GIS Modeling with R

GIS Modeling with R, available at $19.99, has an average rating of 4.4, with 11 lectures, based on 5 reviews, and has 39 subscribers.

You will learn about This course is designed for statistical computing, data visualization and GIS. Students use it for Elementary Data Analysis, and data mining to graphing. R is an advanced free programming language that performs various complex statistical analyses and modelling. R in GIS is growing because of its enhanced capabilities for data visualization and you will do practice on real data set. You will learn about the extensive libraries for to generate high-quality graphs and visuals. This course is ideal for individuals who are Research Scholar and those who want to become carrier in the field of data scientist. It is particularly useful for Research Scholar and those who want to become carrier in the field of data scientist.

Enroll now: GIS Modeling with R

Summary

Title: GIS Modeling with R

Price: $19.99

Average Rating: 4.4

Number of Lectures: 11

Number of Published Lectures: 11

Number of Curriculum Items: 11

Number of Published Curriculum Objects: 11

Original Price: $29.99

Quality Status: approved

Status: Live

What You Will Learn

This course is designed for statistical computing, data visualization and GIS. Students use it for Elementary Data Analysis, and data mining to graphing.
R is an advanced free programming language that performs various complex statistical analyses and modelling.
R in GIS is growing because of its enhanced capabilities for data visualization and you will do practice on real data set.
You will learn about the extensive libraries for to generate high-quality graphs and visuals.

Who Should Attend

Research Scholar and those who want to become carrier in the field of data scientist.

Target Audiences

Research Scholar and those who want to become carrier in the field of data scientist.

Analysing data requires a lot of research. But do you know anything that can make it easier? R is used to create projects and models. These projects are dependent on data. Researchers use this programming language to create business models and perform data analysis functions. This course benefits research scholars and those who want to be data scientists. R has been around since 1995, becoming the most popular programming language among data scientists worldwide. This course includes several data packages and functions, making it an attractive programming language for data scientists. R gives an excellent platform for data analysis, data wrangling, data visualisation, machine learning and open source. This course covers traditional statistics to advance statistics and GIS applications, such as models, graph descriptive statistics, mathematical trend modelling and spatial plots. R is designed to be a tool that helps scientists analyse data, and It has many excellent functions that make plots and fit models to data. Because of this, many statisticians learn to use R as if it were a piece of software; they discover which functions accomplish what they need and ignore the rest. This course has been divided into two measures part: the first part is the data visualisation, and the second part is the GIS in R. The course has been done on the actual data set.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Chapter 2: How to install R, RStudio and Descriptive statistics

Lecture 1: R, RStudio Installation, Directory Path and Descriptive Statistics

Chapter 3: Data Visualization by Box Plot

Lecture 1: Data visualization through different box plot

Chapter 4: Data visualization through different bar plot

Lecture 1: Data visualization through different bar plot

Chapter 5: Data visualization through histogram plot

Lecture 1: Data visualization through histogram plot

Chapter 6: Data visualization through regression analyses and QQ plot

Lecture 1: Data visualization through regression analyses and QQ plot

Chapter 7: Shape file import, export and shapefile fetching of any region

Lecture 1: Shape file import, export and shapefile fetching of any region

Chapter 8: Clip and Crop

Lecture 1: Clip and Crop

Chapter 9: Raster Image Stacking

Lecture 1: Raster Image Stacking

Chapter 10: Level plot

Lecture 1: Level plot

Chapter 11: Raster to contour

Lecture 1: Raster to contour

Instructors

Seemab Akhtar
Geology & Geostatistical Programming Fusion

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2 stars: 1 votes
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5 stars: 4 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

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