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Topics of Python language that we must pay attention to!
  • Level: All Levels
  • Duration: 00m
  • Release date: 2022-02-18
  • Author: Dr. Spyros Giannelos .
  • Provider: Udemy

Topics of Python language that we must pay attention to!


Most online courses on Python start teaching the very basics of Python and barely touch on the advanced topics, let alone the really difficult and complicated ones. This course does touch on the more complicated topics of Python development but in a way that even beginners can understand. Python development involves understanding some key topics such as what a metaclass is, what metaclass inheritance is about, how to construct loggers and properly use annotations, how to build classes in a more meaningful way , how to use Polymorphism in Python and many more. Knowing these details can empower you towards developing Python software, whether this software is for Data Analysis, or whether it is a full-blown Machine Learning model, or an Optimization model, a Forecasting model, etc. There is NO other such course anywhere online covering so clearly fuzzy topics such as Metaclass Inheritance! Nobody dares to touch upon them... You will never need to google-search again to find answers on some difficult , complicated Python topics !The great majority of courses on Python are related to Data Analysis and Machine Learning, including Artificial Intelligence. However, these algorithms may yield WRONG results if the underlying Python model that has been developed is inefficiently constructed. And most data scientists do not know how these Python development concepts really work, and as a result, they cannot properly test/check the model. For example, many AI models on Python have metaclass inheritance built-in; and in many cases, these metaclasses are not properly constructed. As a result, they may yield errors that propagate in a very insidious way into the final results, which are wrongly deemed correct.In conclusion, trust me- you really need this course if you want to make a difference as a Python developer, a Data Scientist, a Data Architect/ Engineer, a software engineer, etc.