Alzheimer’s disease is a prevalent medical condition that affects the elderly and is a growing cause of concern for society, especially for old people and their families. Alzheimer’s disease is the most relevant type of dementia. This is a progressive disease that starts with light memory loss and can go on to render a person incapable of carrying out even the simplest tasks. To help us carry out an analysis to identify early onset Alzheimer’s disease in a patient, to ensure prompt medical attention, we have decided to study the structural changes in the Alzheimer’s disease induced degeneration of the brain using Topological Data Analysis. By examining the changes in the brain structure using topology, we may investigate changes in connectivity of the brain cells. The areas of the brain responsible for thought, memory, language, decision making, all get affected by onset of Alzheimer’s disease. Using tools like persistent homology, persistent barcodes, and persistent diagrams, we use them to study structural changes in the brain, and see if the method proves to be more accurate than the already existing method for detection of Alzheimer’s disease which is based on Convolutional Neural Networks which consists of running a deep learning model on brain MRI scans and training a model to differ between an Alzheimer’s addled brain and a normal healthy brain.