Beginners Data Analysis and Visualization with R Programming 2021

[mitsumi]

Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | VTT | Size: 2.26 GB | Duration: 4h 29m

1: Introduction

The course has a capstone project at the end, this project walks students through the entire workflow of data handling using the RStudio and performs analytics on the dataset along with the visualizations. This demonstrates the basics learned by the students in the former sections. The solution of the project is provided but it is recommended that the student first try to solve the problem on their own and then move to the solution. Below is the description of the project:

The project is based on the very famous Titanic dataset. Students need to import the dataset provided in the resource section. And prepare it for analysis. This involves analysis based on gender, survived passengers, their siblings traveling with them on board, passenger ages and much more. Once students have prepared the data they can move to perform the visualization on these analytics.

2: What action the student must take in order to complete the project

Students should watch all course sections in the order as the course is designed. Students must install R and RStudio and complete all labs performed in each section themselves.

3: What skills they need to apply to complete the project.

Students must be able to learn the concepts explained in the course. To be completely able to solve the project problems, a student must have knowledge of importing data, data frames, converting dataframe to vectors, matrix. Manipulating the vectors, arrays, matrix in R language programming. Students must also know how to perform basic arithmetic and statistics on the dataset. All of these concepts are explained in resection 1 to 7, which students can learn first, and then attempt the capstone project.

4: How students can share the project with other students on the platform in order to get feedback.

Students can share the project files using either their git repositories link or by uploading the code files to the desired shared storage location for easy access.

5: Resources:

All the resources for this project are attached as working files.

Screenshots

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