In This course we'll cover data engineering, data cleaning, machine learning in addition sklarn library.
In this course we will cover very important topics that are very important. We use real world dataset and effective methods for data wrangling and cleaning, also Data prepration and visualization as well as statistical analysis.
In second chapter we are going to introduce and work with different machine learning methods, and evaluation methods such as train-test-split and Cross-validation and testing the model using MSE or R2 methods.
Also as deep learning is one of the most important parts of machine learning, I will cover deep learning and neural networks using Tensorflow and keras, which are widely used recently.
This course is completely practical and you will learn by writing codes that is the best way of learning.
