Technology and science fascinate us, there are innovations and discoveries that push the boundaries of science every year and has made artificial intelligence a concept we are much familiar to these days. Although more of the usage of applied AI (applied machine learning), which obviously requires skills, resources, and knowledge going beyond data science present a challenge usually absent in the academic and scientific research settings.

Machine learning and artificial intelligence are fast becoming common in many organizations today. Owing to their capability to turn around fortunes for businesses, many organizations have implemented machine learning projects in different areas of their operations. When it comes to estimating the cost of machine learning projects, many enterprises often face difficulties. However, this should not be the case. Estimating the cost of such a project should be straightforward if done procedurally. In a world where technology is highly in demand and dynamic, requirements often change midway through the project. This leads to development and feature changes, integration issues, and many others.

Cities worldwide are growing and the rising population is forcing them to reconfigure themselves for the purpose of sustainability in the future and enhancing the quality of life for every dweller.  This growth in population means taking advantage of renewable sources of energy, enhancing efficiency, and scaling up the use of electric transport modes. With the arrival of machine learning and artificial intelligence (AI), we are seeing new tools for ensuring efficiency in using resources around our cities. The growth of computing power in recent years, the availability of data, and the rise of effective algorithms have made AI one of the most valuable technologies in the 21^st century in managing various aspects within cities.