Over the past few years, Twitter has rapidly grown into a prominent social media platform, and various research papers have attempted to prove the relationship between the stocks and the tweets made on Twitter. The purpose of this research paper is to investigate the specific connection between Elon Musk's twitter and the stock value of Tesla. The primary form of analysis used was Exploratory Data Analysis to be able to more easily distinguish patterns within our dataset, which was preprocessed to exclude any stopwords. Utilizing various graphs and Machine Learning algorithms such as Logistic Regression and Support Vector Machine, we wrote this research paper that respectively analyzes the change in the close price of Tesla's stock and Elon Musk's Twitter engagement, including tweets, likes, and retweets dating from the start of 2015 up until July of 2020. Furthermore, the article illustrates the contents of Elon Musk's tweets and allows a deeper understanding of other correlations that may exist through the use of Machine Learning to perform Sentiment Analysis. This was achieved by categorizing Elon's tweets into three different tones (positive, negative, and neutral) and seeing how the underlying mood would correspondingly affect Tesla's stock value. The combination of such techniques and factors allowed for a conclusive result in which a distinct correlation was apparent: an increase in the number of tweets/engagement would lead to an increase in the closing price of Tesla, as well as vice versa.