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Climate Change Economics using Data Science

Climate Change Economics using Data Science
Climate Change Economics using Data Science

Climate Change Economics using Data Science

Economics on Climate Change

What you’ll learn

Climate Change Economics using Data Science

  • Economics of Climate Change
  • Evaluating the effect of different measures in tackling climate change
  • Evaluating the Climate-change caused immigration, using Data Science
  • Tracking the carbon emissions intensity
  • and many more

Requirements

  • The only prerequisite is to take the first course of the “Giannelli dot com” program, which is the course “Data Science Code that appears all the time at the workplace”.

Description

What is the course about:

The course teaches that part of Object Oriented Programming that is needed in Data Science. And we learn how to use it and when.

We start with classes and data classes and we learn how and when to use data classes along with custom objects. We also go through lambda functions and use them with lists and dictionaries of custom objects.

We go through real-world examples and understand concepts such as metaclasses, superclasses, inheritance, and polymorphism.

This is a necessary course for building efficient Data Science applications.

Important:

  • Prerequisites: The course Data Science Code appears all the time at Workplace.
  • Every detail is explained, so that you won’t have to search online, or guess. In the end, you will feel confident in your knowledge and skills.
  • We start from scratch so that you do not need to have done any preparatory work in advance at all.  Just follow what is shown on screen, because we go slowly and explain everything in detail.

Who this course is for:

  • Entrepreneurs
  • Economists
  • Quants
  • Members of the highly googled Giannelli dot com program
  • Investment Bankers
  • Academics, Ph.D. Students, MSc Students, Undergrads
  • Postgraduate and Ph.D. students.
  • Data Scientists
  • Energy professionals (investment planning, power system analysis)
  • Software Engineers
  • Finance professionals

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