The average trading volume in the NYSE( New york stock exchange) is between 2 and 6 billion shares worth about five(5) trillion dollars. Within all that movement and business dealings lies a lot of investment opportunities. Finding the right stock to buy at the right time can lead to a great deal of profit. Moreover harnessing the tools in order to predict and determine these business opportunities is even worth more. Predicting how the stock market will perform is no easy task. There are so many factors involved in this prediction, physical, psychological and alot more. These factors combine to make share prices volatile and hence very difficult to predict with a high degree of accuracy. Over at SkyNet, we committed to innovation. Our proposal is to leverage our knowledge in machine learning to create a tool to predict stock prices with a high degree of accuracy. Using Tesla (TSLA) as our test case, wes shall build a pipeline to get daily information alongside tracking the stock prices, combine that into a model or serval that can forecast the stock price a week in advance. Utilizing ML algorithms; Natural Language Processing (NLP) and time series modeling, we shall create this investment tool should you accept our proposal.