Learn Data Science With R Part 1 of 10
4.5 (31 ratings)
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Learn Data Science With R Part 1 of 10

Data Science with R Basics
New
4.5 (31 ratings)
Instead of using a simple lifetime average, Udemy calculates a course's star rating by considering a number of different factors such as the number of ratings, the age of ratings, and the likelihood of fraudulent ratings.
4,627 students enrolled
Created by Ram Reddy
Last updated 8/2017
English
Price: Free
Includes:
  • 8.5 hours on-demand video
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
What Will I Learn?
  • Basic Data Science Roles
View Curriculum
Requirements
  • Basic Maths,Stats and Programing
Description

You will learn Basics of Data Science like 

You will learn What is Data Science

You will learn Data Types

You will learn Vectors

You will learn Factors

You will learn List

You will learn Matrices

You will learn Data Frames

You will learn Read Data from Files

You will learn Read Data from oracle Database using RJDBC

You will learn Read Data from oracle Database using RODBC

You will learn Read Data from oracle Database using ROracle


Who is the target audience?
  • Anyone who want to work as Data Scientist
Compare to Other Data Science Courses
Curriculum For This Course
10 Lectures
08:41:52
+
Introduction
10 Lectures 08:41:52
What is Data Science
52:29

R Installation and Data Types
01:00:15

Vectors
01:03:07

Data Science Tutorial Part 4 Matrices
52:08

Factors
49:39

Data Frames Part 1
53:58

Data Frames Part 2
31:35

List
34:27

Import Data From Files Part 1
01:03:20

Import Data From Files Part 2 and Import from Oracle
01:00:54
About the Instructor
Ram Reddy
4.4 Average rating
55 Reviews
5,031 Students
9 Courses
Data Scientist

Data scientist and founder of RRITEC, a company dedicated to helping scientists better understand and visualize their data. Ram Has hands-on exposure to a wide variety of datasets has informed him of the many problems scientists face when trying to visualize their data.

Some of the main roles are 

Develop and improve robust predictive algorithms that are the core of the product 

Combine an understanding of business goals with data analysis and machine learning 

Investigate new data sources; acquire, analyze, clean and structure data 

Utilize state of the art machine learning techniques to improve and expand existing models