Udemy - Creating Smart Maps with Python and Leaflet Windows Version

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Udemy - Creating Smart Maps with Python and Leaflet Windows Version (Size: 1.3 GB)
  1. Adding the Leaflet Config Code.mp4 26 MB
  1. Adding the Leaflet Config Code.srt 4.7 KB
  1. Adding the settings.py Code.mp4 38 MB
  1. Adding the settings.py Code.srt 7.8 KB
  1. Creating a Python Virtual Environment.mp4 27.2 MB
  1. Creating a Python Virtual Environment.srt 3.8 KB
  1. Creating a Spatial Database.mp4 23.1 MB
  1. Creating a Spatial Database.srt 4.7 KB
  1. Creating the Dataset API Endpoints.mp4 79.7 MB
  1. Creating the Dataset API Endpoints.srt 11.6 KB
  1. Installing Python on Windows.mp4 8.8 MB
  1. Installing Python on Windows.srt 1.5 KB
  1. Introduction.mp4 111 MB
  1. Introduction.srt 7.9 KB
  1. Source Code.html 204.8 B
  2. Adding the Static Files.mp4 22.5 MB
  2. Adding the Static Files.srt 3.2 KB
  2. Creating a Django Admin User.mp4 9.8 MB
  2. Creating a Django Admin User.srt 2.3 KB
  2. Displaying Data on the Map.mp4 69.5 MB
  2. Displaying Data on the Map.srt 9.2 KB
  2. Installing PostgreSQL and PostGIS on Windows.mp4 44.2 MB
  2. Installing PostgreSQL and PostGIS on Windows.srt 6 KB
  2. Installing and Configuring GeoDjango and GDAL on Windows Part 1.mp4 45.5 MB
  2. Installing and Configuring GeoDjango and GDAL on Windows Part 1.srt 6.6 KB
  3. Creating the Layout Page Part 1.mp4 11.3 MB
  3. Creating the Layout Page Part 1.srt 2.3 KB
  3. Creating the Legend.mp4 93.7 MB
  3. Creating the Legend.srt 11.7 KB
  3. Creating the Model.mp4 28.9 MB
  3. Creating the Model.srt 6.9 KB
  3. Installing and Configuring GeoDjango and GDAL on Windows Part 2.mp4 14.6 MB
  3. Installing and Configuring GeoDjango and GDAL on Windows Part 2.srt 1.7 KB
  4. Creating the Bar Chart Legend.mp4 35 MB
  4. Creating the Bar Chart Legend.srt 4.1 KB
  4. Creating the Layout Page Part 2.mp4 130.1 MB
  4. Creating the Layout Page Part 2.srt 21.3 KB
  4. Downloading the Sample Dataset.mp4 23.3 MB
  4. Downloading the Sample Dataset.srt 4.2 KB
  4. Installing Visual Studio Code IDE.mp4 11.5 MB
  4. Installing Visual Studio Code IDE.srt 1.5 KB
  5. Creating a Django Base Application.mp4 20.9 MB
  5. Creating a Django Base Application.srt 3.1 KB
  5. Creating the Bar Chart.mp4 176.2 MB
  5. Creating the Bar Chart.srt 14.4 KB
  5. Creating the GeoAdmin and Testing the Spatial Back-end.mp4 62 MB
  5. Creating the GeoAdmin and Testing the Spatial Back-end.srt 12 KB
  5. Creating the Index Page.mp4 24.1 MB
  5. Creating the Index Page.srt 5.9 KB
  6. Creating the Index View.mp4 45.1 MB
  6. Creating the Index View.srt 8.7 KB
  6. Testing the Django Installation.mp4 19.5 MB
  6. Testing the Django Installation.srt 3.3 KB
  7. Modifying and Styling the Index Page.mp4 94.8 MB
  7. Modifying and Styling the Index Page.srt 10.6 KB
  Bonus Resources.txt 307.2 B
  Get Bonus Downloads Here.url 204.8 B
  ▲ 57 total files

Description


Creating Smart Maps with Python and Leaflet Windows Version



MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 28 lectures (3h 18m) | Size: 1.08 GB
Learn GeoDjango, by building a Web GIS Application
What you'll learn:
Be able to create a Full-stack web GIS application from scratch
Build a Full-stack Django Application
Be able to use a 3rd party JavaScript charting library
Geodjango Application Development for Windows
PostGIS for Windows

Requirements
A basic knowledge of Python, Javascript, and GIS
A Windows operating system
Some coding experience

Description
Welcome to the Creating Smart Maps with Python and Leaflet Windows Version course. We'll be building a python GIS application from scratch using a variety of open source technologies. The purpose of this course and many more to follow, is to learn to create geospatial analytics and convert it into a functional application.

In our use case we will be working with residential water consumption data and we will be applying data processing techniques to extract transform and load the data into our spatial database. Once we have processed and cleaned the data, we will use it as a data source for building our GeoDjango Web Map Application.

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