Overview
Who this competition fits
Learners with some ML coursework who want a structured DataCamp-style project sprint.
Read the original official blurb
You work for an energy company in Australia. Your company builds solar panel arrays and then sells the energy they produce to industrial customers. The company wants to expand to the city of Melbourne in the state of Victoria. Prices and demand for electricity change every day. Customers pay for the energy received using a formula based on the local energy market's daily price. Your company's pricing committee wants your team to estimate energy prices for the next 12-18 months to use those prices as the basis for contract negotiations. In addition, the VP of strategy is researching investing in storage capacity (i.e., batteries) as a new source of revenue. The plan is to store some of the energy produced by the solar panels when pricing conditions are unfavorable and sell it by the next day on the open market if the prices are higher. Create a report that covers the following: Scoring notes: [object Object],[object Object],[object Object],[object Object]
Preparation
From registration to a first submission
- 01
Python or R basics
- 02
DataCamp / DataLab workflow
- 03
pandas or tidyverse
Before you commit: Task framing and scoring details live in the notebook; weak validation still hurts rankings.
Source
How this page was assembled
Competition information is structured from the official page. Scores are platform estimates for decision support; official rules take precedence.
- Official competition page
- DataCamp
- Last checked
- Mar 23, 2022