Mostakim, MoinNoor, JannatunDas, KaushikAzad, TahzibIslam, SadidChowdhury, NuzhatAhmed, Nazia2023-12-062023-12-0620232023-05ID 19101600ID 19101464ID 19101296ID 19101262ID 19101227http://hdl.handle.net/10361/21928Cataloged from PDF version of thesis.Includes bibliographical references (pages 43-45).This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2023.Accurately predicting the stock value enables investors to earn more money, reducing their uncertainty on whether to buy and sell. Again during the COVID-19 period, many companies have shown a different picture of the stock market situation. That is why investors cannot consider the company’s exact status in the stock market. The primary objective of our paper is to predict the future behavior of the stock market in the event of a pandemic using machine learning classification. To consider the future stock market condition, first, we looked at the past stock market condition and tried to make predictions by collecting data from two companies. Second, we tried to understand what happened in the stock market during the pandemic and used machine learning algorithms. Finally, make predictions through machine learning classifications by merging the data during the pandemic with past data. In conclusion, we have attempted to identify what was lacking in our instance and provide a concise description of the next steps.45 pagesenBrac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.Stock marketPredictionData miningCovid-19Machine learningDatabase managementThesis