Quantifying Energy Investments using Data Science

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Price: 189.99$

What is the course about: An electric power system is a network of electrical components deployed to supply, transfer, and use electric power. An example of a power system is the electrical grid that provides power to homes and industries within an extended area. Despite their common components, power systems vary widely both with respect to their design and how they operate. This section introduces some common power system types and briefly explains their operation. This course teaches how to use Data Science for investments in energy. Specifically, we learn how to calculate costs: fixed investment costs, variable investment costs, capital expenditure, and per unit costs. We then learn how to discount these costs – using discount factors and cumulative discount factors. Then, we learn how to identify mutual investments from large investment datasets. We accompany these Python implementations with the theory of energy investments. We also use the Learning curve and S- curve to understand more about the behavior of investment costs – how these costs change with more investment. This is the absolute course for economic and financial studies on investments  (quantitative and theoretical).   Important: 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.