Introduction to Python

Course Highlights

What is Python?

• A versatile programming language used by Data Analysts, Business Analysts, Data Scientists, and Programmers.

• Handles all aspects of data – from storage to security, analytics, and forecasting.

Role of Python in Data Analysis:

• Perform Chapter-to-Chapter Data Analytics with ease using Python modules like Pandas and Numpy.

Role of Python in Programming:

• Design applications and implement business logic.

• Python programming demands strong coding skills and is always in high demand.

Who Can Join?

• Anyone! Training starts from the basics and progresses to advanced analytics and programming with hands-on, real-time projects.

System Requirements for Lab Practice:

• Windows OS

• 8 GB RAM

Course Content

Module 1: Python Fundamentals and Analytics

• Duration: 6 Weeks

·        Pricing : 235USD |20000 INR

·        Discount: 117USD |9999 INR

• Key Topics: 

  • Python Introduction

  • Python Basics

  • Data Types, Type Casting

  • Python Operators

  • Sequences, Strings, Lists, Tuples, Sets, and Dictionaries

  • Conditional Statements and Loops

  • Functions, Modules, Packages, Exception Handling

  • File Handling and Regular Expressions

  • Popular Libraries: Numpy, Matplotlib, Pandas

  • Python Programming and OOP

Module 1: Python Fundamentals & Analytics

Chapter 1: Python Introduction

• Python in Data Analysis

• History of Python

• Python Versions

• Python Implementations

• Python Installations

• Python IDE & Usage

• Print Function

Chapter 2: Python Basics

• Basic Operations in Python

• Python Scripts

• Single & Multiline Statements

• Single & Multi-Line Comments

• Python Internal Architecture

• Compiler vs Interpreter

• Id() Function

Chapter 3: Data Types & Type Casting

• Type()

• Numeric Data Types

• Text Data Types

• Boolean & Binary Types

• Sequence Types: List and Tuple

• Sequence Types: Sets and Dictionaries

• Multi Assignments & Casting

Chapter 4: Python Operators

• Arithmetic Operators

• Assignment Operators

• Comparison Operators

• Logical & Identity Operators

• Membership Operators

• Bitwise Operators

• Operator Precedence

Chapter 5: Sequences & Strings

• Introduction

• Ordering and Indexing Concepts

• Strings: Introduction

• String Slicing

• String Operators

• String Methods

• Escape Sequences

Chapter 6: Lists & Tuples

• Lists: Introduction

• Slicing: Lists

• List Operators

• List Methods

• Tuples: Introduction

• Slicing: Tuples

• Tuple Operators

• Tuple Methods

Chapter 7: Sets & Dictionaries

• Sets: Introduction

• Set Operations

• Set Methods

• Set Functions

• Dictionaries: Introduction

• Dictionary Operations

• Dictionary Methods

Chapter 8: Conditional Statements (If, If-elif-else)

• If-elif-else Statements

• Using Print with If Loops

• Short-Hand If

• Logical Operators in If Loops

• Nested If Loops

• Practical Examples

Chapter 9: Python Loops

• Overview of Python Loops & Real-Time Use Cases

• While Loop 

  • Using Print with While

  • Iterations & Conditions

  • Exit Conditions

• For Loop

• Using Python Constructors

Module 2: Intermediate Python Concepts

Chapter 10: Control Flow Statements

• Break and Continue Statements

Chapter 11: Functions - Part 1

• Introduction to Python Functions

• Function Parameters

Chapter 12: Functions - Part 2 & Lambda Functions

• Lambda Functions

• Break, Continue & Range

• enumerate()

• zip() and Unzipping

• assert Statement and Usage

• Function Arguments:

  • Positional & Default Arguments

  • Keyword & Arbitrary Arguments

  • **kwargs

• Return Keyword

• Recursion()

• Anonymous Functions

• Built-in Functions:

  • Filter()

  • Map()

  • Reduce()

• Examples

Chapter 13: Modules & Packages

• Python Modules

• Variables in Modules

• Built-in Modules

• datetime Module:

  • Date Object Creation

  • strftime() Method

  • datetime.now()

• Creating and Importing Python Packages

• Popular Python Packages

Chapter 14: Exception Handling

• Importance and Usage of try and except

• Using else with try-except

• Working with the finally Block

• Types of Exceptions

• Creating Custom Exception Classes

Chapter 15: File Handling

• File Handling Activities:

  • Modes: r, a, w, x

  • Operations: t, b

• File Operations:

  • Read, Write, Append, Close

• Overwriting Files

• import os

• File Methods: f.open, f.write, f.read, f.close

Chapter 16: Regular Expressions

• Importance of Regex

• Creating Patterns

• Quantifiers and Special Sequences

• Data Validation

• Regex Functions:

  • match(), search(), findall()

  • sub(), split(), compile()

Module 3: Data Analysis & Visualization with Python

Chapter 17: Numpy

• Introduction to NumPy

• Creating Arrays

• Array Properties

• Multi-dimensional Arrays

• Slicing NumPy Arrays

• Statistical Operations on Arrays

• Array Manipulations

Chapter 18: Matplotlib

• Introduction to Data Visualization

• Types of Plots:

  • Simple Plots: Single and Multiple Lines

  • Subplots

  • Bar Graphs & Histograms

  • Pie Charts

  • Scatter Plots

Chapter 19: Pandas – Part 1

• Introduction to Pandas

• Data Structures in Pandas

• Creating DataFrames (Multiple Methods)

• Indexing and Slicing DataFrames

• loc and iloc Concepts

• Sorting DataFrames

• Manipulating DataFrames

• Removing Duplicates

Chapter 20: Pandas – Part 2

• Data Filtering and Conditional Changes

• Handling Missing Data

• Exporting DataFrames to Excel/CSV

• Plotting DataFrames using Matplotlib

• Understanding Correlation: Good vs Bad

Chapter 21: SQL with Python API

• Introduction to DB-API

• Libraries for Different Databases

• Establishing Database Connections

• Executing SQL Queries via Python

• Integrating Pandas and NumPy with SQL

• Plotting DataFrames

Module 2: Python Programming

Chapter 22: Python Classes & Objects

• Introduction to Object-Oriented Programming (OOP)

• Understanding Classes and Objects

• Creating Classes in Python

• self Parameter

• init() Method

• Constructors in Python

• Types of Variables

Chapter 23: Methods & Their Types

• Types of Methods in Python:

  • Instance Methods

  • Class Methods

  • Static Methods

• Parameters of Methods

• Differences Between Method Types

• Overview of OOP Concepts

Chapter 24: OOP Concepts - Inheritance (Part 1)

• Introduction to Inheritance

• Types of Inheritance:

  • Single Inheritance

  • Multiple Inheritance

  • Multilevel Inheritance

  • Hierarchical Inheritance

  • Hybrid Inheritance

• Characteristics of Inheritance

• Declaring Private Members

Chapter 25: OOP Concepts - Inheritance (Part 2)

• Characteristics of Inheritance

• Method Overriding

• super() Keyword and Usage

• Advantages of Inheritance

• Examples and Use Cases

Chapter 26: OOP Concepts - Abstraction & Polymorphism

• Introduction to Abstraction

• Abstract Classes and Methods

• ABC Class (Abstract Base Class)

• Understanding Polymorphism

• Polymorphism at the Class Level

• Polymorphism with Inheritance

Chapter 27: OOP Concepts - Encapsulation & Access Specifiers

• Introduction to Encapsulation

• Data Hiding in Python

• Types of Access Specifiers:

  • Public

  • Protected

  • Private

• Working with Different Access Specifiers

• Practical Use Cases of Encapsulation

Real-Time Projects:

• End-to-End Case Studies covering Python’s applications in Data Analytics, Programming

Benefits of Joining Doyenex

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