Let us start by looking at what Python is. What is Python? The name Python comes from the British comedy group Monty Python. To be precise, Python is a programming language, which we use to make a task easier. It has syntax rules for writing what is considered correct for Python. So we cannot paste or write code consistent of syntax suitable for a different coding language into Python. The programming language is also referred to as a Python interpreter, as this reads the source code intended for the Python language. Furthermore, you see a lot of Monty Python and serpentine references on Python documentations. But what is programming? Programming, it's just a process of giving the computer a set of instructions to perform a task. In every programming language, we have some foundation commands, such as do this and do that, if this is x do y, do a certain action for a certain number of times, keep doing a certain action until certain results are achieved. The process shown on the screen is just an example of where we command the Python language to do a task and it gives a designated end result. But how do we use Python in the finance industry? Python is vastly used for stocks trading and financial data analysis, namely, data modelling, data analysis, visualisation and ticketing trends in the market for potential investment opportunities Python can also be used alongside libraries to manage and maintain client or market data. It can also be used to perform tasks quickly. So for example, if we want to calculate the net present value of a cash flow for different interest rates, we can just create a function that calculates this for us. But why do we use Python when we have Excel to do this? Excel really good with smaller data, but when the data size increases, Excel isn't competent