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Quick Facts

Medium Of Instructions	Mode Of Learning	Mode Of Delivery
English	Self Study, Virtual Classroom	Video and Text Based

Course Overview

The Data Analytics for Machine Learning with R training makes candidates familiar with standard data analysis and management technologies, including machine learning, which may be used in real-world situations for creating statistical models by utilizing machine learning.

This IIIT-Bhagalpur Certified Data Analytics for Machine Learning with R Online Course is designed to develop professional Data Analysts capable of working on data mining, machine learning, and statistical modeling for prescriptive and predictive corporate analytics. This program provides the opportunity to gain a thorough grasp and hands-on experience in Machine Learning and Data Analysis.

The Data Analytics for Machine Learning with R syllabus broadly covers R, as it is the most common data analytics tool because it is open-source, versatile, and has a large number of packages and a big community. “R” is the most popular program for Data Scientists because of its statistical capacity, graphical capability, and extensive range of packages. Join the queue for exciting professions in new technologies and become specialists with the IIIT-Bhagalpur Training Program to obtain experience and skills to tackle difficult business issues.

The Highlights

12 Interactive Live Modules
Project-based Learning
Offered by IIIT Bhagalpur
2 Capstone Projects
25 Interactive Sessions
50 Hours of Learning
Course provider Vitti AI

Programme Offerings

Learning Management System
Projects
assignments
online learning
Workshop
Learning aid
reference materials

Courses and Certificate Fees

Certificate Availability	Certificate Providing Authority
yes	IIIT Bhagalpur

Data Analytics for Machine Learning with R Fees

Course Fee

Rs. 40,000 + GST

Eligibility Criteria

Certification Qualifying Details

After completing the Data Analytics for Machine Learning with R course from IIIT Bhagalpur via Vitti AI with all the assignments, projects, and class works, candidates will receive the Data Analytics for Machine Learning with R certification.

What you will learn

Machine learningKnowledge of PythonKnowledge of Artificial Intelligence

After completing the Data Analytics for Machine Learning with R online training, students will learn about machine learning, artificial intelligence, and its parts including supervised learning, unsupervised learning, and reinforcement learning. Candidates will also learn about various programming languages such as Python, R.

Who it is for

Data AnalystData Scientist

Any intermediate-level persons who are familiar with the fundamentals of machine learning, including traditional methods such as logistic regression and linear regression, but wish to learn a little more about it investigate all of its domains.
Anyone who is not very familiar with coding but is interested in Machine Learning and wants to apply it to datasets effortlessly.
College students who are interested in pursuing a career in data science.
Any data analysts who wish to enhance their Machine Learning skills.
Anyone who is dissatisfied with their current work and wishes to become a Data Scientist.
Anyone who wants to add value to their business by leveraging sophisticated Machine Learning technologies.

Admission Details

To Enrol in the Data Analytics for Machine Learning with R online course, follow the steps mentioned below :

Step 1. Follow the link below to see the official Data Analytics for Machine Learning with R course page.

(https://www.vittiai.com/course/data-analytics-for-machine-learning-with-r)

Step 2. To proceed, click the 'Pay Now' button.

Step 3. Fill out the essential fields and press the "Submit" button.

Step 4. Once you have paid the course cost, you will get your credentials through email.

Step 5. To begin learning, log in using your credentials.

The Syllabus

Introduction to Artificial Intelligence (Evolution of Technology)
Branches of Artificial Intelligence and what is Machine Learning.
Supervised, Unsupervised & Reinforcement Learning.
How machine learning can be applied in technology, science, trading etc.
Comparison B/W R, Python & SAS
Why Learn R?
Introduction to R.
R Overview, R Interface, R WorkSpace, Help, Variables, Programming
Install R.
Running a few simple programs

Some Common Terms & Basics in R
Data Types
Importing Data
Keyboard Input, Database Input, Export Data
Variable Labels, Value Labels, Missing Data, date Values
R Iteration & Conditional Constructs
R Packages: installation and Usages
Data Manipulation
Hands-On Session
Some Advance Programs using Data from R Data repository

Architecture of CNN
Types of layers in CNN
Building an image classifier using CNN
Deep Learning with CNN

Introduction to Data Visualization
Basic Graphics: line, bar, box, histogram plots
Trellis
Scatter plots
Basic Statistics: mean median, mode, percentile, quantile
Frequency Distribution, Histogram Analysis
Data: Distribution, Types of Data Distribution, and Hypothesis Testing

Introduction to Predictive Models
Linear Regression
Logistic Regression
Decision Tree
Random Forest
Implementation of Predictive Models using R
The Art of Feature Engineering, Pattern recognition & Principal component analysis

Classification & Clustering
Supervised Learning K- Nearest Neighbors Classification
Unsupervised Learning K – means Clustering Algorithm
Reinforcement Learning
Implementation of Classification & Clustering Using R
Introduction to Neural Networks
Introduction Deep Learning
Implementation of Neural Network using R, Multilayer Perceptron (MLP), Support Vector Machine (SOM)