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Military Geopolitics using Data Analysis

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Military Geopolitics using Data Analysis
Military Geopolitics with Data Science

Python and Data Science for Military Geopolitical Analyses

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Udemy Coupon Code for Military Geopolitics using Data Analysis Course. Python and Data Science for Military Geopolitical Analyses

Created by Research Team led by Dr SGiannelos | 3 hours on-demand video course

Military Geopolitics Course Overview

Military Geopolitics using Data Analysis

This Military Geopolitics using Data Analysis course offers an introduction to the key concepts of military alliances and the tools needed to map them effectively. You will learn how to install Python and essential packages like Geopandas, navigating any challenges that may arise. The Python tutorials will teach you how to create and manipulate geolocation data, design maps of various regions, plot pipelines, update territories, and integrate entities like the European Union into your maps.

In the advanced modules, you will focus on current military alliances such as NATO, CSTO, and SCO. You will gain practical skills in mapping out NATO’s potential expansions into Europe, the Middle East, and Eurasia.

Each lesson is designed to provide a hands-on approach, ensuring you can visualize and plan complex geopolitical scenarios. By the end of the course, you will have a comprehensive understanding of how to design and analyze military alliances, equipping you with valuable skills for strategic planning and analysis.

This course is ideal for anyone looking to deepen their understanding of strategic planning. Whether you’re a student of international relations, a professional in the defense industry, or simply a geopolitics enthusiast, this course provides valuable, hands-on skills that are directly applicable to real-world scenarios.

By mastering the art of designing military alliances on a map, you’ll enhance your analytical abilities, making you more adept at predicting and understanding geopolitical movements. This unique expertise is not only intellectually rewarding but also highly sought after in various fields, offering you a competitive edge in your career or academic pursuits.

There are no prerequisites. The course uses Python, Pyomo and GAMS, assuming no prior experience. It is easy to follow the lectures because the videos are very detailed. Come back here every 6 – 12 months to watch the updated version as the content is regularly updated.

What you’ll learn

  • IMPORTANT: Use this code at checkout (remove spaces) to also download the book “ALGORITHMIC MILITARY GEOPOLITICS”: 1A1EB 88B2FF C9AA5 997D
  • VISIT OFTEN: Content is regularly updated. Visit every 6-12 months to download the updated material!
  • My LinkedIn : /in/spyrosgnl and my website is: www [dot] energycodeschool [dot] com
  • Learn to create and manipulate geolocation data to design maps of various regions.
  • Learn to plot interconnectors and pipelines on maps and update territorial boundaries using Geopandas
  • Learn how to analyze and visualize current military alliances such as NATO, CSTO, and SCO.
  • Learn how to install and set up Python and essential packages like Geopandas for geolocation tasks.
  • Learn to map out potential NATO expansions into Europe, the Middle East, and Eurasia, as geopolitical scenarios.

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Who this course is for

  • Students and professionals in international relations, geopolitics, and defense studies.
  • Individuals with an interest in understanding military alliances and geopolitical strategies.
  • Geopolitics enthusiasts keen on visualizing and analyzing military expansions and territorial changes.
  • Researchers looking to enhance their skills in geolocation and mapping.
  • Analysts aiming to leverage Python and Geopandas for strategic planning.
  • Beginners seeking a practical introduction to data science tools in geopolitics.
  • Experienced professionals wanting to deepen their expertise in military geopolitics.
  • Anyone interested in using data science to understand and visualize complex geopolitical scenarios.

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Taught by Research Team led by Dr SGiannelos

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