Day 1. MODULE: PYTHON ESSENTIALS INTRODUCTION

 What is Python…?

 A Brief history of Python

 Why Should I learn Python…?

Career opportunities after learning Python

Installing Python

Overview of Anaconda and different IDEs

        Day 2.

 How to execute Python program

 Write your first program

 Variables

Different data types

Different Operator

Immutable and Mutable

Object Referencing and Identity

     Day 3.

Strings and escape char

String Formatting ( f string)

formats() for string formatting

Input Statement

Indexing, Slicing & Dicing

List

Day 4

Tuple

Dictionary

Sets

Operators in details

Day 5

IF_ELSE

Basic for loops

for loops

Day 6

while loops

nested loops

infinite loops

loops deep dive

Break statement

Continue statement

Day 7

List

List methods

List Comprehension

List Comprehension with If & Else

Day 8

String, String methods

Tuple, Tuple Methods

Dictionary, Dictionary methods

Tuple, Dictionary Comprehension

Day 9

Function in python

Lambda

MAP

Filter

Reduce

Zip

Accumulate

Decorators

Day 10

math_stats_lib

Datetime

Classes in Date time

RegEx

Day 11

Iterable and Iterator

Generator

Generator vs List

Enumerate

Modules

Day 12

OOPS Concept

Class & Objects

__init__

__str__

Abstraction

Inheritance

Super()

Encapsulation

Polymorphism

__init__ module

Day 13

File Handling in Python

File objects and Modes of file operations

Reading, writing and use of ‘with’ keyword

read(), readline(), readlines(),write(),writeline()

Day 14

⦁    Exception Handling

⦁          Understanding exceptions

⦁          try, except, else and finally

⦁          raising exceptions with: raise, assert

Day 15

logging and debugging

Python Connection with SQL Server

Day 16

NumPy Overview

Properties, Purpose, and Types of ndarray

Class and Attributes of ndarray Object

Basic Operations: Concept and Examples

Initializing arrays: random, ones, zeros

Accessing Array Elements: Indexing, Slicing, Iteration, Indexing with Boolean Arrays

Shape Manipulation

Day 17

Pandas

Day 18

Pandas

Day 19

Data analysis – Visualization using Pandas, Matplotlib, Plotly & Seaborne

Day 20

Python EDA project

Day 21

Getting to Know APIs

SOAP vs REST

Calling Your First API Using Python

We’re going to create a API

Introduction to Git

Useful Git Commands

Day 22

Introduction to Big Data

Apache Spark Introduction

PySpark Introduction

Platforms to use PySpark

Day 23

PySpark Data frame

Reading The Dataset

Checking the Data types of the Column(Schema)

Selecting Columns And Indexing

Check Describe option similar to Pandas

Adding Columns

Dropping columns

Renaming Columns

Dropping Columns

Dropping Rows

Various Parameters in dropping functionalities

Handling Missing values by Mean, Median and Mode

Filter Operation

&,|,==

~

PySpark Group By And Aggregate Functions

Day 24

Pyspark Use Case

End of Course

Thanks

Duration 24 Hours