It is an initial phase of any data science project, is a critical step in the data analysis process, used to understand the underlying structure, patterns, and relationships within a dataset before formal modeling or hypothesis testing. It's like detective work, where you delve into your data to understand its characteristics, identify patterns, and uncover potential insights.

Not many companies invest enough in data as much as they do in Data Science. Albeit the realization is growing that to be seen as an ‘AI-first’ company, one needs to establish itself as a ‘Data-first’ company. The biggest challenge In this section we will give an overview of what end-to-end data processing looks like from the viewpoint of a data science project:

In this lesson, we will learn to do it the right way and we will also introduce the concept of PRD - Product Requirement Document, a wildly misused or unused tool that is needed to align people on a common mission.

Before we go and start understanding various machine learning algorithms, let us discuss the end-to-end framework of data science deployment. We will talk about many interesting concepts and walk you through who should own which part and what should be the expected output of each part.

An objective function in the context of machine learning is a mathematical function that quantifies how well the algorithm is performing at a particular task.

Now before we jump onto the next section, let us check our understanding of Module 1. Take the Module 1 Quiz by clicking on the button on the right side.You will see your scores and right answers upon completion of the quiz.