This repository contains all the course materials for Python Data Analysis For Data Science and Machine Learning course on UDEMY
Learn Industry Level Data Cleaning, Data Preprocessing, And Advanced Feature Engineering. All You Need Is Covered!!
Course Link: https://bit.ly/2YF7hKi
Interested in the field of Data Analytics, Business Analytics, Data Science or Machine Learning?
Do you want to know the best ways to clean data and derive useful insights from it?
Do you want to save time and easily perform Exploratory Data Analysis(EDA)?
Then this course is for you!!
According to Forbes: "60% of the Data Scientist's or Data Analyst's time is spent in cleaning and organising the data..."
In this course, you will not just get to know the industry level strategies but also I will practically demonstrate them for better understanding.
This course has been practically and carefully designed by industry experts to reflect the real-world scenario of working with messy data.
This course will help you learn complex Data Analytic techniques and concepts for easier understanding and data manipulations.
We will walk you through step-by-step on each topic explaining each line of code for your understanding.
This course has been structured in the following form:
Introduction To Basic Concepts
Introduction To Data Analysis Tools
BONUS: Python Crush Course
How To Properly Deal With Python Data Types
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
Beginner To Advanced Data Visualisation
Different Feature Engineering Techniques including:
Feature Encoding
Feature Scaling
Feature Transformation
Feature Normalisation
Automated Feature EDA Tools
pandas-profiling
Dora
Autoviz
Sweetviz
Automated Feature Engineering
RFECV
FeatureTools
FeatureSelector
Autofeat
Web scraping
Wikipedia
online bookstore
Amazon .com
This course aims to help beginners, as well as an intermediate data analyst, students, business analyst, data science, and machine learning enthusiasts, master the foundations of confidently working with data in the real world.