Computers & Technology   

Learn how Deep Learning (DL) paired with Neural Networks (NN) have taken Artificial Intelligence into new possibilities.  Unlike Expert Systems they are not programmed with the classic set of IF, THEN, ELSE rules.  Understand how Neural Networks are programmed to LEARN.  See how Deep Learning/Neural Networks can learn much like humans do and how they are taught.  Understand how this architecture uses an input layer based on object features, feeding numerous hidden layers of perceptrons that filter using weights and biases, to acquire the output layer of “knowledge”.

After this session you will understand what you just read and the meaning of the above image. Through examples you will see the basic differences between an Expert System and a DL/NN.   Learn how various forms of Neural Networks function.  Learn about the basic concepts of Neural Networks, and how to train them.  We will focus on Convolutional Neural Networks (CNN).  Gain an understanding of how massive amounts of structured and unstructured data are converted to useful knowledge that can be applied to various fields such as customer support, medical diagnosis, image analysis and self-driving vehicles. Learn how a computer can decipher handwriting or pick a dog out of a millions of animal pictures. Learn the difference between forward chaining and backward chaining, supervised learning and unsupervised learning, and the advantages of using multilayer perceptrons. You will be able to communicate with others in the field and develop an understanding and appreciation of what these systems can do to resolve complex problems and how this all will fit into the future.  This class is designed to not only spark an interest in Artificial Intelligence but also to generate interest in very lucrative careers. Don’t miss this opportunity to gain an understanding of the most powerful field of study in computer science.

Learn how Deep Learning (DL) paired with Neural Networks (NN) have taken Artificial Intelligence into new possibilities.  Unlike Expert Systems they are not programmed with the classic set of IF, THEN, ELSE rules.  Understand how Neural Networks are programmed to LEARN.  See how Deep Learning/Neural Networks can learn much like humans do and how they are taught.  Understand how this architecture uses an input layer based on object features, feeding numerous hidden layers of perceptrons that filter using weights and biases, to acquire the output layer of “knowledge”.

After this session you will understand what you just read and the meaning of the above image. Through examples you will see the basic differences between an Expert System and a DL/NN.   Learn how various forms of Neural Networks function.  Learn about the basic concepts of Neural Networks, and how to train them.  We will focus on Convolutional Neural Networks (CNN).  Gain an understanding of how massive amounts of structured and unstructured data are converted to useful knowledge that can be applied to various fields such as customer support, medical diagnosis, image analysis and self-driving vehicles. Learn how a computer can decipher handwriting or pick a dog out of a millions of animal pictures. Learn the difference between forward chaining and backward chaining, supervised learning and unsupervised learning, and the advantages of using multilayer perceptrons. You will be able to communicate with others in the field and develop an understanding and appreciation of what these systems can do to resolve complex problems and how this all will fit into the future.  This class is designed to not only spark an interest in Artificial Intelligence but also to generate interest in very lucrative careers. Don’t miss this opportunity to gain an understanding of the most powerful field of study in computer science.

Learn how Deep Learning (DL) paired with Neural Networks (NN) have taken Artificial Intelligence into new possibilities.  Unlike Expert Systems they are not programmed with the classic set of IF, THEN, ELSE rules.  Understand how Neural Networks are programmed to LEARN.  See how Deep Learning/Neural Networks can learn much like humans do and how they are taught.  Understand how this architecture uses an input layer based on object features, feeding numerous hidden layers of perceptrons that filter using weights and biases, to acquire the output layer of “knowledge”.

After this session you will understand what you just read and the meaning of the above image. Through examples you will see the basic differences between an Expert System and a DL/NN.   Learn how various forms of Neural Networks function.  Learn about the basic concepts of Neural Networks, and how to train them.  We will focus on Convolutional Neural Networks (CNN).  Gain an understanding of how massive amounts of structured and unstructured data are converted to useful knowledge that can be applied to various fields such as customer support, medical diagnosis, image analysis and self-driving vehicles. Learn how a computer can decipher handwriting or pick a dog out of a millions of animal pictures. Learn the difference between forward chaining and backward chaining, supervised learning and unsupervised learning, and the advantages of using multilayer perceptrons. You will be able to communicate with others in the field and develop an understanding and appreciation of what these systems can do to resolve complex problems and how this all will fit into the future.  This class is designed to not only spark an interest in Artificial Intelligence but also to generate interest in very lucrative careers. Don’t miss this opportunity to gain an understanding of the most powerful field of study in computer science.