Applied Data Science with R Specialization

Create and access a database instance on the cloud

Compose and execute basic SQL statements - SELECT, INSERT, UPDATE, DELETE, CREATE, DROP

Construct SQL statements to filter, sort, group results, use built-in functions, compose nested queries, access multiple tables

Analyze data from Jupyter using R and SQL by combining SQL and R skills to query real-world datasets

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

Compare and contrast predictive models using simple linear, multiple linear, and polynomial regression methods.

Examine data using descriptive statistics, data grouping, analysis of variance (ANOVA), and correlation statistics.

Evaluate a model for overfitting and underfitting conditions and tune its performance using regularization and grid search.

Create bar charts, histograms, pie charts, scatter plots, line graphs, box plots, and maps using R and related packages.

Design customized charts and plots using annotations, axis titles, text labels, themes, and faceting.

Create maps using the Leaflet package for R.

Create interactive dashboards using the Shiny package for R.

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.