Course Content
1. R Programming Basics

•  Introduction To R Programming

•  Installing R And R Studio

•  Basic Syntax

•  Data Types And Variables

•  Taking Input

•  Loops And Conditional Statements

•  Using Next And Repeat

2. R Data Structures

•  R Vectors

•  Matrix

•  List In R

•  Data Frame

•  Factors

•  Arrays

3. R Functions

•  Functional Programming With R

•  Return Multiple Values

•  Environment And Scope

•  Recursion

•  Infix Operator And Switch

4. R Objects and Class

•  Object And Class

•  R S3 Class

•  R S4 Class

•  R Reference Class

•  R Inheritance

5. R Apply Family Functions

•  Apply() – Alternatives Of For Loop

•  Lapply()

•  Sapply()

•  Vapply()

•  Mapply()

•  Rapply()

•  Tapply()

6. Exploratory Data Analysis

•  Basic Graphs

•  Bar Plot And Histograms

•  Pie Chart

•  Box Plot

•  Saving Plot

•  Treating Missing Values

•  Working With Categorical And Continuous Data

7. Data Manipulation

•  Feature Engineering

•  Techniques Of Outlier Detection And Treatment

•  Label Encoding / One Hot Encoding

8. R Packages

•  Introduction To Dplyr

•  Filter, Select, Mutate, Summarize And Distinct

•  Introduction To Ggplot2

•  Grammar Of Graphics

•  Ggplot2 Vs Basegraphics

•  Aesthetic Mapping

•  Geometric Object

•  Plotting Histograms, Barplots, Frequency Polygons With Ggplot2

•  Introduction To Ggrepel

•  Set Theme In Ggplot

•  Faceting

•  Introduction To Tidyr

•  Web Scrapping With Rvest Module

•  Reshape2

•  Plotly

9. Predictive Modeling Using Machine Learning

•  Linear Regression

•  Logistic Regression

•  Decision Tree

•  Clustering

•  Apriori

•  Eclat

•  Upper Confidence Bound (UCB)

•  Thompson Sampling

COURSE OVERVIEW

The Machine Learning with R course is designed to provide you with a comprehensive understanding of machine learning concepts and techniques using the R programming language.

Through a combination of theoretical explanations and hands-on coding exercises, this course aims to equip you with the necessary skills to build and deploy machine learning models using R.

COURSE OBJECTIVES

Develop a solid understanding of the Unity game development engine and its core features.

Learn to create interactive and visually appealing games using Unity's tools and components.

Gain proficiency in game physics, scripting, and implementing game mechanics.

Understand the process of designing game levels and user interfaces for optimal player experience.

Course Instructors
Instructor 1

Ravikant Tyagi

Hello everyone, I am Ravikant Tyagi and I do have experience of 8+ years in IT as a developer and trainer. I have more than 100 websites live on internet and I have taught thousands of students, teachers & developers to learn to code and how to become professional developer with 100% practical knowledge.

What People Says About us


Frequently Asked Questions
Can I attend a demo session before enrolment?

•  Yes! You can attend a One Demo class free of Cost.

What if I miss a class?

•  All Classes sessions are recorded in HD Quality , so if you miss a class so you can watch the recordings.

Will I get placement assistance?

•  100 % Placement Assistance.

Who are the Trainers at Brain Mentors?

•  All our Trainers are Software Professionals, Having 7 to 15 Years’ of Experience. All Trainers worked with Top Brands.

What if I have more queries?

•  Feel free to contact us on :7042434524 01145138947

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