Google Colab For Data Science & Ai Using Python

Master Python Programming from Scratch Using Google Colab –Hands-on, Beginner-Friendly, and Practical.

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 JavaScript 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.