Cyber-Security-Data-Analysis

1. Introduction

Online learning platforms are getting popularity day by day and hence, generating tons of data and we all know data is the fuel for today's world. We can leverage this data to it's true potential to help the course or the platform to grow and gain more traction by improving the course even further. So, in this report we will try to answer questions like, which device learners use frequently to access the content, from which region more learners are taking up the course, over the various iterations of the course number of enrolled learners are increasing or decreasing.

2. Objective

There are mainly two objectives for this analysis:

2.1. Target Right Audience.

We want to know from which location mostly people are enrolling for the course, what are their employment background and status, their age range etc. This will allow the course provider to target right audience. First, we will try to analyze which continent has most enrolled learners, then we will pin point the country. This way it will be easy to target right locations with precision for advertisement. After this, analysis will be done on learners gender, age range, heights education qualification, employment area and status to understand better which type of people are showing keen interest in the course and hence, personalized ads can be pushed to the right audience.

2.2. Course Improvement.

Once right audience has been singled out, course can be improved to make it more appealing to the potential learners. This can be done in various ways such as, analysing which type of devices (Desktop, Mobile Phone, Tablet) are being used most often than others, is there any trend in usability of a particular device over different runs of the course. Analysis can also be done on sentiments of the learners who have taken the course in the past and peaking into the reasons why they chose to leave the course.

3. Steps to execute this Project.

1. Download/fork/clone the project by clicking here and place all the data files in ./data/ directory or simply unzip the project folder provided via NESS(it already has all the data).
2. (Mandatory step if downloading from git): Create ./data/ and ./cache/ directory in the project folder.
3. Open RStudio
4. alpha2lat.csv is important. It can be downloaded from here and put it into ./data/ directory or if you unzip the file provided via NESS this file will already be there in the ./data/ directory
5. Set working directory by using the command setwd("path/where/you/downloaded/the/project/file") or you can simply click on sessions tab present in the top menu bar then go to set working directory then choose directory (Session > Set Working Directory > Choose directory).
6. Open ./reports/Reports.rmd and run all the chunks by clicking on Run > Run All button in Rstudio.
7. To generate the pdf report click on knit or knit to pdf.

4. Reports

There are two report files:

1. Generated by rmarkdown: This file contains all the analysis and plot description. This file is in ./reports/Reports.pdf
2. 2 page critical report: This file contains summary of the analysis that was done and the experience of using the tools and techniques like ProjectTemplate, Git, CRISP-DM, RMarkdown. This file is in ./reports/Roshan_Pandey_210113925.pdf

5. Important Consideration

This project runs perfectly fine on windows machine by following the steps mentioned in section 3. If want to run on different OS, encoding needs to be changed for text processing.