Data Science: Data Cleaning & Feature Engineering for ML

Real–life data are dirty. This is the reason why preprocessing tasks take approximately 70% of the time in the ML modeling process. Moreover, there is a lack of dedicated courses which deals with this challenging task

Introducing,  Data Science Course: Data Cleaning & Feature Engineering a hardcore completely dedicated course to the most tedious tasks of Machine Learning modeling – Data preprocessing .

if you want to enhance your data preprocessing skills to get better high–performing ML models, then this course is for you!

This course has been designed by experienced Data Scientists will help you to understand the WHYs and HOWs of preprocessing.

I will walk you step–by–step into the process of data preprocessing. With every tutorial, you will develop new skills and improve your understanding of preprocessing  challenging ways to overcome this challenge

It is structured the following way:

Part 1– EDA (exploratory Data Analysis): Get insights into your dataset

Part 2 – Data Cleaning: Clean your data based on insights

Part 3 – Data Manipulation: Generating features, subsetting, working with dates, etc.

Part 4 – Feature Engineering– Get the data ready for modeling

Part 5 – Function writing with Pandas Darframe

Who this course is for:

Anyone who is interested to become efficient in data preprocessing