Instructor: Alper Karakus
Lectures: 16
Students: 420
Duration: 10 weeks

Categories: * Certificate Courses *, * E-Certificate Courses *, Artificial Intelligence, Computer Engineering, Computer Science, Courses in English, Engineering & Technology, Physics, Programming, Science & Research, Software

Tags: Artificial, Neural

Neural networks are parallel computing devices, which are basically an attempt to make a computer model of the brain. The main objective is to develop a system to perform various computational tasks faster than the traditional systems. This course by Academy Europe covers the basic concept and terminologies involved in Artificial Neural Network. Sections of this course also explain the architecture as well as the training algorithm of various networks used in ANN.

Free Certification

Academy Europe presents high-quality formal diplomas, certificates and e-certificates which are formal proof and recognition of accredited online courses. It shows all student’s abilities to learn and achieve high results and is very useful to promote personal career including with CVs, job applications and self improvements.

How can you get your certificate at Academy Europe?

You must click “complete” link at the end of every lesson of your course after you finish them.
When you finish all lessons of course, the “finish course” link is going to be active at the end of last lesson.
When you click the “finish course” link, you will finish your course on Academy Europe officially. Then, “certificate” page of you completed course will be automatically active.
You can see and download your certificate online after you click on your “certificate” link.

Audience

This course will be useful for graduates, post graduates, and research students who either have an interest in this subject or have this subject as a part of their curriculum. The reader can be a beginner or an advanced learner.

Prerequisites

ANN is an advanced topic, hence the reader must have basic knowledge of Algorithms, Programming, and Mathematics.

Artificial Neural Network - Basic Concepts 0/1
- Lecture 2.1
  
  Artificial Neural Network – Basic Concepts
Artificial Neural Network - Building Blocks 0/1
- Lecture 3.1
  
  Artificial Neural Network – Building Blocks
Learning and Adaptation 0/1
- Lecture 4.1
  
  Learning and Adaptation
Supervised Learning 0/1
- Lecture 5.1
  
  Supervised Learning
Unsupervised Learning 0/1
- Lecture 6.1
  
  Unsupervised Learning
Learning Vector Quantization 0/1
- Lecture 7.1
  
  Learning Vector Quantization
Adaptive Resonance Theory 0/1
- Lecture 8.1
  
  Adaptive Resonance Theory
Kohonen Self-Organizing Feature Maps 0/1
- Lecture 9.1
  
  Kohonen Self-Organizing Feature Maps
Associate Memory Network 0/1
- Lecture 10.1
  
  Associate Memory Network
Artificial Neural Network - Hopfield Networks 0/1
- Lecture 11.1
  
  Artificial Neural Network – Hopfield Networks
Boltzmann Machine 0/1
- Lecture 12.1
  
  Boltzmann Machine
Brain-State-in-a-Box Network 0/1
- Lecture 13.1
  
  Brain-State-in-a-Box Network
Optimization Using Hopfield Network 0/1
- Lecture 14.1
  
  Optimization Using Hopfield Network
Other Optimization Techniques 0/1
- Lecture 15.1
  
  Other Optimization Techniques
Artificial Neural Network - Genetic Algorithm 0/1
- Lecture 16.1
  
  Artificial Neural Network – Genetic Algorithm
Applications of Neural Networks 0/1
- Lecture 17.1
  
  Applications of Neural Networks

Alper Karakus

Alper Karakus is the CEO and Founder of Academy Europe. He holds a PhD in Educational Technology, double masters degree in Computer and Electrical Engineering and bachelors degree in Electrical Engineering. He has worked extensively as an automotive engineer, vehicle software engineer, braking system designer, system trainer and educater in advanced engineering technologies. He has 2 patents in cluster and multiplexer control unit design. He works as a researcher and edupreneur for free learning forever for everyone. His vision is that providing the provision of learning products and services that provoke authentic, comprehensive, continuous, creative and challenging learning experiences.

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Artificial Neural Network

Free Certification

Audience

Prerequisites

Artificial Neural Network - Basic Concepts 0/1

Artificial Neural Network - Building Blocks 0/1

Learning and Adaptation 0/1

Supervised Learning 0/1

Unsupervised Learning 0/1

Learning Vector Quantization 0/1

Adaptive Resonance Theory 0/1

Kohonen Self-Organizing Feature Maps 0/1

Associate Memory Network 0/1

Artificial Neural Network - Hopfield Networks 0/1

Boltzmann Machine 0/1

Brain-State-in-a-Box Network 0/1

Optimization Using Hopfield Network 0/1

Other Optimization Techniques 0/1

Artificial Neural Network - Genetic Algorithm 0/1

Applications of Neural Networks 0/1

Price

Rating

Artificial Neural Network

Free Certification

Audience

Prerequisites

Artificial Neural Network - Basic Concepts 0/1

Artificial Neural Network - Building Blocks 0/1

Learning and Adaptation 0/1

Supervised Learning 0/1

Unsupervised Learning 0/1

Learning Vector Quantization 0/1

Adaptive Resonance Theory 0/1

Kohonen Self-Organizing Feature Maps 0/1

Associate Memory Network 0/1

Artificial Neural Network - Hopfield Networks 0/1

Boltzmann Machine 0/1

Brain-State-in-a-Box Network 0/1

Optimization Using Hopfield Network 0/1

Other Optimization Techniques 0/1

Artificial Neural Network - Genetic Algorithm 0/1

Applications of Neural Networks 0/1

Price

Rating

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