Introduction to Data Analytics and R Programming
Unlock the Power of Data: Master the Essentials of Data Analytics and R Programming
Updated on Jul, 2024
Language - English
Programming Languages,Data Analytics
Lectures -60
Resources -5
Duration -4 hours
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Course Description
Embark on your journey into the dynamic world of data analytics with this comprehensive introductory course. Designed for beginners, this course will equip you with the essential skills and knowledge needed to analyze, interpret, and visualize data using R, a powerful and versatile programming language widely used in the field.
Throughout the course, you will learn the fundamentals of data analytics, including data collection, cleaning, and transformation. You will explore various statistical methods and techniques to draw meaningful insights from the data. Through hands-on exercises and real-world examples, you will become proficient in using R for data manipulation, statistical analysis, and data visualization.
Key topics covered include:
Understanding the data analytics lifecycle
Basics of R programming and RStudio environment
Whether you're a student, a professional looking to upskill, or simply curious about data, this course will provide you with a solid foundation in data analytics and R programming.
Goals
By the end of this course, students will be able to:
Understand Data Analytics Fundamentals: Comprehend the data analytics lifecycle, including data collection, cleaning, transformation, analysis, and visualization.
Gain Proficiency in R Programming: Develop a solid foundation in R programming, including understanding the RStudio environment, basic syntax, and essential functions.
Prerequisites
This course is designed for beginners, and no prior knowledge of data analytics or R programming is required. However, to ensure a smooth learning experience, the following prerequisites are recommended:
Basic Computer Literacy: Familiarity with basic computer operations, including file management and software installation.
Logical Thinking and Problem-Solving Skills: Ability to think logically and solve problems systematically.
Interest in Data and Analysis: A genuine interest in working with data and a curiosity about how data-driven decisions are made.
Curriculum
Check out the detailed breakdown of what’s inside the course
Introduction to Data Analysis
10 Lectures
-
What is Data
02:50
02:50
-
Importance of Data
03:35
03:35
-
Type of Data - Categorical
03:45
03:45
-
Type of Data - Numerical
02:10
02:10
-
Analytics and Analysis
02:26
02:26
-
Data Analytics
05:39
05:39
-
Data Analysis
02:04
02:04
-
Classification of Data Analytics
09:57
09:57
-
Process
03:12
03:12
-
Resource file
Introduction to R programming
2 Lectures
R and R studio Installation in Ubuntu
6 Lectures
R Programming Basics
11 Lectures
Operators
7 Lectures
Control Structure
3 Lectures
Looping Statement
4 Lectures
String Handling
5 Lectures
Vector Operations
4 Lectures
Functions
8 Lectures
Instructor Details
Vignesh Muthuvelan
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