Hello and welcome to the Feature Engineering for Data Science.
My Name is Dr Bright, I hold a PhD in Data Science, am a former Data Scientist at Microsoft and an instructor here at WPI.
My research interest is in Unbasing Artificial Intelligence, Computational Machine Learning and Conversational AI. Recently I do more research on how companies can use Data Science to achieve more results without compromising on the privacy of their customers.
I am the author of the book “How to become a Full Stack Data Scientist” and also “The Data Science Mindset”
I will be your lead instructor in this course.
According to Forbes: "80% of the Data Scientist or Machine Learning engineer's time is spent in cleaning and organizing the data..." and having been a Data Scientist at Microsoft with over 8 years of industry experience, I know how important it is to perform the right feature engineering before building a machine learning model.
Building a machine learning models only takes a few minutes to do but preparing your data in order to build a robust a machine learning model is what differentiates a good and successful Data Scientist from a bad one.
If your feature engineering skills are wrong, your entire Data Science or Machine Learning journey is a waste of time.
In this course, you will not just get to know the industry level strategies to perform Feature engineering but I will also practically demonstrate them for better understanding.
You will get to understand all the industry level strategies to deal with messy data.
I will walk you through step-by-step on each topic explaining each line of code for your understanding.
We will start with:
Introduction To Basic Concepts
How To Properly Deal With Data Types in python
How To Properly Deal With Date and Time In Python
How To Properly Deal With Missing Values
How To Properly Deal With Outliers
How To Properly Deal With Data Imbalance
How To Properly Deal With Data Leakage
How To Properly Deal With Categorical Values
Now after we are done with these foundational concepts, then we will start with:
Then we will move on to
So you see we will cover everything that you need to know when it comes to preparing your data for building a robust machine learning models.
This is a beginner to advanced course so you do not need any prerequisite to start.
If you are really interested in becoming a Data Scientist and be good at your work and valuable in your team, and be successful in your career, then this course is right for you.
Enroll Now !!
