# Introduction to Artificial Neural Networks

Learn about the Artificial Neural Networks, the backbone of Artificial Intelligence in a Self Paced Certificate Course. Both Simple and Polynomial Neural Networks were covered with Self Explanatory Presentations along with example problems. On securing pass marks in the Weekly Assignments and End of the Month Tests, Certificate of Completion is provided. Scope of publication will also be granted at the end of the course and on securing pass mark in the assignment and tests.

### Course Content :

1)Introduction

2)Classification of Neural Networks

3)Training Algorithms

a)Quick Propagation

b)Conjugate Gradient Descent

c)Levenberg Marquadart

d)Quasi Newton

e)Newtons Method

4)Topology Optimization

a)Genetic Algorithm

b)Trial and Error

5) Polynomial Neural Network

**Course Duration**: Minimum One Year and more if required

**Certificate**: Yes and :

i)**Self-Paced Learning Option**: Yes

ii)**Course Videos & Readings**: Yes

iii)**Practice Quizzes**: Yes

iv)**Graded Assignments with Peer Feedback**: Yes

v)**Graded Quizzes with Feedback**: Yes

vi)**Scope of Paper/Book Chapter Publication**: Yes

vii) *Scope of one to one interaction with the coordinator for one year.*

**Introduction to Artificial Neural Networks**

Learn about the Artificial Neural Networks, the backbone of Artificial Intelligence in a Self Paced Certificate Course. Both Simple and Polynomial Neural Networks were covered with Self Explanatory Presentations along with example problems. On securing pass marks in the Weekly Assignments and End of the Month Tests, Certificate of Completion is provided. Scope of publication will also be granted at the end of the course and on securing pass mark in the assignment and tests.

## Course Content :

1)Introduction

2)Classification of Neural Networks

3)Training Algorithms

a)Quick Propagation

b)Conjugate Gradient Descent

c)Levenberg Marquadart

d)Quasi Newton

e)Newtons Method

4)Topology Optimization

a)Genetic Algorithm

b)Trial and Error

5) Polynomial Neural Network

Course Duration: Minimum One Year and more if required

Certificate: Yes and :i)

Self-Paced Learning Option: Yesii)

Course Videos & Readings: Yesiii)

Practice Quizzes: Yesiv)

Graded Assignments with Peer Feedback: Yesv)

Graded Quizzes with Feedback: Yesvi)

Scope of Paper/Book Chapter Publication: Yesvii)

Scope of one to one interaction with the coordinator for one year.

#### Monthly

#### Every 6 months

#### Yearly

Explained with example problems.Weekly Assignments and End of Month Tests and lastly Opportunity to Publish

##### Course Duration

One Year but can be extended##### How many examples provided

Minimum 10 per topic but regularly updated##### What I will miss if I terminate the subscription ?

Regular updates in Examples, Case Studies and New Materials

- Explained with example problems.Weekly Assignments and End of Month Tests and lastly Opportunity to Publish
- Course Duration
**One Year but can be extended** - How many examples provided
**Minimum 10 per topic but regularly updated** - What I will miss if I terminate the subscription ?
**Regular updates in Examples, Case Studies and New Materials**