Artificial Intelligence Bootcamp in R Programming (Udemy.com)

Practical Neural Networks and Deep Learning in R

( 11 Reviews )

Created by: Minerva Singh

Produced in 2021

What you will learn

How to build Artificial Neural Networks (ANN) in R
How to build Convolutional Neural Networks (CNN) in R
How to use H20 package in R to solve real world challenges
Read Data Into R Environment From Different Sources
Implement Pre-processing Tasks in R Environment

Quality Score

Content Quality

Video Quality

Qualified Instructor

Course Pace

Course Depth & Coverage

Overall Score : 94 / 100

Course Description

YOUR COMPLETE GUIDE TO ARTIFICIAL NEURAL NETWORKS & DEEP LEARNING IN R:

This course covers the main aspects of neural networks and deep learning. If you take this course, you can do away with taking other courses or buying books on R based data science.

In this age of big data, companies across the globe use R to sift through the avalanche of information at their disposal. By becoming proficient in neural networks and deep learning in R, you can give your company a competitive edge and boost your career to the next level!

LEARN FROM AN EXPERT DATA SCIENTIST:

My name is Minerva Singh and I am an Oxford University MPhil (Geography and Environment) graduate. I recently finished a PhD at Cambridge University.

I have +5 years of experience in analyzing real life data from different sources using data science related techniques and producing publications for international peer reviewed journals.

Over the course of my research I realized almost all the R data science courses and books out there do not account for the multidimensional nature of the topic .

This course will give you a robust grounding in the main aspects of practical neural networks and deep learning.

Unlike other R instructors, I dig deep into the data science features of R and give you a one-of-a-kind grounding in data science...

You will go all the way from carrying out data reading & cleaning to to finally implementing powerful neural networks and deep learning algorithms and evaluating their performance using R.

Among other things:

You will be introduced to powerful R-based deep learning packages such as h2o and MXNET.

You will be introduced to deep neural networks (DNN), convolution neural networks (CNN) and unsupervised methods.

You will learn how to implement convolutional neural networks (CNN)s on imagery data using the Keras framework

You will learn to apply these frameworks to real life data including credit card fraud data, tumor data, images among others for classification and regression applications.

With this course, you'll have the keys to the entire R Neural Networks and Deep Learning Kingdom!Who this course is for:

Data Scientist and Machine Learning enthusiasts who wants to add R Programming into their toolkit

Time: 10h

Instructor Details

Minerva Singh

4.7 Rating
11 Reviews

Hello. I am a PhD graduate from Cambridge University where I specialized in Tropical Ecology. I am also a Data Scientist on the side. As a part of my research I have to carry out extensive data analysis, including spatial data analysis.or this purpose I prefer to use a combination of freeware tools- R, QGIS and Python.I do most of my spatial data analysis work using R and QGIS. Apart from being free, these are very powerful tools for data visualization, processing and analysis. I also hold an MPhil degree in Geography and Environment from Oxford University. I have honed my statistical and data analysis skills through a number of MOOCs including The Analytics Edge (R based statistics and machine learning course offered by EdX), Statistical Learning (R based Machine Learning course offered by Standford online). In addition to spatial data analysis, I am also proficient in statistical analysis, machine learning and data mining. I also enjoy general programming, data visualization and web development. In addition to being a scientist and number cruncher, I am an avid travelerHi there,
We are the SuperDataScience Social team. You will be hearing from us when new SDS courses are released, when we publish new podcasts, blogs, share cheatsheets and more!
We are here to help you stay on the cutting edge of Data Science and Technology.
See you in class,
Sincerely,
The Real People at SuperDataScience

Project Based Python Programming For Kids & Beginners

Project Based Python Programming For Kids & Beginners (2018)
4.6 (382 Reviews)

- Provider: Udemy
- Time: 5h

$11.99

Regression Analysis for Statistics & Machine Learning in R

Regression Analysis for Statistics & Machine Learning in R (2021)
4.6 (295 Reviews)

- Provider: Udemy
- Time: 7.5h

$11.99

Core Spatial Data Analysis: Introductory GIS with R and QGIS

Core Spatial Data Analysis: Introductory GIS with R and QGIS (2021)
4.4 (288 Reviews)

- Provider: Udemy
- Time: 2.5h

$11.99

Data Science:Data Mining & Natural Language Processing in R

Data Science:Data Mining & Natural Language Processing in R (2021)
4.6 (196 Reviews)

- Provider: Udemy
- Time: 13h

$11.99

[Intermediate] Spatial Data Analysis with R, QGIS & More

[Intermediate] Spatial Data Analysis with R, QGIS & More (2021)
4.7 (170 Reviews)

- Provider: Udemy
- Time: 5h

$11.99

Species Distribution Models with GIS & Machine Learning in R

Species Distribution Models with GIS & Machine Learning in R (2021)
4.8 (159 Reviews)

- Provider: Udemy
- Time: 3.5h

$11.99

All courses by Minerva Singh

More artificial intelligence courses

Convolutional Neural Networks
5.0 (709 Reviews)

- Provider: Coursera
- Time: 21h

Free

AI For Everyone
5.0 (541 Reviews)

- Provider: Coursera
- Time: 9h

Free

Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization

Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
5.0 (526 Reviews)

- Provider: Coursera
- Time: 15h

Free

A Crash Course in Data Science
5.0 (490 Reviews)

- Provider: Coursera
- Time: 5h

Free

Sequence Models
4.9 (755 Reviews)

- Provider: Coursera
- Time: 18h

Free

Open Source tools for Data Science
4.9 (485 Reviews)

- Provider: Coursera
- Time: 7h

Free

All artificial intelligence courses

Reviews

4.7

11 total reviews

5 star 4 star 3 star 2 star 1 star

Write a Review

By Anil Kumar Pandey

Informative

By sushma Pandey

Informative and excellent

By Susan Tang

This is most detailed AI course I seen

By Monica Shah

It is good to have a deep learning course that uses R

By Posey Parker

A good mix of theory and application

By Sunny Lamba

I really enjoyed the theoretical lectures. They teach the basic ideas without the jargon

By John D Hazard

Instructor assumes quite a bit of previous knowledge. I wouldn't recommend to a beginner. MxNet won't install on R 3.6.1.

By Prity Polly

Very thorough deep learning course in R

By Selvia Jain

Good mix of theory and practical AI lectures

By Infine

super good material! but you need to have some little experience with R

By Bryan Butler

Overall, this was a very good course to cover a wide variety of deep learning frameworks in R including MXNet, H2o, and Keras across a variety of different uses cases. The structure is set so that there is a limited amount of theory (which I covered in previous python courses), and more code work which gets into the nuts and bolts of how to actually use these frameworks in R.

My version of R (3.6.1) was newer than the one available for MXNet so I skipped those sections; in my work H2o and Keras are far more relevant.

The main models focused on both 'toy' data like MNist and some real world data. With some of the Keras models at the end, it would have been great to take it one step further beyond the model accuracy and loss and show the final use - especially in the text/fraud case.