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Business Business Analytics & Intelligence Data Analysis

Data Analysis with R

Learn data analytics in easy to follow stages for beginners
Rating: 3.8 out of 53.8 (58 ratings)
1,261 students
Created by Mangirdas Adomaitis
Last updated 12/2013
English
English [Auto]
30-Day Money-Back Guarantee

What you'll 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

Requirements

  • Internet connection
  • Computer with Mac, Windows or Linux
  • Desire to master data analysis

Description

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 project will 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 - visualization capabilities. After the course you will be able to produce convincing graphs.

Background behind functional programming will 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 R being fully empowered programming language itself. Main programming concepts presented:

  • Various data types
  • Conditional statements
  • For and While loops

No previous programming knowledge required.

Finally, data mining and 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.

Who this course is for:

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

Course content

12 sections • 44 lectures • 5h 14m total length

  • Preview03:05
  • Preview06:13

  • Preview13:00
  • Getting help
    04:59
  • Preview07:30
  • Preview10:26
  • Preview07:18

  • Numbers
    13:31
  • Characters
    07:31
  • Logical
    09:49
  • Assignment 1
    06:52
  • Data frame
    11:23
  • List
    11:19
  • Assignment 2
    12:50

  • R packages
    07:52
  • Import
    10:28
  • Export
    07:13
  • Assignment
    07:09

  • If-Else
    05:53
  • While
    09:48
  • For
    11:40
  • Assignment
    02:46

  • First functions
    09:21
  • More complex functions
    09:02
  • Assignment 1
    08:13
  • Assignment 2
    02:19

  • Line, Scatter charts
    09:04
  • Bar, Pie charts. Graph export
    12:12
  • Assignment
    08:56

  • Named Vectors
    02:19
  • Matrixes
    04:49
  • Dates and Times
    06:01

  • Summarize - Data frames
    06:36
  • Summarize - Lists
    06:27
  • Assignment 1
    06:00
  • Reshape data - reshape2 package
    08:39
  • Assignment 2
    03:23
  • Reshape data - plyr package
    07:35
  • Assignment 3
    03:14

  • Data Science workflow
    02:11
  • Possible project suggestion(data included)
    2 pages

Instructor

Mangirdas Adomaitis
Data analyst, Online Advertising specialist
Mangirdas Adomaitis
  • 3.5 Instructor Rating
  • 66 Reviews
  • 1,665 Students
  • 2 Courses

Data analyst with more than 3 years of experience.

Employing various tools for data analysis. Always picking the right tool to do the job. I use R package often combining it with Excel, SQL databases and Access on daily basis.

Graduated econometrics from Vilnius University faculty of Mathematics and Informatics. Afterwards I worked as economical forecaster. Currently my position being analyst of online advertising data in leading advertising platform - focusing on insights from large datasets.

I am constantly participating in events/conferences regarding data analysis. Currently interested in open data initiatives - possibilities to open up more government data for public use. Participating in contests of predictive analytics.

Let me know if you have any questions/suggestions regarding data and analysis. You can find my on Google+ or Linkedin.

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