Data Analysis with R

Data Analysis with R, available at $49.99, has an average rating of 3.8, with 44 lectures, based on 68 reviews, and has 1327 subscribers.

You will learn about Data Science project at the end of the course Learn programming concepts Conduct your independent data analysis Learn by examples Assignments after each section Have fun by doing all above Introduction to data science and analytics This course is ideal for individuals who are Beginners data analysts or Students or Users of other analysis tools or Those who loves data It is particularly useful for Beginners data analysts or Students or Users of other analysis tools or Those who loves data.

Enroll now: Data Analysis with R

Summary

Title: Data Analysis with R

Price: $49.99

Average Rating: 3.8

Number of Lectures: 44

Number of Published Lectures: 44

Number of Curriculum Items: 44

Number of Published Curriculum Objects: 44

Original Price: $64.99

Quality Status: approved

Status: Live

What You Will Learn

Data Science project at the end of the course
Learn programming concepts
Conduct your independent data analysis
Learn by examples
Assignments after each section
Have fun by doing all above
Introduction to data science and analytics

Who Should Attend

Beginners data analysts
Students
Users of other analysis tools
Those who loves data

Target Audiences

Beginners data analysts
Students
Users of other analysis tools
Those who loves data

Data analysis becomes essential part of every day life. After this course, you will be able to conduct data analysis task yourself. Gain insights from the data.

Will be using R– widely used tool for data analysis and visualization.

Data Science projectwill be core course component – will be working on it after mastering all necessary background. Doing data analysis from ground up to final insights.

Starting from very basics we will move to various input and output methods. Yet another important concept – visualizationcapabilities. After the course you will be able to produce convincing graphs.

Background behind functional programmingwill be presented – including building your own functions.

After finishing the course you will feel much more comfortable programming in other languages as well. This is because Rbeing fully empowered programming language itself. Main programming concepts presented:

Various data types
Conditional statements
For and While loops

No previous programming knowledge required.

Finally, dataminingand data science techniques in R delivered in clear fashion together with assignments to make sure you understand topics. Main statistical capabilities behind data science covered.

Course is interactive. Specific topic covered in each lecture. Each lecture includes multiple examples. All material covered in videos are available for download! This way student is able to program himself – break things and fix them.

Students will finish course in approximately 7-10 days working 3 hours per day. Time spent working individually included.

After each section assignment should be completed to make sure you understand material in the section.After you are ready with the solution – watch video explaining concepts behind assignment.

I will be ready to give you a hand by answering your questions.

Finally, this course is specifically designed to get up to speed fast. Biggest emphasis put on real examples and programming yourself. This distinguishes this course from other material available online – usual courses includes vague slides and long textbooks with no real practise.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Course outline

Lecture 2: Install R

Chapter 2: Getting feet wet

Lecture 1: Working with directories

Lecture 2: Getting help

Lecture 3: Basic commands

Lecture 4: Common functions

Lecture 5: Assignment

Chapter 3: Data types

Lecture 1: Numbers

Lecture 2: Characters

Lecture 3: Logical

Lecture 4: Assignment 1

Lecture 5: Data frame

Lecture 6: List

Lecture 7: Assignment 2

Chapter 4: External Data

Lecture 1: R packages

Lecture 2: Import

Lecture 3: Export

Lecture 4: Assignment

Chapter 5: Control structures

Lecture 1: If-Else

Lecture 2: While

Lecture 3: For

Lecture 4: Assignment

Chapter 6: Functions

Lecture 1: First functions

Lecture 2: More complex functions

Lecture 3: Assignment 1

Lecture 4: Assignment 2

Chapter 7: Graphs

Lecture 1: Line, Scatter charts

Lecture 2: Bar, Pie charts. Graph export

Lecture 3: Assignment

Chapter 8: Additional data types

Lecture 1: Named Vectors

Lecture 2: Matrixes

Lecture 3: Dates and Times

Chapter 9: Data mining

Lecture 1: Summarize – Data frames

Lecture 2: Summarize – Lists

Lecture 3: Assignment 1

Lecture 4: Reshape data – reshape2 package

Lecture 5: Assignment 2

Lecture 6: Reshape data – plyr package

Lecture 7: Assignment 3

Chapter 10: Data Science Project

Lecture 1: Data Science workflow

Lecture 2: Possible project suggestion(data included)

Chapter 11: Additional material

Lecture 1: Useful Cheat Sheets

Lecture 2: Popular R packages

Chapter 12: Final thoughts

Lecture 1: Round Up

Instructors

Mangirdas Adomaitis
Data analyst, Online Advertising specialist

Rating Distribution

1 stars: 8 votes
2 stars: 5 votes
3 stars: 13 votes
4 stars: 20 votes
5 stars: 22 votes

Frequently Asked Questions

How long do I have access to the course materials?

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

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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