What you'll learn

Understand Python fundamentals, including syntax, data types, and control flow.
Work with Google Colab, an online Jupyter-based platform, without the need for local installations.
Store and manipulate data using variables, lists, tuples, dictionaries, and sets.
Make decisions using conditional statements and automate tasks with loops.
Create reusable functions, work with arguments, and explore lambda functions.
Work with classes, objects, inheritance, polymorphism, and encapsulation.
Read, write, and manage text, CSV, and JSON files while handling errors effectively.
Explore NumPy, Pandas, Matplotlib, Seaborn, and Plotly for data manipulation and visualization.
Load, clean, and analyze datasets using Pandas and visualize insights with Matplotlib and Seaborn.
Fetch and process data from external sources using the requests library.
Apply pattern matching for data validation and text processing.
Learn advanced Python concepts for efficient programming.
Understand fundamental concepts, train simple models, and evaluate their performance.

Requirements

Basic Computer Skills – Comfortable with using a computer, browsing the internet, and managing files.
A Google Account – Required to access Google Colab (free to create).
Internet Access – Since Google Colab runs online, a stable internet connection is necessary.
Curiosity and Willingness to Learn – A problem-solving mindset and eagerness to explore Python.
Basic Mathematics Understanding (Optional) – A general understanding of basic math concepts (addition, subtraction, multiplication, division) will be helpful, but not mandatory.
No Software Installation Required! – Since we will be using Google Colab, there is no need to install Python or any additional software on your local machine. Everything runs in the cloud!

Description

Learn Python from Scratch Using Google Colab – A Hands-On, Beginner-Friendly Approach!Python is one of the most powerful, versatile, and beginner-friendly programming languages used in web development, data science, automation, and artificial intelligence. In this course, you will learn Python from scratch using Google Colab, a free, cloud-based coding platform that eliminates the need for software installation, making it easy to write and execute Python code from any device.Through step-by-step lessons, hands-on exercises, and real-world examples, you will build a strong foundation in Python programming and develop the skills needed for practical applications. Whether you are an absolute beginner, a student, or a professional looking to enhance your technical skills, this course will provide the structured learning experience you need.What You Will LearnPython Basics – Understand Python syntax, variables, data types, operators, and expressions. Control Flow and Loops – Implement conditional statements (if-else), loops (for, while), and loop control mechanisms (break, continue).Functions and Modular Programming – Write reusable code using functions, parameters, return values, and lambda functions.Working with Data Structures – Learn how to store and manipulate data efficiently with lists, tuples, dictionaries, and sets Object-Oriented Programming (OOP) – Understand the principles of OOP, including classes, objects, inheritance, encapsulation, and polymorphism.File Handling & Exception Management – Read, write, and process text and CSV files while handling errors efficiently using try-except blocks.Hands-On with Google Colab – Explore the features of Google Colab, including code cells, markdown, file management, and library integration. Working with Python Libraries – Use NumPy, Pandas, Matplotlib, and Seaborn for data manipulation and visualization.Regular Expressions & API Interactions – Apply pattern matching for text processing and interact with external REST APIs using the requests library.Advanced Python Features – Learn about decorators, iterators, generators, and context managers for writing efficient Python code.Data Analysis and Visualization – Load and analyze datasets, clean and transform data, and create interactive plots using Plotly.Introduction to Machine Learning – Get a basic understanding of machine learning, explore data preprocessing, and train simple models using scikit-learn.Course Highlights100% Hands-On Learning – Apply Python concepts in real-world coding exercises and projects.No Installations Required – Work directly in Google Colab, eliminating setup complexities. Step-by-Step Guidance – Every concept is explained with clear examples and practice exercises. Practical Applications – Learn how Python is used in automation, data science, and web development. Interactive Coding Experience – Code along with instructor-led exercises in a structured environment.

Overview

Section 1: Introduction to Python and Google Colab
Lecture 1 Origins and evolution of Python
Lecture 2 Why Python is popular ?
Lecture 3 Compare and contrast Python with other languages
Lecture 4 Showcase real-world applications
Lecture 5 Procedural Programming
Lecture 6 Object-Oriented Programming (OOP)
Lecture 7 Functional Programming
Lecture 8 Local Installation
Lecture 9 Dependency Management
Lecture 10 Virtual Environments
Lecture 11 What is Google Colab It_s purpose & Advantages ?
Lecture 12 Setting up a Google Colab account
Lecture 13 Detailed tour of the Colab interface (menus, toolbar, file explorer).
Lecture 14 Explain the concept of cells
Lecture 15 Demonstrate basic cell operations (adding, deleting, moving, running).
Lecture 16 Python Basics-Variables
Lecture 17 Data Types - Integers & Type Conversion.
Lecture 18 Operators - Arthmetic, Comparision & Logical Operators
Lecture 19 String Manipulations
Lecture 20 Input() Function
Lecture 21 Print() Function
Lecture 22 Comments in Python
Lecture 23 Python Code Style Guidelines
Lecture 24 Hands On - Write a program that takes the user's name as input and greets them
Lecture 25 Hands On - Write a program that performs basic arithmetic operations
Lecture 26 Hands On - Format the Notebook
Section 2: Module 2: Control Flow and Functions
Lecture 27 Conditional Statements : If , Elif , Else
Lecture 28 Conditional Statements : Nested If Statements
Lecture 29 Loops : For Loop
Lecture 30 Loops : While Loop
Lecture 31 Loops : Nested Loops
Lecture 32 Loop Control Statements : Break
Lecture 33 Loop Control Statements : Continue
Lecture 34 Loop Control Statements : Pass
Lecture 35 Functions : Definition
Lecture 36 Functions: Parameter and Return Values
Lecture 37 Functions: Default Arguments
Lecture 38 Functions: Keyword Arguments
Lecture 39 Functions: Scope of Variables
Lecture 40 Lambda Functions : Anonymous Functions
Lecture 41 Lamdba Functions : Syntax of Lambda Functions
Lecture 42 Lambda Functions : Use Cases
Lecture 43 Hands On - Write a function to calculate the factorial of a number
Lecture 44 Hands On - Write a function to check if a number is prime.
Lecture 45 Hands On - Write a function to reverse a string
Lecture 46 Hands On - Create a function to calculate the area of different shapes.
Section 3: Module 3: Data Structures
Lecture 47 Lists : Creating lists using Square brackets
Lecture 48 Lists : Indexing and slicing accessing elements by their position
Lecture 49 Lists : Modifying Lists
Lecture 50 Lists : List Methods
Lecture 51 Lists : List Comprehensions
Lecture 52 Lists : Iterating over Lists
Lecture 53 Tuples : Creating tuples using Parentheses()
Lecture 54 Tuples : Accessing Elements
Lecture 55 Tuples : Immutability
Lecture 56 Tuples : Tuples use cases
Lecture 57 Dictionaries : Creating Dictionaries
Lecture 58 Dictionaries : Accessing Values
Lecture 59 Dictionaries : Modifying Dictionaries
Lecture 60 Dictionaries : Dictionary Methods
Lecture 61 Dictionaries : Dictionary Comprehensions
Lecture 62 Dictionaries : Iterating over Dictionaries
Lecture 63 Sets : Iterating over Dictionaries
Lecture 64 Sets : Uniqueness
Lecture 65 Set Operations
Lecture 66 Set Method
Lecture 67 Hands On - Create a dictionary to store student information
Lecture 68 Hands On - Use sets to find common elements between two lists.
Lecture 69 Hands On - Implement a shopping cart using a dictionary to store items
Lecture 70 Hands On - Write a program to find the most frequent element in a list
Absolute Beginners in Programming – If you've never written a line of code before, don't worry! This course will guide you step by step in a beginner-friendly way.,Students & Educators – Ideal for students learning Python for the first time and educators who want to introduce Python programming in their curriculum.,Aspiring Data Scientists & Analysts – If you want to explore data science, machine learning, or automation, Python is an essential skill, and this course will help you build a strong foundation.,Professionals Looking to Upskill – Whether you're in IT, finance, marketing, or any other field, Python can help automate tasks, analyze data, and enhance productivity.,Developers & Programmers from Other Languages – If you have experience in other programming languages like Java, C++, or jаvascript and want to learn Python quickly, this course will provide a smooth transition.,Business & Non-Tech Professionals – Learn how Python can be used for automation, basic data analysis, and productivity enhancements without needing extensive programming knowledge.,Machine Learning & AI Enthusiasts – Python is the foundation of artificial intelligence and machine learning. This course will help you start your journey into these advanced fields.,Freelancers & Entrepreneurs – If you're looking to add Python to your skill set for freelancing, web development, or automation, this course will be a great starting point.


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