Ultimate Python Bootcamp For Data Science & Machine Learning

Learn How To Code Python For Data Science, ML & Data Analysis, With 100+ Exercises and 4 Real Life Projects !

What you will learn

☑ Build a Solid Foundation in Data Analysis with Python

☑ You will be able to work with the Pandas Data Structures: Series, DataFrame and Index Objects

☑ Learn hundreds of methods and attributes across numerous pandas objects

☑ You will be able to analyze a large and messy data files

☑ You can prepare real world messy data files for AI and ML

☑ Manipulate data quickly and efficiently

☑ You will learn almost all the Pandas basics necessary to become a ‘Data Analyst’


Hi, dear learning aspirants welcome to “Ultimate Python Bootcamp For Data Science & Machine Learning ” from beginner to advanced level. We love programming. Python is one of the most popular programming languages in today’s technical world. Python offers both object-oriented and structural programming features. Hence, we are interested in data analysis with Pandas in this course.

This course is for those who are ready to take their data analysis skill to the next higher level with the Python data analysis toolkit, i.e. “Pandas”.

This tutorial is designed for beginners and intermediates but that doesn’t mean that we will not talk about the advanced stuff as well. Our approach of teaching in this tutorial is simple and straightforward, no complications are included to make bored Or lose concentration.

In this tutorial, I will be covering all the basic things you’ll need to know about the ‘Pandas’ to become a data analyst or data scientist.

We are adopting a hands-on approach to learn things easily and comfortably. You will enjoy learning as well as the exercises to practice along with the real-life projects (The projects included are the part of large size research-oriented industry projects).

I think it is a wonderful platform and I got a wonderful opportunity to share and gain my technical knowledge with the learning aspirants and data science enthusiasts.

What you will learn:

You will become a specialist in the following things while learning via this course

“Data Analysis With Pandas”.

  • You will be able to analyze a large file
  • Build a Solid Foundation in Data Analysis with Python

After completing the course you will have professional experience on;

  • Pandas Data Structures: Series, DataFrame and Index Objects
  • Essential Functionalities
  • Data Handling
  • Data Pre-processing
  • Data Wrangling
  • Data Grouping
  • Data Aggregation
  • Pivoting
  • Working With Hierarchical Indexing
  • Converting Data Types
  • Time Series Analysis
  • Advanced Pandas Features and much more with hands-on exercises and practice works.




Getting Started

Course Introduction

How To Get Most Out Of This Course

Better To Know These Things

How To Install Python IPython And Jupyter Notebook

How To Install Anaconda For macOS And Linux Users

How To Work With The Jupyter Notebook Part-1

How To Work With The Jupyter Notebook Part-2

Pandas Building Blocks

How To Work With The Tabular Data

How To Read The Documentation In Pandas

Pandas_Data Structures

Theory On Pandas Data Structures

How To Construct The Pandas Series

How To Construct The DataFrame Objects

How To Construct The Pandas Index Objects

Practice Part 01

Practice Part 01 Solution

Data Indexing And Selection

Theory On Data Indexing And Selection

Data Selection In Series Part 1

Data Selection In Series Part 2

Indexers Loc And Iloc In Series

Data Selection In DataFrame Part 1

Data Selection In DataFrame Part 2

Accessing Values Using Loc Iloc And Ix In DataFrame Objects

Practice Part 02

Practice Part 02 Solution

Essential Functionalities

Theory On Essential Functionalities

How To Reindex Pandas Objects

How To Drop Entries From An Axis

Arithmetic And Data Alignment

Arithmetic Methods With Fill Values

Broadcasting In Pandas

Apply And Applymap In Pandas

How To Sort And Rank In Pandas

How To Work With The Duplicated Indices

Summarising And Computing Descriptive Statistics

Unique Values Value Counts And Membership


Practice_Part_03 Solution

Data Handling

Theory On Data Handling

How To Read The Csv Files Part – 1

How To Read The Csv Files Part – 2

How To Read Text Files In Pieces

How To Export Data In Text Format

How To Use Python’s Csv Module

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Practice_Part_04 Solution

Data Cleaning And Preparation

Theory On Data Preprocessing

How To Handle Missing Values

How To Filter The Missing Values

How To Filter The Missing Values Part 2

How To Remove Duplicate Rows And Values

How To Replace The Non Null Values

How To Rename The Axis Labels

How To Descretize And Bin The Data Part – 1

How To Filter And Detect The Outliers

How To Reorder And Select Randomly

Converting The Categorical Variables Into Dummy Variables

How To Use ‘map’ Method

How To Manipulate With Strings

Using Regular Expressions

Working With The Vectorized String Functions


Practice_Part_05 Solution

Data Wrangling

Theory On Data Wrangling

Hierarchical Indexing

Hierarchical Indexing Reordering And Sorting

Summary Statistics By Level

Hierarchical Indexing With DataFrame Columns

How To Merge The Pandas Objects

Merging On Row Index

How To Concatenate Along An Axis

How To Combine With Overlap

How To Reshape And Pivot Data In Pandas


Practice_Part_06 Solution

Data Grouping And Aggregation

Thoery On Data Groupby And Aggregation

Groupby Operation

How To Iterate Over Groupby Object

How To Select Columns In Groupby Method

Grouping Using Dictionaries And Series

Grouping Using Functions And Index Level

Data Aggregation


Practice_Part_07 Solution

Time Series Analysis

Theory On Time Series Analysis

Introduction To Time Series Data Types

How To Convert Between String And Datetime

Time Series Basics With Pandas Objects

Date Ranges Frequencies And Shifting

Date Ranges Frequencies And Shifting Part – 2

Time Zone Handling

Periods And Period Arithmetic’s


Practice_Part_08 Solution

How To Analyse With The Part of Real Life Projects

A Brief Introduction To The Pandas Projects

Project_1 Description

Project_1 Solution Part – 1

Project_1 Solution Part – 2

Project_2 Description

Project_2 Solution

Project_3 Description

Project_3 Solution Part – 1

Project_3 Solution Part – 2

Project Assignment

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