3 Months Uncool, Comprehensive and Rigorous Deep Learning Course
with focus on mathematics and implementation
Register  https://in.explara.com/e/deeplearning3monthcourse
Reference Books 

Machine Learning  Tom Mitchell

Neural Networks and Learning Machines  Simon Haykin

Deep Learning  Ian Goodfellow et.al

Pattern Recognition and Machine Learning  Bishop
Framework 

PyTorch
Course Aim  Thorough understanding of foundations of Deep Learning.
Prerequisites 

You should have a laptop on which google colab can be run

Good grasp on 12th level mathematics
Fee  Rs 10000 (One time payment), Rs 5000 (monthly for 3 months)
Mode of delivery  Recorded Lectures delivered during the week + Live special sessions on weekends(Only for those who complete assignments).
Refund  full refund after the course starts.
Syllabus 
Module 0  Introduction to Python
Module 1  Necessary Mathematics

Probability Theory

Information Theory

Probability Distributions

Linear Algebra

Matrices

Determinants

Vector Algebra

Module 2  Introduction to Neural Networks 

Universal Approximation Theorem

Introduction to PyTorch

Neural Networks

Backpropagation in detail

Paper Review  Theoretical framework for backpropagation

Implementing Neural Network in python using numpy.

Implementing Simple Neural Network in PyTorch.


Regularisation

Optimisations
Module 3  Convolution Neural Networks
Theory and Implementation
Module 4  Recurrent Neural Networks
Theory and Implementation
Module 5  Advanced Computer Vision Neural Networks