ARTIFICIAL NEURAL NETWORK (ANN)
- What you will Learn?
- Introduction to Artificial Neural Network (ANN)
- Advantages of ANN
- Disadvantages of ANN
- Applications of ANN
- Neurons Concept
- Schematic Diagram of Neuron
- Comparison Between Human brain and ANN
- Artificial Neuron Network Simulation To Neuron
- Layers In ANN Model
- Artificial Neural Network(ANN) Structure
- Supervised ANN and Unsupervised ANN
- Characteristics of Artificial Neural Networks
- Elements of Artificial Neural Networks
- Different Types of Artificial Neural Networks
- Transfer Functions (Activation Functions) of ANN
- Training Of ANN
- Applications of ANN Other Activities
- Self-Objective Type Question
- Descriptive type Interview questions
- Basic understanding of Computer Programming terminologies.
- Basic knowledge of Artificial intelligence and its terminologies.
- Basic understanding of Mathematics and statistics.
- Understanding of any one programming language is an added advantage
- Great desire to Learn AI
The aim of this course is to understand the concepts and develop Artificial Neural Network (ANN). ANN mimics human brain. Like human brain, ANN can be trained to solve various magnitudes of real life problems. In this Level, we will learn Introduction of ANN, Hidden layers, backpropagation, Supervised and Unsupervised ANN,How to train ANN and its wide range of applications. And the end of this course ,you will learn to develop your own Neural Network using python programming language.
After every final test the student will receive a certificate of completion which will be on blockchain. All this learning gives the students an edge over others and learning it through Blocklogy eLearning Mobile App is always easy and user friendly.
Course for whom
- IT Professionals(freshers or experienced).
- Non IT professionals wants to make career in Data Science.
- Business Analyst