Systems Thinking for Software Development

The AI inputs and outputs must be compatible with the existing system and its components. Such compatibility allows complex sub‐systems to work as a single entity. This is an important feature of AI, as it can work autonomously in a complex system, and can continue to improve when following the evolution of the system in which it operates. Designing the system with the AI capability in mind is essential to avoid redesigning the existing product/project, which cannot be amended due to delays with associated cost overruns. Creating an effective system architecture that draws on the experience, intuition, and good judgment of the engineers is key to devising an optimized solution. This chapter addresses how the software essentials set up and use artificial neural networks. The objective is to develop a mathematical tool that is more accurate when reality is complex, uncertain, and difficult to interpret. We apply linear and non‐linear algebraic combinations to describe the various interactions happening in our brain when we solve problems. The settings for Excel are explained in detail, as well as the installation of PyCharm for the examples in Python programming language.