🚀🔥 𝗕𝗲𝗰𝗼𝗺𝗲 𝗮𝗻 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗔𝗜 𝗕𝘂𝗶𝗹𝗱𝗲𝗿 — 𝗙𝗿𝗲𝗲 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗣𝗿𝗼𝗴𝗿𝗮𝗺
Master the most in-demand AI skill in today’s job market: building autonomous AI systems.

In Ready Tensor’s free, project-first program, you’ll create three portfolio-ready projects using 𝗟𝗮𝗻𝗴𝗖𝗵𝗮𝗶𝗻, 𝗟𝗮𝗻𝗴𝗚𝗿𝗮𝗽𝗵, and vector databases — and deploy production-ready agents that employers will notice.

Includes guided lectures, videos, and code.
𝗙𝗿𝗲𝗲. 𝗦𝗲𝗹𝗳-𝗽𝗮𝗰𝗲𝗱. 𝗖𝗮𝗿𝗲𝗲𝗿-𝗰𝗵𝗮𝗻𝗴𝗶𝗻𝗴.

👉 Apply now: https://go.readytensor.ai/agentic-ai-cert-resources

🔰 Deep Python Roadmap for Beginners 🐍

Setup & Installation 🖥⚙️
• Install Python, choose an IDE (VS Code, PyCharm)
• Set up virtual environments for project isolation 🌎

Basic Syntax & Data Types 📝🔢
• Learn variables, numbers, strings, booleans
• Understand comments, basic input/output, and simple expressions ✍️

Control Flow & Loops 🔄🔀
• Master conditionals (if, elif, else)
• Practice loops (for, while) and use control statements like break and continue 👮

Functions & Scope ⚙️🎯
• Define functions with def and learn about parameters and return values
• Explore lambda functions, recursion, and variable scope 📜

Data Structures 📊📚
• Work with lists, tuples, sets, and dictionaries
• Learn list comprehensions and built-in methods for data manipulation ⚙️

Object-Oriented Programming (OOP) 🏗👩‍💻
• Understand classes, objects, and methods
• Dive into inheritance, polymorphism, and encapsulation 🔍

React "❤️" for Part 2

Python Roadmap
|
|-- Fundamentals
| |-- Basics of Programming
| | |-- Introduction to Python
| | |-- Setting Up Development Environment (IDE: PyCharm, VSCode, etc.)
| |
| |-- Syntax and Structure
| | |-- Basic Syntax
| | |-- Variables and Data Types
| | |-- Operators and Expressions
|
|-- Control Structures
| |-- Conditional Statements
| | |-- If-Else Statements
| | |-- Elif Statements
| |
| |-- Loops
| | |-- For Loop
| | |-- While Loop
| |
| |-- Exception Handling
| | |-- Try-Except Block
| | |-- Finally Block
| | |-- Raise and Custom Exceptions
|
|-- Functions and Modules
| |-- Defining Functions
| | |-- Function Syntax
| | |-- Parameters and Arguments
| | |-- Return Statement
| |
| |-- Lambda Functions
| | |-- Syntax and Usage
| |
| |-- Modules and Packages
| | |-- Importing Modules
| | |-- Creating and Using Packages
|
|-- Object-Oriented Programming (OOP)
| |-- Basics of OOP
| | |-- Classes and Objects
| | |-- Methods and Constructors
| |
| |-- Inheritance
| | |-- Single and Multiple Inheritance
| | |-- Method Overriding
| |
| |-- Polymorphism
| | |-- Method Overloading (using default arguments)
| | |-- Operator Overloading
| |
| |-- Encapsulation
| | |-- Access Modifiers (Public, Private, Protected)
| | |-- Getters and Setters
| |
| |-- Abstraction
| | |-- Abstract Base Classes
| | |-- Interfaces (using ABC module)
|
|-- Advanced Python
| |-- File Handling
| | |-- Reading and Writing Files
| | |-- Working with CSV and JSON Files
| |
| |-- Iterators and Generators
| | |-- Creating Iterators
| | |-- Using Generators and Yield Statement
| |
| |-- Decorators
| | |-- Function Decorators
| | |-- Class Decorators
|
|-- Data Structures
| |-- Lists
| | |-- List Comprehensions
| | |-- Common List Methods
| |
| |-- Tuples
| | |-- Immutable Sequences
| |
| |-- Dictionaries
| | |-- Dictionary Comprehensions
| | |-- Common Dictionary Methods
| |
| |-- Sets
| | |-- Set Operations
| | |-- Set Comprehensions
|
|-- Libraries and Frameworks
| |-- Data Science
| | |-- NumPy
| | |-- Pandas
| | |-- Matplotlib
| | |-- Seaborn
| | |-- SciPy
| |
| |-- Web Development
| | |-- Flask
| | |-- Django
| |
| |-- Automation
| | |-- Selenium
| | |-- BeautifulSoup
| | |-- Scrapy
|
|-- Testing in Python
| |-- Unit Testing
| | |-- Unittest
| | |-- PyTest
| |
| |-- Mocking
| | |-- unittest.mock
| | |-- Using Mocks and Patches
|
|-- Deployment and DevOps
| |-- Containers and Microservices
| | |-- Docker (Dockerfile, Image Creation, Container Management)
| | |-- Kubernetes (Pods, Services, Deployments, Managing Python Applications on Kubernetes)
|
|-- Best Practices and Advanced Topics
| |-- Code Style
| | |-- PEP 8 Guidelines
| | |-- Code Linters (Pylint, Flake8)
| |
| |-- Performance Optimization
| | |-- Profiling and Benchmarking
| | |-- Using Cython and Numba
| |
| |-- Concurrency and Parallelism
| | |-- Threading
| | |-- Multiprocessing
| | |-- Asyncio
|
|-- Building and Distributing Packages
| |-- Creating Packages
| | |-- setuptools
| | |-- Creating environment setup
| |
| |-- Publishing Packages
| | |-- PyPI
| | |-- Versioning and Documentation

Best Resource to learn Python

Python Interview Questions with Answers

Freecodecamp Python ML Course with FREE Certificate

Python for Data Analysis

Python course for beginners by Microsoft

Scientific Computing with Python

Python course by Google

Python Free Resources

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ENJOY LEARNING 👍👍

Important Machine Learning Algorithms 👆

Some helpful Data science projects for beginners

https://www.kaggle.com/c/house-prices-advanced-regression-techniques

https://www.kaggle.com/c/digit-recognizer

https://www.kaggle.com/c/titanic

BEST RESOURCES TO LEARN DATA SCIENCE AND MACHINE LEARNING FOR FREE

https://developers.google.com/machine-learning/crash-course

https://www.kaggle.com/learn/overview

https://forums.fast.ai/t/recommended-python-learning-resources/26888

https://www.fast.ai/

https://imp.i115008.net/JrBjZR

https://ern.li/OP/1qvkxbfaxqj

ENJOY LEARNING 👍👍

Complete Pandas 🐼 Notes 🚀✅