Python Fundamentals for Beginners

Great Learning

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3 Hours

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Medium of instructions English	Mode of learning Self study	Mode of Delivery Video and Text Based

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Free

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The syllabus

Module 1 - Importance and Applications of Programming Languages

Industry Applications and Automation

Define programming paradigms and industry applications. Explore how software engineering automates tasks, processes data, and scales operations across domains like web development and data science.

Module 2 - Variables in Programming

Memory Allocation and Data Storage

Understand memory allocation in computer science. Define variables as named storage locations in system memory used to store, retrieve, and manipulate data dynamically during program execution.

Module 3 - Decision Making Statements

Conditional Decision-Making Statements

Control program execution paths using conditional statements. Implement if, else-if, and else logic to execute specific code blocks based on dynamic Boolean conditions and logical evaluations.

Module 4 - Iteration Structures

Looping and Code Automation

Automate repetitive tasks using Iteration Structures. Implement loops to execute code blocks continuously until a specific exit condition or counter threshold is met.

Module 5 - Modular Programming:

Functions and Code Reusability

Write modular, reusable code using Functions. Define function signatures, pass arguments, and return values to break down complex algorithms into manageable sub-routines.

Module 6 - Object Oriented Programming Concepts

Classes and Objects

Model real-world entities using Object-Oriented Programming (OOP). Define Classes as architectural blueprints and instantiate Objects with specific attributes (properties) and methods (behaviors).

Module 7 - Algorithm Design and Computational Problem Solving

Formulate step-by-step computational solutions using the Algorithmic Approach. Design logical sequences to process inputs, optimize mathematical operations, and generate accurate outputs for complex problems.

Module 8 - Python Setup:

PyCharm, Anaconda, and Jupyter Installation

Configure a professional Python development environment. Install the Python interpreter, set up the PyCharm IDE, deploy Anaconda for package management, and launch Jupyter Notebooks.

Module 9 -Interactive Coding with the Jupyter Notebook Environment

Execute Python scripts interactively using Jupyter Notebook. Navigate the browser-based REPL (Read-Eval-Print Loop) environment for data analysis, code testing, and inline visualization.

Module 10 -Python Data Types:

Integers, Floats, Strings, and Booleans

Declare and initialize Python variables. Manage system memory dynamically by assigning primitive data types including integers (int), floating-point numbers (float), text (str), and logical values (bool).

Module 11 -Python Operators:

Arithmetic, Relational, and Logical

Execute programmatic calculations using Python Operators. Apply Arithmetic operators for math, Relational operators for value comparison, and Logical operators (AND, OR, NOT) for complex Boolean evaluations.

Module 12 - Python Lexical Structure:

Tokens, Keywords, and Identifiers

Analyze the lexical components of Python syntax. Identify standard Python Tokens including reserved Keywords, user-defined Identifiers, hardcoded Literals, and functional Operators.

Module 13 - Strings in Python

This module begins with an introduction to Python strings. You will learn to implement Python strings in 3 different ways in the Jupyter notebook. You will also be familiarized with some inbuilt string functions of Python.

Module 14 - Data Structures in Python

Data structures in Python include tuple, list, dictionary, set, conditional statement, and looping statement. This section shall enrich your knowledge on each of these with the code snippets in Jupyter Notebook.

Module 15 - If Statement in Python

This section explains why and when to use “if-else” statements and demonstrates how to use them with an example.

Module 16 - Looping Statements in Python

This section explains why and when to use “loop” statements and demonstrates how to use them with an example.

Module 17 - Functions in Python

This section shall define what functions are in Python and demonstrate how a block of code performs a targeted action with an ATM working example.

Module 18 - Intro to Object Oriented Programming in Python

Module 19 - Intro to Object Oriented Programming in Python

This section shall begin by introducing you to OOPs, then continues by demonstrating how to create classes, adding parameters into the method, and constructors. You will then learn the concept of inheritance and understand its different types later in this section.

Module 20 - Creating Python Classes:

Blueprint Initialization

Define a Python Class as a structural blueprint. Use the 'class' keyword to encapsulate related variables (attributes) and functions (methods) into a single, cohesive software entity.

Module 21 - Python Class Methods and the 'self' Parameter

Define interactive class behaviors using Python Methods. Pass parameters into methods and utilize the mandatory 'self' parameter to access and modify instance-specific attributes.

Module 22 -Python Constructors:

The initDunder Method

Initialize object state upon instantiation using Python Constructors. Define the init dunder method to automatically assign initial values to instance attributes when a new object is created.

Module 23 - Python Inheritance:

Parent and Child Class Relationships

Promote code reusability using Python Inheritance. Create Child classes that inherit attributes and methods from a Parent (Base) class to extend application functionality efficiently without redundant coding.

Module 24 - Advanced Inheritance:

Single, Multiple, and Multi-Level

Architect complex class hierarchies. Implement Single, Multiple, Multi-Level, and Hybrid inheritance models in Python to establish sophisticated parent-child relationship chains and Method Resolution Orders (MRO).

Instructors

Mr Bharani Akella
Data Scientist
Great Learning

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Python Fundamentals for Beginners

Beginner

Online

3 Hours

Free

Quick Facts

Course and certificate fees

Type of course

Free

certificate availability

certificate providing authority

The syllabus

Module 1 - Importance and Applications of Programming Languages

Industry Applications and Automation

Module 2 - Variables in Programming

Memory Allocation and Data Storage

Module 3 - Decision Making Statements

Conditional Decision-Making Statements

Module 4 - Iteration Structures

Looping and Code Automation

Module 5 - Modular Programming:

Functions and Code Reusability

Module 6 - Object Oriented Programming Concepts

Classes and Objects

Module 7 - Algorithm Design and Computational Problem Solving

Module 8 - Python Setup:

PyCharm, Anaconda, and Jupyter Installation

Module 9 -Interactive Coding with the Jupyter Notebook Environment

Module 10 -Python Data Types:

Integers, Floats, Strings, and Booleans

Module 11 -Python Operators:

Arithmetic, Relational, and Logical

Module 12 - Python Lexical Structure:

Tokens, Keywords, and Identifiers

Module 13 - Strings in Python

Module 14 - Data Structures in Python

Module 15 - If Statement in Python

Module 16 - Looping Statements in Python

Module 17 - Functions in Python

Module 18 - Intro to Object Oriented Programming in Python

Module 19 - Intro to Object Oriented Programming in Python

Module 20 - Creating Python Classes:

Blueprint Initialization

Module 21 - Python Class Methods and the 'self' Parameter

Module 22 -Python Constructors:

The initDunder Method

Module 23 - Python Inheritance:

Parent and Child Class Relationships

Module 24 - Advanced Inheritance:

Single, Multiple, and Multi-Level

Instructors

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