Phân tích Không gian & Khoa học Dữ liệu Địa không gian với Python

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 insights from 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 data using Pandas and how to perform spatial 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 Jupyter notebooks for Geographic data analysis