Big Data in Economics / Energy

Big Data in Economics / Energy

What is the course about:

This course focuses on today's reality - the fact that all Datasets are getting Bigger and Bigger.

Big Data is becoming a big issue because they are reaching a point where these datasets cannot be processed.

In this course, we recognize this reality, by presenting a series of methodologies that enable us to deal with Big Data.

We begin with a 6-step methodology applied to a Big Dataset of Electricity Demand. We reduce it as much as possible,

while retaining the important information held in it.

We then proceed to create a Dummy Big-Dataset. This is necessary because many times companies prefer to conceal some information from inside their datasets.

Also, we proceed to select important information from within Big Data, and present a number of techniques to do so.

We also learn how to transition from small data , to big data, in an  accurate way.

*** updating

Who:

I am a research fellow at Imperial College London, and I have been part of high-tech projects at the intersection of Academia & Industry for over 10 years, prior to, during & after my Ph.D. I am also the founder of the giannelos dot com program in data science.

• Doctor of Philosophy (Ph.D.) in Analytics & Mathematical Optimization applied to Energy Investments, from Imperial College London, and Masters of Engineering (M. Eng.) in Power Systems and Economics.

Special Acknowledgements:

To Himalaya Bir Shrestha, energy system analyst, who has been contributing to the development of Python scripts for this course as well as to Medium. 

Important:

• Prerequisites: The course Data Science Code that 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.
  

Big Data is everywhere in Finance, Energy, Machine Learning, A.I. etc. In this course we address them in various ways.

Url: View Details

What you will learn

• Big Data Methodology - Maximize Data Reduction & Minimize Loss of information. Application: Electricity demand
• Step-by-step: MATLAB, Excel, Python
• Creating a dummy Big Dataset

Rating: 4.94444

Level: All Levels

Duration: 6.5 hours

Instructor: Dr. Giannelos