The attached plot shows the level of electricity in Africa. How best can it increase? using smart grids? micrograms?

Since linear and logistic regression are supervised models and are frequently used for exploratory analysis in data mining, would it be accurate to say that the distinction between data mining and machine learning is primarily methodological (discovery vs prediction) rather than algorithmic? Please feel free to share any experiences choosing to use data mining for Energy or any other industry.

A new report has been published and examines why the prices of copper increased in 2025. Copper is a metal which is used a lot in energy. It is essential for electricity systems and it is used in wiring, motors, and many machines and in Renewable energy systems and electric vehicles. Copper is central to electrification: it is used across clean-energy technologies, and grid expansion. If copper gets more expensive, power grids, renewable projects, electric vehicles, and data centres can cost more. Sharing also a slide about copper supply (source: LSEG) ---------------------------- You can access all energy reports by clicking the 'Classroom' menu and navigating to Section 6.2. These reports have been created using the sources below (Financial Times, etc), along with my comments , all written in simple, beginner-friendly language. If you have any questions feel free to ask. By the way these sources below, all request you to subscribe to read their articles. But you don't need to subscribe because you get all the necessary content by simply reading the reports that I publish and which you can find in Classroom section 6.2. Why read these reports: they are very helpful when you find yourself in discussions related to energy or economics. It displays market awareness. How to read these reports: one read is sufficient. They are written very simply. Also, for any questions feel free to message me. [1]: Financial Times: https://www.ft.com/content/29bc6bce-7188-43f2-9f15-6894cf7aa754 [2]: Bloomberg: https://www.bloomberg.com/news/articles/2025-11-07/copper-s-huge-tariff-bet-is-back-as-traders-bid-for-us-supplies? [3]: Wall Street Journal: https://www.wsj.com/finance/commodities-futures/copper-is-2025s-hottest-commodity-c7c21ec4

Massive investments in AI infrastructure. See attached image. a) How will this affect investments in the Energy Sector ? b) How will this affect demand for data scientists/ Software Engineers in Energy Sector? c) What salary ranges in the Energy Sector do we expect e.g. increase/ decrease etc? d) Which regions do you foresee maximum growth ?

In Energy Economics/ Finance the CDF of the standard normal distribution is very popular. It appears in many economic models. If a model involves risk, probability, (like strike prices), the CDF is usually the tool doing the calculation. No need to know all the details e.g. mathematical formulas etc. We just need to interpret it. Also in our code we need to implement it. You can copy-paste it from this file (attached) into any model you develop that includes the CDF. Specifically this is the CDF of the standard normal distribution. CDF = Cumulative Distribution Function. The word "Cumulative" means "accumulating" or "summing up". Attached is a Python file (.ipynb for Jupyter notebook) that implements the Cumulative Distribution Function (CDF) for the standard normal distribution in Python, in two ways. The video explains all we need to know about the CDF for energy economics. Such a question is very frequent in interviews. E.g. to explain what the CDF is, and how to implement it in Python.