Introduction To Data Science Using R Programming [Video]
-
Free ChapterIntroduction
-
Basics of R tool
-
Basic Data Visualization
-
Advance Data Visualization
- Advanced Data Visualization
- Basic Illustration of ggplot2 package
- Facetting
- Boxplots and Jittered Plots
- Histograms and Frequency Polygons
- Bar Charts and Time Series
- Basic Plot Types
- Case Study for ggplot2 package Scatterplot Encircling
- Surface Plots
- Revealing uncertainity
- Weighted data
- Drawing Maps- Vector Boundries
- Drawing Maps - Point Metadata
- Diamonds data for research
- Dealing with overlapping
- Statistical summaries
- Scatterplot from excel file
- Heatmap and area chart from excel file
- Various bar charts from excel file
-
Leaflet Maps
-
Statistics
- Mean, median and mode
- Linear Regression
- Multiple Regression
- Logistic Regression
- Normal Distribution
- Binomial Distribution
- Poisson Regression
- Analysis of Covariance
- Time Series Analysis
- Case study Time Series from dataset
- Decision Tree
- Implementation of decision tree in Dataset
- Nonlinear Least Square
- Case Study- Random Forest
- Survival Analysis
-
Data Manipulation
Data was once only powerful when it came to making business decisions, but today data plays a more important role and is currently the basis of all modern business functions. This course focuses on helping to breakdown R and the R programming language into simple and easy to understand concepts that cover everything you need to know about how to get started with data science. The course will not only help you learn the R language’s basic syntax, but also the computing environment where you will learn exactly how to import data, organize the data, create charts and graphs, and also export data.
The course will cover topics in-depth such as basic data visualization, advanced data visualization, generating maps using JSON structures, implementation of statistics, data munging/wrangling, data manipulation and so much more!
Let see what this course covers:
- Basic data visualization
- Advanced data visualization
- Generating maps using JSON structures
- Implementation of statistics
- Data munging/wrangling
- Data manipulation - Import/export of data into CSV or Excel format
At the end of this course, you will have mastered exactly how to clean and organize data as well as how to import and export data to R! This is the perfect course for anyone who is looking to make the jump into the world of Data Science.
Style and Approach
The course is designed with a practical approach and easy-to-follow examples to get you a strong start in data science.
- Publication date:
- December 2018
- Publisher
- Packt
- Duration
- 6 hours 59 minutes
- ISBN
- 9781789959840