Spatial Analysis & Geospatial Data Science in Python

Spatial Analysis & Geospatial Data Science in Python, available at $54.99, has an average rating of 4.24, with 53 lectures, based on 529 reviews, and has 52348 subscribers.

You will learn about The course introduces you to the most essential Geopython Libraries Perform Spatial Data analysis with Python Learn the essentials of Geopy,Plotly Library, the workhorse of Geospatial data science in Python. Learn how to visualize Geospatial data in Python (static and interactive maps) Learn how to pre-process geospatial data. Perform Geocoding on Data This course is ideal for individuals who are One who is curious about DataScience It is particularly useful for One who is curious about DataScience.

Enroll now: Spatial Analysis & Geospatial Data Science in Python

Summary

Title: Spatial Analysis & Geospatial Data Science in Python

Price: $54.99

Average Rating: 4.24

Number of Lectures: 53

Number of Published Lectures: 46

Number of Curriculum Items: 53

Number of Published Curriculum Objects: 46

Original Price: ₹1,199

Quality Status: approved

Status: Live

What You Will Learn

The course introduces you to the most essential Geopython Libraries
Perform Spatial Data analysis with Python
Learn the essentials of Geopy,Plotly Library, the workhorse of Geospatial data science in Python.
Learn how to visualize Geospatial data in Python (static and interactive maps)
Learn how to pre-process geospatial data.
Perform Geocoding on Data

Who Should Attend

One who is curious about DataScience

Target Audiences

One who is curious about DataScience

This is the first course that gives hands-on Spatial Data Science / Spatial Analysis Projects using Python..

Student Testimonials:

Excellent course. The narration and presentation of the course are beautiful and simple. The contents contain very clear and interesting explanations. I love this course. Spatial Data Science course in python is entertaining, it contains very clear explanations, every minute you learn something new, it is really exciting. Thank you very much for this wonderful course – Leonardo Guevara

Great course about Spatial analysis using Python! Simple to understand and packed with practical knowledge and real-world examples. Thanks Shan Singh for creating this course! – Gabriel Borja

I was longing to get a kick start on geospatial analysis. This has given me a very clear explanation which I will put into practise – Geoffrey Mogonchi

Geospatial data science is a subset of data science that focuses on spatial data and its unique techniques. In this, we are going to perform spatial analysis and trying to find insightsfrom spatial data. In this course, we lay the foundation for a career in Geospatial Data Science. You will get hands-on Geopy, Plotly , Folium etc.. the workhorse of Geospatial data science Python libraries.

The topics covered in this course widely touch on some of the most used spatial technique in Geospatial data science. We will be learning how to read spatial data , manipulate and process spatial datausing Pandas and how to performspatial operations.. A large portion of the course deals with spatial Visuals like Choropleth, Geographical Scatter plot, Geographical Heatmap, Markers, Geographical HeatMap.. Each video contains a summary of the topic and a walkthrough with code examples in layman terms that will help you learn more effectively.

Who this course is for:

Students who want to become Data Scientist by show-case these Projects on his/her Resume

Students who like to take their first steps in the Geospatial data science career

Python users who are interested in Spatial Data Science

GIS users who are new to python and Jupyternotebooks for Geographic data analysis

Course Curriculum

Chapter 1: Introduction

Lecture 1: About Courses benefits

Lecture 2: Utilize this GOLDEN oppurtunity , QnA section !!

Lecture 3: How to follow this course-Must Watch

Lecture 4: Installation of Anaconda Navigator

Chapter 2: Introduction to Life-Cycle of Spatial Analysis Project

Lecture 1: First Stage : Business Understanding in Real World

Lecture 2: Second Stage : What is ETL (Extract ,Transform,Load) Pipeline ?

Lecture 3: Third Stage : EDA(Exploratory Data Analysis) + Conclusions

Chapter 3: —————– Project 1->> Intro to Zomato use-case —————

Lecture 1: Overview of Problem Statement

Lecture 2: Datasets & Resources

Chapter 4: Perform Data Pre-Processing on Zomato

Lecture 1: Lets Read Data For Spatial Analysis

Lecture 2: Performing basic Data Pre-Processing

Lecture 3: Extract Latitudes & Longitudes of Data

Lecture 4: How to write Structured Queries to extract Latutudes & Longitudes

Chapter 5: Zomato Spatial Analysis

Lecture 1: HeatMap of Restaurants Density

Lecture 2: Performing Marker Cluster Analysis !

Lecture 3: Plotting all the markers of places of Bangalore !

Chapter 6: Data Cleaning in Zomato

Lecture 1: Dealing with missing values

Chapter 7: Advanced Geospatial Analysis

Lecture 1: Analysing Most highest rated restaurants !

Chapter 8: ——————–Project 2–>> Global Warming Analysis

Lecture 1: Datasets & Resources

Lecture 2: Analyse Average Temperature of country

Lecture 3: Analyse Existence of Global Warming

Lecture 4: Visualise Average Temperature in Each Season

Lecture 5: Perform Spatial analysis on Average Temperature of USA States

Lecture 6: Visualise Average temperature of major Indian Cities

Lecture 7: Perform Spatial Analysis on Average temperature of major Indian Cities

Chapter 9: ——————–Project 3 –>> Intro to Covid-19 Project——————–

Lecture 1: Datasets & Resources

Lecture 2: Reading Data of Covid-19

Chapter 10: Spatial Analysis on Covid-19

Lecture 1: Idea behind Choropleth Maps

Lecture 2: Choropleth Map for Confirmed Covid-19 Cases

Lecture 3: Choropleth Map of Particular continent

Lecture 4: Idea behind Geographical Scatter plot

Lecture 5: Geographical Scatter plot for Confirmed Covid-19 Cases

Lecture 6: Plotting of Recovery using Choropleth & Geo Scatter plot

Lecture 7: Plotting of Deaths using Choropleth & Geo Scatter plot

Chapter 11: Covid-19– Interactive Geospatial Data visualisation

Lecture 1: How to extract Latitudes & Longitudes of a location

Lecture 2: Data Preparation For Spatial Analysis

Lecture 3: Fetch Geographical Co-ordinates of a country

Lecture 4: Idea behind Tileset,Raster & Vector Data

Lecture 5: Use-case of Markers

Lecture 6: creating a base map

Lecture 7: Plot Confirmed Cases using Markers

Lecture 8: Plotting of Recovered & Deaths using Markers

Chapter 12: Covid-19– Advanced GeoSpatial Analysis

Lecture 1: Plot Deaths using Marker cluster

Lecture 2: Idea behind Geographic Heatmap

Lecture 3: Geographic HeatMap of Confirmed Cases

Chapter 13: Bonus Section

Lecture 1: Bonus Session

Instructors

Shan Singh
Top Rated & Best-Selling Udemy Instructor , Data Scientist

Rating Distribution

1 stars: 4 votes
2 stars: 14 votes
3 stars: 78 votes
4 stars: 178 votes
5 stars: 256 votes

Frequently Asked Questions

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

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