Data, Models and Machine Learning in the Energy Sector

Get started with energy analytics and using data science in the energy sector

What is Energy Analytics? How is data science used in the energy sector, what machine learning and statistical algorithms are the most useful, how can they be applied, and where can you find the data to build your models?

If you've been curious about a sector that's expected to reach $170 billion in five years and is growing exponentially, or if you want to take your skills to the next level and get started using data science in the energy sector, this is the course for you!

We'll walk you through the areas and concepts in how data science is used in energy, identify useful data sources and step through an example problem where we'll explore a dataset from buildings that will allow us to identify opportunities for improved energy accessibility and conservation.

Prerequisites:

1. Access to a computer with QGIS and Python version 3, the Anaconda installation. If you need help installing Python or QGIS, we walk you through the process in our free course "Install Essential Data Science Tools for Clean Technology".


Your Instructor


Gayathri Gopalakrishnan
Gayathri Gopalakrishnan

Gayathri is an award-winning scientist who has been pioneering the integration of clean technology and data science since 2003. She worked in large organizations, including Facebook, Argonne National Laboratory, several Silicon Valley startups and is the recipient of numerous national and international awards. As a scientist, her work has been recognized by the US National Academies of Science and Engineering for innovative environmental research and she was invited by the White House in 2014 to participate in the conference on innovation in clean technology and big data. As an engineer and data scientist, she built the data infrastructure, including data pipelines, dashboards and algorithms, for several startups. She received her PhD in Environmental Engineering from the University of Illinois at Urbana-Champaign and her Bachelors in Civil Engineering from BITS, Pilani, India.



Course Curriculum


  Introduction and Learning Objectives
Available in days
days after you enroll
  The Energy Sector and Data Science Applications
Available in days
days after you enroll
  Data and Data Sources in the Energy Sector
Available in days
days after you enroll
  Models in Data Science and Energy
Available in days
days after you enroll
  Example Problem: Exploring energy use in a building in Colorado, USA
Available in days
days after you enroll
  Wrap Up and Course Feedback
Available in days
days after you enroll

Frequently Asked Questions


When does the course start and finish?
The course is completely self-paced - start and finish it when you choose!
How long do I have access to the course?
How does lifetime access sound? After enrolling, you have unlimited access to this course for as long as you like - across any and all devices you own.
What if I am unhappy with the course?
We would never want you to be unhappy! If you are unsatisfied with your purchase, contact us in the first 30 days and we will give you a full refund.

Get started now!