About the course
The most common question we get from beginners in the field of Deep Learning is  Where to begin? The journey to becoming a Deep Learning expert can be difficult if one does not have the right resources to follow. There are a million resources to refer and it is tough to decide where to start from.
We are here to help you take your first steps into the world of Deep Learning. Here is a free learning path for people who want to become a Deep Learning expert in 2019. We have arranged the best resources in a logical manner along with exercises to make sure that you only need to follow one single source to become a data scientist.
Why take this course?
The course is ideal for beginners in the field of Deep Learning. Several features which make it exciting are:
Beginner friendly course
The course assumes no prerequisites and is meant for beginners
Curated list of resources to follow
All the necessary topics are covered in the course, in an orderly manner with links to relevant resources and hackathons.
Prerequisites
This is a beginner friendly course and has no prerequisites.
Course curriculum

1
January 2019
 Getting Started
 Overview of the Learning Path
 Month on Month plan
 Introduction to Deep Learning
 Applications of Deep Learning
 Setting up your System
 Descriptive Statistics and Probability
 Python
 Exercise : Python

2
February 2019
 Start engaging in data science / deep learning communities
 Inferential Statistics
 Exercise : Statistics
 Partial Derivative
 Linear Algebra  Part 1
 Linear Regression
 Logistic Regression
 Exercise : Linear and Logistic Regression
 Regularization Techniques (Ridge and Lasso)
 Project

3
March 2019
 Start building your GitHub profile
 Start building your GitHub profile
 Linear Algebra  Part 2
 Getting Started with Neural Networks
 Understanding Forward Propagation
 Understanding Back Propagation
 Exercise : Understanding Neural Networks
 Build your first Neural Network in Numpy
 Frameworks for Deep Learning
 Introduction to Keras
 Build your first Neural Network in Keras
 Project

4
April 2019
 Start Participating in Competitions
 Handling / Preprocessing Images
 Exercise
 Hyperparameter Tuning
 Regularization Techniques
 Optimization Algorithms
 Exercise
 Transfer Learning
 Data Augmentation
 Project

5
May 2019
 Understanding Convolutional Neural Networks (CNNs)
 Exercise : CNNs
 Hyperparameter Tuning
 Transfer Learning
 Project

6
June 2019
 Build your resume and apply for Internships
 Visualizing Convolutional Neural Networks
 Visualizing Convolutional Neural Networks
 Visualizing Convolutional Neural Networks
 Project 3 on CV
 Project 4 on CV

7
July 2019
 Start writing articles
 Handling / Preprocessing Text Data
 Exercise
 Recurrent Neural Networks (RNNs)
 RNNs  Video
 LSTM
 GRUs
 Project 1 on NLP

8
August 2019
 Word Embeddings
 Exercise
 Project 2 on NLP

9
September 2019
 Attention Models
 Attention Models  Text
 Project on Attention Models

10
October 2019
 Unsupervised Deep Learning
 Project on Unsupervised Deep Learning

11
November 2019
 GANs : Video
 GANs
 Project o