Basics of R for Data Science

Basics of R for Data Science, available at $19.99, has an average rating of 4.4, with 33 lectures, based on 5 reviews, and has 48 subscribers.

You will learn about Data Science intermidate level linear Regression This course is ideal for individuals who are Analytics Aspirants With R It is particularly useful for Analytics Aspirants With R.

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Summary

Title: Basics of R for Data Science

Price: $19.99

Average Rating: 4.4

Number of Lectures: 33

Number of Published Lectures: 33

Number of Curriculum Items: 33

Number of Published Curriculum Objects: 33

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

Data Science intermidate level

linear Regression

Who Should Attend

Analytics Aspirants With R

Target Audiences

Analytics Aspirants With R

Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from noisy, structured and unstructured data and apply knowledge and actionable insights from data across a broad range of application domains. Data science is related to data mining, machine learning and big data.

Data science is a “concept to unify statistics, data analysis, informatics, and their related methods” in order to “understand and analyse actual phenomena” with data. It uses techniques and theories drawn from many fields within the context of mathematics, statistics, computer science, information science, and domain knowledge. However, data science is different from computer science and information science. Turing Award winner Jim Gray imagined data science as a “fourth paradigm” of science (empirical, theoretical, computational, and now data-driven) and asserted that “everything about science is changing because of the impact of information technology” and the data deluge. A data scientist is someone who creates programming code and combines it with statistical knowledge to create insights from data.

Data science is one of the trending fields. This course is designed for Data Science Enthusiasts who want to start their career in Data Science with R. You are required to have the basic knowledge of programming and you don’t need to be a superman in coding. This course is designed with simple examples for intermediate learners and its created with my young research team who are mastered in below concepts

Introduction to R,Overview of R,Data types in R,Basic Data management in R,Basic Flow control in R,Basic Graphs in R,Basic of Statistics, Linear Regression

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Lecture 2: Basic Syntax

Lecture 3: Introduction To Data Structures In R

Lecture 4: Vectors

Lecture 5: Matrices

Lecture 6: Data Frames

Lecture 7: Matrices

Lecture 8: Arrays

Chapter 2: Data Importing

Lecture 1: Importing through Key Board

Lecture 2: Importing CSV Files

Lecture 3: Basic Functions in R

Chapter 3: Data Management

Lecture 1: Introduction To Data Management

Lecture 2: Dates

Lecture 3: Typecasting

Lecture 4: Renaming

Lecture 5: Sorting Merging Subsetting

Lecture 6: Math functions

Chapter 4: Basic Graphs

Lecture 1: Introduction T Graphs

Lecture 2: Plot function

Lecture 3: Bar plot

Lecture 4: Pie Chart

Lecture 5: Histogram

Lecture 6: Box plot

Chapter 5: Basic Statistics

Lecture 1: Introduction to statistics

Lecture 2: Descriptive statistics

Lecture 3: Frequency and Contingency Tables

Lecture 4: Statistical Functions

Lecture 5: Correlation

Chapter 6: Linear Regression

Lecture 1: Analytics life cycle

Lecture 2: Types of Learnings

Lecture 3: Linear Regression Theory

Lecture 4: Model Evaluation

Lecture 5: Implementation of Linear Regression

Instructors

Prof. M. NAGABHUSHANA RAO , Team, MLRITM, Hyderabad – INDIA
R Programming Language Basics

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2 stars: 0 votes

3 stars: 1 votes

4 stars: 3 votes

5 stars: 1 votes

Frequently Asked Questions

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You can view and review the lecture materials indefinitely, like an on-demand channel.

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