facebook-pixel
$49.99
Certification

Industry recognized certification enables you to add this credential to your resume upon completion of all courses

Need Custom Training for Your Team?
Get Quote
Call Us

Toll Free (844) 397-3739

Inquire About This Course
Instructor
Ugonna Alinnor, Instructor - Deep Learning with R

Ugonna Alinnor

Founder of Cartwheel Technologies, an Artificial Intelligence Company. Investigated the effect of Avocado leaf extracts on male and female Wistar rats. Analyzed and wrangled the NYC subway data.

Instructor: Ugonna Alinnor

Learn how to develop and apply your own deep neural networks to solve problems like Speech recognition, drug discovery, breast cancer detection, and more.

Deep learning is the core technology behind artificial intelligence that is transforming our world.

In this course, you’ll cover Convolutional and Recurrent Neural Networks, Generative Adversarial Networks, Data preparation, Deployment, and more. You’ll use R, and have access to GPUs to train models faster.  This is the ideal point-of-entry into the field of AI.

Instructor is the founder of Cartwheel Technologies, an Artificial Intelligence Company.   Investigated the effect of Avocado leaf extracts on male and female Wistar rats. Analyzed and wrangled the NYC subway data.

Course Description

Deep learning is the core technology behind artificial intelligence that is transforming our world. In this course, you’ll cover Convolutional and Recurrent Neural Networks, Generative Adversarial Networks, Data preparation, Deployment, and more. You’ll use R, and have access to GPUs to train models faster. This is the ideal point-of-entry into the field of AI.

What am I going to get from this course?

Learning and understanding of Deep Learning technologies and how it can be applied to research.

Prerequisites and Target Audience

What will students need to know or do before starting this course?

Outside of the computer science knowledge, it's a beginner-friendly program that will take you from beginner’s level to expert level understanding of Deep Learning technologies.

Who should take this course? Who should not?

Created specifically for students who are interested in research, machine learning, Artificial Intelligence, and/or deep learning, and who have a basic knowledge of computer science, including R. 

Curriculum

Module 1: Deep Learning

Lecture 1 Deep Learning-Definition

Defining deep learning.

Lecture 2 Deep Learning- Examples at Work

Explain why does deep learning even matter.

Module 2: Overview

Lecture 3 Deep Learning- Overview

Examples of how deep learning is used in different industries.

Lecture 4 Deep Learning- Why they Work

How deep learning works, a basic understanding of the tech.

Module 3: History

Lecture 5 A Brief History- Part 1

Computers can now play games, who taught them?

Lecture 6 Brief History- part 2

Growth in deep learning conferences and online course continues to soar because of its wide applicability .

Lecture 7 Brief History- part 3

Who are the founding founders of Deep learning?

Lecture 8 Brief History- part 4

Long short-term memory was proposed.

Module 4: Deep Learning Models

Lecture 9 Deep Learning Models

Here a few classic deep learning models - Convolutional Neural Network, Recurrent Neural Network.

Lecture 10 Recurrent Neural Network

The power of Recurrent Neural Network.

Lecture 11 Reinforcement ( Deep) Learning

More classic deep learning models - Auto-encoders, Reinforcement Learning .

Module 5: Challenges

Lecture 12 Deep Learning Challenges

Deep Learning is no doubt a powerful tool but they are some challenges lying ahead.

Lecture 13 Deep Learning Challenges- Contd

Deep Learning is no doubt a powerful tool but they are some challenges lying ahead.

Module 6: Deep Learning App (1/4)

Lecture 14 Speech Recognition

Learn to build a deep learning App that converts audio and voice into written text.

Lecture 15 Data Preparation (Case study)

Data preparation a case study.

Module 7: Deep Learning App (2/4)

Lecture 16 Image Recognition

An introduction into how computer recognizes faces.

Module 8: Deep Learning App (3/4)

Lecture 17 Breast Cancer Detection

How breast cancer can be detected in a woman’s breast given a a certain data-set.

Module 9: Deep Learning App (4/4)

Lecture 18 Drug Discovery

This module will show how Deep learning can be applied into drug discovery.

Module 10: Summary

Lecture 19 Why Deep Learning is Relevant

Much has been said of Deep learning but we are only scratching the surface.

350