Computational Investing
  • Machine Learning Algorithms for Trading

Taught by

Tucker Balch

Reviews

3.1 rating, based on 14 Class Central reviews

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  • Anonymous
    I enjoyed learning about how machine learning applies to trading strategy, but was very disappointed that mini-courses 2 and 3 included no coding assignments! This, despite the instructors repeated assurances that we'd be building cool things later in the course. I'm feeling a bit swindled, particularly given the pleasant experience I've had with the two previous courses taken at Udacity, which both had lots of coding challenges sprinkled throughout the course. :(
  • Anonymous
    All in all I'm extremely disappointed. The combination of theory and practical coding was great in the first third of the course, and I really learned a lot! But when things were starting to get really interesting, they gave up! No more Python and no more practical examples. All that was left was just tedious examples of extremely basic financial theory. Honestly, I don't undeerstand what they were aiming for here.
  • I don't know why people so complain about no code in session 2 and 3. All I can say about this course is "I want more" I want more knowledge about how machine learning can apply to trading, I want more about Financial more about ML not Python this course is intro us to trading not how to create it's no python code? it would be great if instructor add more code in session 2 and 3 but this is not programming course it's ML for Trading
  • Anonymous
    Implementation of theory using Python is missing in 2nd and 3rd part of the course. It is indeed very frustrating and it doesn't provide a glimpse into how to implement those ideas or even a starting point to develop them further. Students are just left with theoretical concepts and no intuition to implement them. I have to say it was very disappointing from 2nd part onwards.
  • Anonymous
    I started with Python and Pandas in the course , which was very helpful as that had many programming stuff.Then I jumped on to Machine Learning part as I was very interested in that part of the course.But was disappointed after that to see that the ML part includes only Theory with no practicals and coding in python
  • Anonymous
    This is not a bad course at all. The all round basics of finance are covered. This is a basic course, it covers the basics well. For higher level stuff the mathematics becomes more complicated. For example if you wanted a course in quant finance you would need to understand measure theory, probability theory, stochastic calculus and computer science. You cannot learn this simply by learning examples. No MOOC will turn you into the finished product, you will have to eventually burn the midnight oil and read dozens of books.
    Quant finance is hard, if you think its easy you are not studying hard enough.
  • Anonymous
    If you are expecting practical lessons on how to actually use machine learning for trading don't waste your time with this course. Everything is basic or just briefly described. It does not show you how to take the models described and actually put them to use with data to create an algortihm. Extremely disappointing course.
  • Anonymous
    this course was great in the first and second but in the third it's should be intro to machine learning. I just want more detail about ML for Trading. But this course was great overall no coding in part 2 3 no problem they teach in first part you all should be applied it's your selft
  • Anonymous
    Completely useless course, if you want to learn how to apply machine learning to trading. Parts 2 and 3 only give very vague theoretical description of some machine learning methods, without any data or example. Nothing practical here at all. I don't even see the point of wasting time on the theory part, since it is very limited and vaguely explained. Total garbage.
  • Anonymous
    very easy introduction to finance world and basic machine learning . i like the way Dr.Tucker teach very easy to follow
  • Anonymous
    There is a good place to start in financial world (and a basic machine learning) from the people from another field like mine
  • Silveira Homero
  • Rob

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