Nikhil Kumar Sharma
Final Year, Computer Science Engineering
TwitteR Data Analysis
● Extraction of Data from TwitteR with R.
● Cleaning of extracted Data with R.
● Data Visualization of cleaned data using ggplot2 library in R.
● Creation of wordcloud through the extracted data to check the associations of words with each other.
Unigram and Bigram Analysis
● Scoring tweets on the basis of no. of words in particular tweets matches with negative and positive words text files for Unigram.
● And with positive-negative, negative-negative, positive-positive, negative-positive files for Bigram Analysis.
● Classifying tweets in reaction as Anger, Happy, Sadness, Surprise and Pleasant. And plotting of results using Histogram and Pie Chart. De-Duplication
● Removal of Duplications from the data on the basis of First Name, Last Name, Gender, DOB.
Sentiment Analysis using Text-Mining
● Implementation of TF (Term Frequency) and IDF (Inverse Document Frequency) to provide weightage to words in a statement.
● Scoring of the tweets from the weightage calculated above. EDUCATION
Bachelor of Technology 2 015 - 2019 ( expected )
CGPA : 5.84
The LNM Institute of Information Technology, Jaipur XII - CBSE Board 2 013 - 2014
Percentage : 80 %
Maheshwari Public School, Kota
X - CBSE Board 2 011 - 2012
CGPA : 8.4
R programming, Python, Tableau, SQL,
Java, C, MS Excel
● Intermediate R at DataCamp.
● Intermediate Python for Data
Science at DataCamp.
● Importing Data in R (.csv, .xlsx, .txt
● Cleaning Data in R at DataCamp.
● Exploratory Data Analysis.
● Data Manipulation in R with dplyr.
● Correlation & Regression in R.
● Complete Statistics with R.
● Analysis with Spreadsheet
● SQL for Data Science.
● Probability and Statistical expert at
● β-Tester at D ataCamp
Singing, Playing Cricket,
Cooking for Self
St. Paul’s Sr. Sec. School, Kota