This course provides a concise introduction to the fundamental concepts in deep learning and popular deep learning algorithms. We will cover the standard and most popular supervised learning algorithms including Linear Algebra For Machine and Deep Learning, ANN, Architecture of ANN, types and applications, Perceptron Method,  Backpropagation method, Tensorflow in details, ANNs With Tensorflow , Keras in details, ANNs With  Keras, Introduction to Convolution Neural Network(CNN) and Recurrent Neural Network(RNN) 

In the course, we will discuss various issues related to the application of deep learning algorithms.  The course will be accompanied by hands-on problem solving with programming and some tutorial sessions.