
WDIS AI-ML Series: Module 2 Lesson 5: Feature Extraction, Feature Selection & Feature Engineering Techniques
How do we use this data that exists in the Data warehouse and/or Data Lake to build Machine Learning (ML) models? However, before we build models, we need to gain a deeper understanding of our data.

WDIS AI-ML Series: Module 2 Lesson 4: Data Collection and Data Preprocessing
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:

WDIS AI-ML Series: Module 2 Lesson 3: Business Objective and Framing of Business Problem into a Machine Learning Model
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.