Ementorhub

What you'll learn

Write a web scraping program to extract data from an HTML file using HTTP requests and convert the data to a data frame.

Prepare data for modelling by handling missing values, formatting and normalizing data, binning, and turning categorical values into numeric values.

Interpret datawithexploratory data analysis techniques by calculating descriptive statistics, graphing data, and generating correlation statistics.

Build a Shiny app containing a Leaflet map and an interactive dashboard then create a presentation on the project to share with your peers.

Skills you'll gain

R Programming

Regression Analysis

Data Transformation

Data Wrangling

Data Collection

Ggplot2

Exploratory Data Analysis

Shiny (R Package)

Statistical Modeling

Web Scraping

Data Presentation

SQL

Data Cleansing

Data Analysis

Dashboard

Predictive Modeling

Tidyverse (R Package)

Data Manipulation

Data Science

There are 6 modules in this course

For this project, you will assume the role of a Data Scientist who has recently joined an organization and be presented with a challenge that requires data collection, analysis, basic hypothesis testing, visualization, and modeling to be performed on real-world datasets. You will collect and understand data from multiple sources, conduct data wrangling and preparation with Tidyverse, perform exploratory data analysis with SQL, Tidyverse and ggplot2, model data with linear regression, create charts and plots to visualize the data, and build an interactive dashboard. The project will culminate with a presentation of your data analysis report, with an executive summary for the various stakeholders in the organization.

Module 2 - Data Wrangling

Module 3: Performing Exploratory Data Analysis with SQL, Tidyverse & ggplot2

Module 4: Predictive Analysis

Module 5 - Building a R Shiny Dashboard App

Module 6 - Present Your Data-Driven Insights