• C++ Programming for Financial Engineering
    Highly recommended by thousands of MFE students. Covers essential C++ topics with applications to financial engineering. Learn more Join!
    Python for Finance with Intro to Data Science
    Gain practical understanding of Python to read, understand, and write professional Python code for your first day on the job. Learn more Join!
    An Intuition-Based Options Primer for FE
    Ideal for entry level positions interviews and graduate studies, specializing in options trading arbitrage and options valuation models. Learn more Join!

Course selection, Machinelearning vs Big Data

Aber

Joined
8/7/15
Messages
91
Points
18
Hi. For my next semester I am considering a big data course or a machinelearning course.
Which course is better than the other for a guy who wants to be a quant?
I am a graduate math finance student. Quant jobs is interest me but I haven't really thought about which areas etc to work.
 
... I know big data is good to know when working in finance. But what about machine learning?
 
These sound like almost the same course. Can you provide more specific information (e.g. from the syllabus) of each course?
 
ibpkpnu said:
These sound like almost the same course. Can you provide more specific information (e.g. from the syllabus) of each course?
Click to expand...
I haven't selected any specific course. I am still waiting to get information about where I will be next year (I have applied exchange for several schools and I don't know where I will be accepted)
I was just wondering how the tools used in those areas could fit in a quant profile in general :)
 
Strictly speaking, big data is a very special use case: the data that you cannot put on your (conventional) HDD, i.e [currently] >10 Tb can be considered as big.

Hadoop takes care about storing you big data in cluster, consiting of (conventinal) hardware notes, IMO for a Data Analyst it is not a must to understand how HDFS technicall works.

What is, however, a must is to understand the MapReduce.
To put it simply: we need to count a number of books in the library, I count the on even shelves, you count on the odd shelves. Finally, we add our partial sums.

So essentially, HDFS + MapReduce = Big Data.
But to make use of them you need machine learning algos, and namely those, that can be reduced to MapReduce.
 
Back
Top