With the emergence of deep learning techniques, in particular, Convolution Neural Networks (CNN), all the state of the art machine learning techniques in the field of computer vision were put aside. Though deep learning is nowadays being widely used in many applications for analysing text data, voice data, data from sensors, it has found major advances in analysing image data with convolution neural networks. This thesis analyses the implementation of CNN in recognizing handwritten Tamil characters in offline mode. CNNs differ from traditional approach of Handwritten Tamil Character Recognition (HTCR) in extracting the features automatically. A CNN model is developed from scratch by training the model with the Tamil characters dataset developed by HP Labs, India in offline mode and have achieved good recognition results on both the training and testing datasets. This work is an attempt to set a benchmark for offline HTCR using deep learning techniques.