June 08 2021

2021 Python Data Analysis | Data Engineering

2021 Python Data Analysis | Data Engineering
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 321 lectures (24h 55m) | Size: 10.9 GB

Learn Industry Level Data Cleaning, Data Preprocessing, And Advanced Feature Eeering.


All You Need Is Covered!!

Master Data Analysis With Python

Master Bner To Advance Level Data Analytics Techniques

Learn The Latest Data Analytics Skills And Techniques In 2021

Master How To Deal With Messy Data(outliers, missing values, data imbalance, data leakage etc.)

Know How To Deal With Complex Data Cleaning Issues In Python

Learn Automated Modern Tools And Libraries For Professional Data Cleaning And Analysis

Get The Skill Needed To Be Part Of The Top 10% Data Analytics and Data Science

Learn The Best Ways To Prepare Your Data To Build Machine Learning Models

Master Different Techniques Of Dealing With Raw Data

Master The Art Of Visualisation And Data Story Telling

Perform Industry Level Data Eeering

This course is a bner to advance level course with a step-by-step walk through.

If you are a complete bner, you have all the lessons from introduction to python to dealing with complex data issues and building a web-scraper.

If you already have the basics in Python, feel free to skip the Python Crush course at the BONUS session.

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 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 is spent in cleaning and organising the data..."

In this course, you will not just get to know the industry level strats 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 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

Bner To Advanced Data Visualisation

Different Feature Eeering Techniques including:

Feature Encoding

Feature Scaling

Feature Transformation

Feature Normalisation

Automated Feature EDA Tools

pandas-profiling

Dora

Autoviz

Sweetviz

Automated Feature Eeering

RFECV

FeatureTools

FeatureSelector

Autofeat

Web scraping

online bookstore

.com

This course aims to help bners, 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.

This course is from a bner level to advance level, and therefore anyone interested in learning basic to complex Data Analytics techniques for Data Science and Machine Learning is strongly advised to enrol.

Anyone preparing for a career in Data Analytics, Data Science, Business Analytics, Business Intelligence, Machine Learning will highly find this course very useful.

Any student ready to learn how to deal with complex machine learning problems such as imbalance data, data leakage, basic to advanced Feature Eeering etc. is strongly recommended to enrol.

Anyone who is looking for a career transition to Data Analytics, Data Science, Business Analytics, Business Intelligence, Machine Learning role and wants to understand the concepts very well from scratch is recommended to enrol.




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