Introduction to Neural Networks and Deep Learning

4.54
learner icon
59.3K+ Learners
intermediate
Intermediate

Expand your knowledge and skills in Neural Networks and Deep Learning with this online free course. Build and train deep neural networks for industry-related problems using key calculations that underlie deep learning tasks.

What you learn in Introduction to Neural Networks and Deep Learning ?

tick
CNN
tick
ANN
tick
RNN
tick
Tensorflow
tick
Deep Learning Algorithms

About this Course

This free Neural Networks and Deep Learning course gives valuable insights into deep learning applications in various fields and a better understanding of the different frameworks used in neural network applications. You will discover and understand various deep learning concepts and get familiarized with Artificial Neural Network topics. You will also be walked through a few fundamental concepts covering things like the history of the subject and the need to learn it. Further, you will study CNN, RNN, and LSTM and compare types of chatbots and conventional interfaces, Machine learning, and Deep Learning. Earn a free certificate for this course after completing the assigned quiz.

 

Begin your learning journey in this leading domain of Neural Networks and Deep Learning by registering for the Machine Learning courses with millions of aspirants across the globe after you have learned from this self-paced intermediate-level guide!

Course Outline

What is Deep Learning?

This module introduces you to the term “Deep Learning”, and you will go through its definition and an example to get an overview. 

Where does DL Fit?

This module explains the Deep Learning cascade and its hierarchy with Machine Learning and Artificial Intelligence. 
 

Where to use DL?

This module explains the widespread applications of Deep Learning in the Finance, Healthcare, Social Media, and Automation industry. 
 

Brief History

This module articulates Deep Learning and discusses its history since the technology emerged. 

 

ML vs. DL

Deep Learning is the subset of Machine Learning, and through this module, you will understand the fine line between Machine Learning and Deep Learning. In order to help you understand it better, you will go through a car classification example.
 

Artificial Neural Network

This module will help you understand artificial neural network better with the help of the diagram of the Bias Layer. You will learn about a fully connected artificial neural network and the layers involved in it and go through the mathematical foundations for artificial neural networks. 
 

 

Tensorflow Playground Demo

In order to enhance your understanding of the mechanism of Deep Learning or a neural net model, this module puts forth a TensorFlow Playground demo.

 

Deep Learning Fundamentals

This module will walk you through Deep Learning concepts like artificial neural networks, activation functions, back propagation, and feed forward nets.
 

 

Basic Set of Layers

This module will let you comprehend the role of the basic set of layers in Deep Learning. You will go through Dense Layer, Dropout Layer, Convolution 1D, Convolution 2D, MaxPooling 1D, and LSTM in detail.
 

Activation Function

This module digs deeper into the activation function and elaborates on linear and non-linear methods of using activation functions.
 

 

Demo Part -1

This module explains Deep Learning with Keras demonstration to help you understand working with industry-oriented problems. 

 

CNN

This module first briefs CNN's history and then continues with explaining its features. It then explains the structure of CNN and defines its terms. 

 

RNN & LSTM

This module starts by introducing you to Recurrent Networks. You will learn about feed forward networks and recurrency. You will also go through RNN and LSTM diagrammatic representation with a thorough explanation. Lastly, you will comprehend long short-term memory.
 

 

Types of Chatbots & Conventional Interface

This module brings different types of chatbots to your knowledge with sample case studies and discusses conventional interface concept. 

 

Demo Part-2

This module demonstrates CNN and LSTM with Keras and Tensorflow to help you understand working with industry-oriented applications. 

 

Our course instructor

Sunil Kumar Vuppala

Director-Data Science

learner icon
59.3K+ Learners
video icon
1 Courses

What our learners say about the course

Find out how our platform helped our learners to upskill in their career.

4.54
Course Rating
69%
25%
4%
1%
1%

Introduction to Neural Networks and Deep Learning

With this course, you get

clock icon

Multi device access

Learn anytime, anywhere

medal icon

Completion Certificate

Stand out to your professional network

medal icon

2.5 Hours

of self-paced video lectures

share icon

Share with friends

Other Artificial Intelligence tutorials for you