Machine Learning with Python and R

Understand Machine Learning, Data Processing with Python and R

Overview

Machine Learning with Python and R Certification



The Machine Learning Online Course gives the learner a holistic understanding of machine learning, covering theory, application, and inner workings of supervised, unsupervised, and deep learning algorithms. The course covers linear regression, K Nearest Neighbors, Clustering, SVM and neural networks using Python and R.

Machine Learning with Python and R Training Objective


Upon completion of this course, a learner should be able to:
– Understand Machine Learning
– Carry out Data processing
– Perform Regression using Python and R
– Perform Classification using Python and R
– Clustering using Python and R, etc…

Duration: 32 Hours

Prerequisites for Machine Learning with Python and R Online Course

Basic Knowledge in R and Python is mandatory. It would be beneficial if the learner has Hadoop skills too

Curriculum


Introduction to Machine Learning

  • What is Machine Learning?
  • Applications of Machine Learning
  • Why Machine Learning is the Future
  • Installing R and R Studio (MAC & Windows)
  • Installing Python and Anaconda (MAC & Windows)

Data Pre-processing

  • Data Preprocessing
  • Importing the Libraries
  • Importing the Dataset
  • For Python learners, summary of Object-oriented programming: classes & objects
  • Missing Data
  • Categorical Data
  • Splitting the Dataset into the Training set and Test set
  • Feature Scaling

Regression

  • Simple Linear Regression
  • Dataset + Business Problem Description
  • Simple Linear Regression in Python
  • Simple Linear Regression in R
  • Multiple Linear Regression
  • Multiple Linear Regression in Python
  • Multiple Linear Regression in R
  • Polynomial Regression
  • Polynomial Regression in Python
  • Polynomial Regression in R
  • Support Vector Regression (SVR)
  • SVR in Python
  • SVR in R
  • Decision Tree Regression in Python
  • Decision Tree Regression in R
  • Random Forest Regression in Python
  • Random Forest Regression in R

Classification

  • Logistic Regression in Python and R
  • K-Nearest Neighbors (K-NN)
  • Support Vector Machine (SVM)
  • Kernel SVM
  • Naive Bayes
  • Decision Tree Classification
  • Random Forest Classification
  • Confusion Matrix
  • CAP Curve

Clustering

  • K-Means Clustering in Python and R
  • Hierarchical Clustering in Python and R

Association Rule Learning

  • Association Rule Learning in Python and R
  • Apriori

Reinforcement Learning

  • Upper Confidence Bound (UCB)
  • Thompson Sampling

Natural Language Processing

  • Natural Language Processing in R
  • Natural Language Processing in Python

Deep Learning

  • Artificial Neural Networks in Python and R
  • Convolution Neural Networks in Python and R

Course Features


LIVE, INSTRUCTOR-LED ONLINE TRAINING

An interactive online live session with an industry expert as your technical trainer/instructor

24/7 SUPPORT

A Technical Team dedicated to resolving your query at any time irrespective of where you are located

LIFETIME LMS ACCESS

Lifetime access to our Learning Management System, again, at any time, from anywhere, till eternity

PRICE MUCH GUARANTEE

The best price, aligning with the quality of our course deliverables.

CERTIFICATE

On completion of the course, you will appear for an assessment conducted by Cognatrix. A course completion certificate will be awarded to those candidates who pass this assessment.

FAQs


CAN I GET ACCESS TO RECORDED SESSIONS OF MISSED CLASSES?

Yes, all our sessions are recorded. Therefore, if you ever miss a class, you will be able to view it on our LMS.

IS THE COURSE MATERIAL AVAILABLE AFTER I FINISH MY CLASS?

The course material is accessible for a lifetime, post-training

WHEN WILL I GET MY CERTIFICATE?

After you successfully complete the training program, you will be evaluated on parameters such as attendance in sessions, an objective examination, and other factors. Based on your overall performance, you will be certified by Cognatrix.