Overview

This online instructor led training course provides the knowledge to better understand deep learning algorithms. In this course students will learn key topics including how neural networks work, the different type of neural networks, how an auto encoder works, and more.

COURSE INSTRUCTOR: Cameron Vetter, AI
COURSE DIFFICULTY: Beginner
COURSE DURATION: 1h 31m

After completing this online training course, students will be able to:

  • Better understanding of an artificial neural network and how it learns

  • Better understanding of convolutional neural networks and how they’re used

  • Better understanding of recurrent neural network

  • Better understanding of self organizing maps and why they converge

  • Better understanding of auto encoder

This course is intended for professionals and managers who are looking to better understand deep learning algorithms, what the current neural networks are, what’s changing, and how it can change your job.

None, but we do recommend Introduction to AI if you’re new to artificial intelligence or machine learning.

01. Artificial Neural Networks
  • What is an ANN
  • What is a Neuron
  • How Does it Learn
02. Convolutional Neural Networks
  • What is a CNN
  • What is a CNN: Convolution
  • What is a CNN: Pooling
  • What is a CNN: Flattening
  • How are They Used
03. Recurrent Neural Networks
  • What is an RNN
  • What Makes it Recurrent?
  • Unrolling Over Time
  • Long Short Term Memory Network
04. Self Organizing Maps
  • What is a Self Organizing Map
  • How Does it Self Organize?
  • Why does it converge?
  • Traveling Salesperson Problem
  • K-Means Clustering
05. Auto Encoder
  • What is an Auto Encoder
  • AutoEncoder Neural Networks Structure
  • Denoising with AutoEncoder