In the interview , for a company (energy investments / commodities) a panel of 3 interviewers asked me the following during a discussion . Panel: Let's talk about some important Python details. It's ok if you don't remember things. Just an approximate answer will be fine for us. So, in Python, what is the difference between a List comprehension and a Generator expression. In a few words... Correct answer: A generator expression is like a list comprehension, except that it doesn't store the list in memory. Panel: Give some example . Write here in the tablet. Answer: list comprehension: simulated_returns = [price * volatility for price in historical_data] portfolio_value = sum(simulated_returns) generator: simulated_returns = (price * volatility for price in historical_data) portfolio_value = sum(simulated_returns)

A new report on energy trends has been published and can be found by clicking on ‘Classroom’ and navigating to Section 6.2 (see the attached screenshot). You can use this report and the visualisations it includes, in your own projects, work, or studies, without limits. This report explains the progress for the UK’s hydrogen rollout. The report includes diagrams and flowcharts that provide context, and also a list of relevant sources that were used to complete this report. These sources are from the Financial Times, Wall Street Journal, the Economist and Investors Chronicle (all sources are available inside the report). Your subscription in this Skool community gives you access to paywalled energy-economics articles from these publications (Financial Times etc) indirectly through these reports. I have also included some explanations and additional text that explains some details. The text is written in beginner-friendly, easy-to-understand language. Reading these reports can help with interviews, meetings, presentations, networking, and public speaking. Strongly recommended.

A new report on energy trends has been published and can be found by clicking on 'Classroom' and navigating to Section 6.2 (See the attached screenshot). You can use this report and the visualisations it includes, in your own projects, work, or studies, without limits. This report is about Small Nuclear Reactors and current trends by February 2026. Big technology companies like Amazon and Google are racing to find reliable electricity to meet the massive energy demands of new AI data centers. Their primary long-term solution is investing in Small Modular Reactors (SMRs) which are smaller nuclear plants that provide steady "zero-emission" electricity. However, because SMRs take about 8 years to build, these companies are also restarting and upgrading existing nuclear plants to bridge the gap. The report includes lots of diagrams and flowcharts that provide context, and also a list of relevant sources that were used to complete this report. These sources are from the Financial Times, Wall Street Journal, the Economist and Investors Chronicle (all sources are available inside the report). Your subscription in this Skool community gives you access to paywalled energy-economics articles from these publications (Financial Times etc) indirectly through these reports. I have also included some explanations and additional text that explains some details. The text is written in beginner-friendly, easy-to-understand language. Reading these reports is helpful for interviews, panel discussions , presentations, networking, and public speaking. Strongly recommended.

This weekend I visualized how electricity access has changed across West Africa over the last 18 years — and the progress is striking, though uneven. Ghana – Near-universal access. A regional benchmark. Côte d’Ivoire – Strong, consistent growth into the top tier. Nigeria – Big improvement, but population size keeps the gap wide. Senegal – Solid gains driven by energy reforms. Mali & Burkina Faso – Progress, but still constrained by infrastructure. Niger – Improvement visible, yet access remains very low. Sierra Leone & Liberia – Large relative gains from low starting points. West Africa is advancing — but where you live still determines whether you have power. I’m excited to continue exploring how data can drive better decisions in energy, development, and policy. Which country’s progress surprised you the most? Data source: World Bank

Thank you for allowing me here, in your group. It is a pleasure to be here. I might be a bit away from the scientists. However, energy is a business as any other, and therefore, we can´t hide behind the "better future" phrases. The main interest of the market players is either to earn or save money. And that´s exactly where my mission starts.