Complete Machine Learning & Data Science with R-2019 (Updated)

Learn Machine learning & Data Science with R programming, rstudio, statistics, data wrangling, mining & visualization.

What you'll learn

Fundamentals of Machine learning
Data science
R programming
Data visualization with base R & libraries like ggplot2, lattice, scatter3d plot & more
Applied statistics for machine learning covering important topics like standard error, variance, p value, t-test etc.
Machine learning models like Neural network, linear regression, logistic regression & more.
Handle advance concepts like dimension reduction & data reduction techniques with PCA & K-Means
Classification & Regression Tree with Random Forest machine learning model
Real life projects to help you understand industry application
Tips & Tools to create your online portfolio to promote your skills
Tutorial on job searching strategy to find appropriate jobs in machine learning, data science or any other industry.


Requirements

Laptop/desktop/phone with internet connection
Desire to learn machine learning & data science

Description

Learn complete Machine learning & Data Science with R covering applied statistics, R programming, data visualization & machine learning models like neural network, CART, Logistic regression & more.

Unlike most machine learning courses out there, the Complete Machine Learning & Data Science with R-2019 is comprehensive. We are not only covering popular machine learning techniques but also additional techniques like ANOVA & CART techniques.

Course is structured into various parts like R programming, data selection & manipulation, applied statistics & data visualization. This will help you with the structure of data science and machine learning.


Here are some highlights of the program:



Visualization with R for machine learning

Applied statistics for machine learning

Machine learning fundamentals

ANOVA Implementation with R

Linear regression with R

Logistic Regression

Dimension Reduction Technique

Tree-based machine learning techniques

KNN Implementation

Naïve Bayes

Neural network machine learning technique


When you sign up for the course, you also:


Get career guidance to help you get into data science

Learn how to build your portfolio

Create over 10 projects to add to your portfolio

Carry out the course at your own pace with lifetime access

Who this course is for:

Students
Working professionals looking to move into data science & machine learning career
Statisticians interested in machine learning