In this post I will discuss the work I completed for the assignments that are part of the "Data Science at Scale specialization" course offered by Coursera and the University of Washington. This is the same as the coursera course "Introduction to Data Science"
In "assignment1", I performed the following: Used Python to access the twitter API, determined the sentiment value (measure of popularity) of tweets. Full details at: https://www.coursera.org/learn/data-manipulation/programming/AxbQn/twitter-sentiment-analysis
In "assignment3", I used the code given in MapReduce.py provided by coursera that implements MapReduce in Python. I then implemented my own MapReduce algorithms to complete the assignments, which included counting the number of friends and determining the asymmetric friendships in an example social network with (person,friend) as key-value pairs. Full details at:https://www.coursera.org/learn/data-manipulation/programming/Dp7qI/thinking-in-mapreduce
The code I used to complete these assignments is in the "assignment1" and "assignment2" folders at the repository located at: https://github.com/jk34/Coursera_DataManipulation_MapReduce
Hello world, my name is Jerry Kim. I have a background in physics and programming and I am interested in a career as a software engineer or data scientist. I created this website to showcase a small sample of the things that I have worked on