Learning Data Analysis with R

4.7( 3 REVIEWS )
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£199 £49 (inc. VAT)
  • 365 Days
  • Beginner and Intermediate
  • Course Certificate
  • Wishlist
  • 07Guided Learning Hours
  • Course Material
  • 15 Number of Modules
  • Exam Included


R is a statistical computing language that is widely used in data analysis and statistics and is a highly regarded skill that is desired in candidates aspiring to get into the industry. If you too are an individual aspiring to or already in the data analysis or statistics industry looking to improve your skills in the area, this course in data analysis with R might just be the one you were looking for. This course is set to thoroughly educate you on R to use it effectively in your data analysis activities.

Data is the foundation in data analysis, data science and statistics, and this course will start off by teaching you how to import data from tables, FTP sites and read.lines, along with guidelines on how to clean the downloaded data to detect and rectify inaccurate data. You will then move learn about vector and raster data and on how to import, export and manipulate it in R as per your requirements. The descriptive aspects of statistics such as the dataset, spread, data plots, multivariate data and outliers will also be duly covered through this course.

Information has to be presented in an effective way that provides maximum data on the subject looked for. Many data visualization methods exist for effective information representation and this course is set to disclose many of these methods, with special attention to spatial data visualization. This course will also provide you an opportunity to improve your data analysis skills by examining the point pattern, cluster and time series analysis. By the end of this course, you will have an outstanding knowledge on R to tremendously improve the quality of your data analysis.

Why study at Global Edulink?

Global Edulink offers the most convenient path to gain recognised skills and training that will give you the opportunity to put into practice your knowledge and expertise in an IT or corporate environment. You can study at your own pace at Global Edulink and you will be provided with all the necessary material, tutorials, qualified course instructor, narrated e-learning modules and free resources which include Free CV writing pack, free career support and course demo to make your learning experience more enriching and rewarding.


  • Access Duration
  • Who is this course aimed at?
  • Entry Requirements
  • Method Of Assessment
  • Certification
  • Career Path
  • Other benefits

The course will be directly delivered to you, and you have 12 months access to the online learning platform from the date you joined the course.  The course is self-paced and you can complete it in stages, revisiting the lectures at any time.

This course is aimed at individuals aspiring to or already in the data science, data analysis or statistics field.
  • Learners must be age 16 or over and should have basic understanding of the English Language, numeracy, literacy and ICT.
  • Some knowledge or experience in R and programming is preferred

The course is assessed online with a final, multiple-choice test, which is marked automatically. You will know instantly whether you have passed the course.

Those who pass this test will get a certificate in Learning Data Analysis with R

This certificate will enhance your resume for a number of jobs in the job market. You can also use this certificate to study further in the area or to make substantial progress in your career. Listed below are few of the jobs this certificate will benefit you in, along with the average UK salary per annum according to https://www.payscale.com/career-path-planner,

  • Data analyst – £25,972 per annum
  • Data scientist – £35,226 per annum
  • Data Manager – £29,986 per annum
  • Statistician – £31,231 per annum
  • High-quality e-learning study materials and mock exams.
  • Tutorials/materials from the industry leading experts.
  • 24/7 Access to the Learning Portal.
  • The benefit of applying for TOTUM extra Discount Card.
  • Recognised Accredited Qualification.
  • Excellent customer service and administrative support

Key Features

Gain an Accredited UK Qualification

Access to Excellent Quality Study Materials

Learners will be Eligible for TOTUM Discount Card

Personalised Learning Experience

UK Register of Learning Providers Reg No : 10053842

Support by Phone, Live Chat, and Email

Course Curriculum

Getting Started
Online Training User Manual 00:00:00
E Certificate Download Guide 00:00:00
Code Files
Learning Data Analysis with R – Code Files 00:00:00
Section 1: Importing Data in Table Format
1.1. The Course Overview 00:00:00
1.2. Importing Data from Tables (read.table) 00:00:00
1.3. Downloading Open Data from FTP Sites 00:00:00
1.4. Fixed-Width Format 00:00:00
1.5. Importing with read.lines (The Last Resort) 00:00:00
1.6. Cleaning Your Data 00:00:00
Section 2: Handling the Temporal Component
2.1. Loading the Required Packages 00:00:00
2.2. Importing Vector Data (ESRI shp and GeoJSON) 00:00:00
2.3. Transforming from data.frame to SpatialPointsDataFrame 00:00:00
2.4. Understanding Projections 00:00:00
2.5. Basic time/dates formats 00:00:00
Section 3: Importing Raster Data
3.1. Introducing the Raster Format 00:00:00
3.2. Reading Raster Data in NetCDF 00:00:00
3.3. Mosaicking 00:00:00
3.4. Stacking to Include the Temporal Component 00:00:00
Section 4: Exporting Data
4.1. Exporting Data in Tables 00:00:00
4.2. Exporting Vector Data (ESRI shp File) 00:00:00
4.3. Exporting Rasters in Various Formats (GeoTIFF, ASCII Grids) 00:00:00
4.4. Exporting Data for WebGIS Systems (GeoJSON, KML) 00:00:00
Section 5: Descriptive Statistics
5.1. Preparing the Dataset 00:00:00
5.2. Measuring Spread (Standard Deviation and Standard Distance) 00:00:00
5.3. Understanding Your Data with Plots 00:00:00
5.4. Plotting for Multivariate Data 00:00:00
5.5. Finding Outliers 00:00:00
Section 6: Manipulating Vector Data
6.1. Introduction 00:00:00
6.2. Re-Projecting Your Data 00:00:00
6.3. Intersection 00:00:00
6.4. Buffer and Distance 00:00:00
6.5. Union and Overlay 00:00:00
Section 7: Manipulating Raster Data
7.1. Introduction 00:00:00
7.2. Converting Vector/Table Data into Raster 00:00:00
7.3. Subsetting and Selection 00:00:00
7.4. Filtering 00:00:00
7.5. Raster Calculator 00:00:00
Section 8: Visualizing Spatial Data
8.1. Plotting Basics 00:00:00
8.2. Adding Layers 00:00:00
8.3. Color Scale 00:00:00
8.4. Creating Multivariate Plots 00:00:00
8.5. Handling the Temporal Component 00:00:00
Section 9: Interactive Maps
9.1. Introduction 00:00:00
9.2. Plotting Vector Data on Google Maps 00:00:00
9.3. Adding Layers 00:00:00
9.4. Plotting Raster Data on Google Maps 00:00:00
9.5. Using Leaflet to Plot on Open Street Maps 00:00:00
Section 10: Creating Global Economic Maps With Open Data
10.1. Introduction 00:00:00
10.2. Importing Data from the World Bank 00:00:00
10.3. Adding Geocoding Information 00:00:00
10.4. Concluding Remarks 00:00:00
Section 11: Point Pattern Analysis of Crime in the UK
11.1. Theoretical Background 00:00:00
11.2. Introduction 00:00:00
11.3. Intensity and Density 00:00:00
11.4. Spatial Distribution 00:00:00
11.5. Modelling 00:00:00
Section 12: Cluster Analysis of Earthquake Data
12.1. Theoretical Background 00:00:00
12.2. Data Preparation 00:00:00
12.3. K-Means Clustering 00:00:00
12.4. Optimal Number of Clusters 00:00:00
12.5. Hierarchical Clustering 00:00:00
12.6. Concluding 00:00:00
Section 13: Time Series Analysis of Wind Speed Data
13.1. Theoretical Background 00:00:00
13.2. Reading Time-Series in R 00:00:00
13.3. Subsetting and Temporal Functions 00:00:00
13.4. Decomposition and Correlation 00:00:00
13.5. Forecasting 00:00:00
Section 14: Geostatistics
14.1. Theoretical Background 00:00:00
14.2. Data Preparation 00:00:00
14.3. Mapping with Deterministic Estimators 00:00:00
14.4. Analyzing Trend and Checking Normality 00:00:00
14.5. Variogram Analysis 00:00:00
14.6. Mapping with kriging 00:00:00
Section 15: Regression and Statistical Learning
15.1. Theoretical Background 00:00:00
15.2. Dataset 00:00:00
15.3. Linear Regression 00:00:00
15.4. Regression Trees 00:00:00
15.5. Support Vector Machines 00:00:00
Mock Exam
Mock Exam : Learning Data Analysis with R 00:40:00
Exam : Learning Data Analysis with R 00:40:00

Students feedback


Avarage rating (3)
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    J D

    Jayden Duncan

    June 05, 2019 - 11:37am

    A very enjoyable course. Even if you are new to R, it is not intimidating. The course has been simplified to suit all levels of learners.

    C S

    Chase Stewart

    May 09, 2019 - 10:45am

    The course offered an overview of R and touched briefly on concepts and high-level theory. It doesn’t move fast, so it allows you to get comfortable with the speed. It is high-quality and practical content.

    D J

    Dakota Jordan

    April 15, 2019 - 9:23am

    This was the first course I took in analytics. While I was surprised to learn it was not at a beginner level, I decided to study it. The course does not focus too much on the basics, but that was fine with me. The course takes you to the next level of R but it was well-paced and explained very well.

Buy Now
£199 £49 (inc. VAT)
  • 365 Days
  • Beginner and Intermediate
  • Course Certificate
  • Wishlist
  • 07Guided Learning Hours
  • Course Material
  • 15 Number of Modules
  • Exam Included
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