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I am a Professional R and Python Developer specializing in Data Science and Machine Learning. Apart from my work, I also taught a Data Science course created by myself with several interesting projects. I possess more than 5 years of experience teaching these topics and have the content ready to be taught for Python Programming, Data Science, and Machine Learning. I love to help people in achieving their goals, and my students always find programming very interesting when I teach them now; they are Confident and Professionals in their field. I have a bachelor’s degree in computer science from the University of Southern California and a Masters degree in data science from Maryville University. Besides, I am an eDX certified data scientist.

Data science is an experimental science. With this, my goal is to get you to the point where you can carry out your own experiments as soon as possible. If you are new to R and/or Python, we’ll start by interactively learning the basics with take-home material to aid in your understanding. Next, we will focus on creating and building a workflow that will start simple so you can begin experiments right away. As we work through the program, we will develop this workflow into a robust template that will consume new data set and allow you to carry out all the experiments you wish. My end goal in designing these programs was to create independent scientists.

I am competent in Machine Learning and will focus on the following aspects to equip you with handson coding experience in R and Python.
Machine Learning:
• Concepts of Machine Learning
• Classification Example
• Decision Boundaries
Supervised Learning
• Regression with One Informative Feature
• Binary Classification with Two Informative Feature
• Binary Classification with Non-Linearly Separable Classes
• KNN (with different values of Neighbors)
• KNeighborsRegressor
Linear Models for Regression:
• Linear Regression
• Ridge Regression
• Lasso Regression