Python Data Analysis For Data Science & Machine Learning

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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!!

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:

1. Introduction To Basic Concepts

2. Introduction To Data Analysis Tools

3. BONUS: Python Crush Course

4. How To Properly Deal With Python Data Types

5. How To Properly Deal With Date and Time In Python

6. How To Properly Deal With Missing Values

7. How To Properly Deal With Outliers

8. How To Properly Deal With Data Imbalance

9. How To Properly Deal With Data Leakage

10. How To Properly Deal With Categorical Values

11. Beginner To Advanced Data Visualisation

12. Different Feature Engineering Techniques including:

a. Feature Encoding

b. Feature Scaling

c. Feature Transformation

e. Feature Normalisation

13. Automated Feature EDA Tools

a. pandas-profiling

b. Dora

c. Autoviz

e. Sweetviz

14. Automated Feature Engineering

a. RFECV

b. FeatureTools

c. FeatureSelector

e. Autofeat

15. Web scraping

a. Wikipedia

b. online bookstore

c. 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.

ENROLL NOW: https://bit.ly/2MJic2Y