#Python
34 articles tagged with #Python
Learn Python Through Cricket: Your Ultimate Beginner's Guide
Discover how cricket can help you understand Python programming in the most exciting way.
Learn Loops in Python by Building a Cricket Scoreboard
A comprehensive guide to learn loops in python by building a cricket scoreboard — written for learners at every level.
Learn Pandas by Analyzing Virat Kohli's Career Stats
A comprehensive guide to learn pandas by analyzing virat kohli's career stats — written for learners at every level.
Python for Beginners: A Complete 2026 Roadmap
A comprehensive guide to python for beginners: a complete 2026 roadmap — written for learners at every level.
How to Install Python and Set Up VS Code (Step by Step)
A comprehensive guide to how to install python and set up vs code (step by step) — written for learners at every level.
Top 20 Python Projects for Beginners to Build a Portfolio
A comprehensive guide to top 20 python projects for beginners to build a portfolio — written for learners at every level.
Object-Oriented Programming in Python Explained Simply
A comprehensive guide to object-oriented programming in python explained simply — written for learners at every level.
Python Error Handling: try, except, finally Made Simple
A comprehensive guide to python error handling: try, except, finally made simple — written for learners at every level.
Pandas for Beginners: A Complete Tutorial
A comprehensive guide to pandas for beginners: a complete tutorial — written for learners at every level.
10 Python Projects to Build From Beginner to Advanced
A comprehensive guide to 10 python projects to build from beginner to advanced — written for learners at every level.
From Cricket Fan to Python Developer: A Learner's Journey
A comprehensive guide to from cricket fan to python developer: a learner's journey — written for learners at every level.
How to Become an AI Engineer (Roadmap 2026)
A clear, step-by-step roadmap from Python foundations to deploying AI systems in production.
Python Functions Explained for Beginners
Functions are named, reusable blocks of code — learn to define them, pass arguments, and return values.
Python Interview Questions and Answers (2026 Edition)
Python interviews cluster around fundamentals, data structures, OOP, and gotchas — this guide prepares you for all of them.
Project: Build a REST API with Python and FastAPI
FastAPI is the fastest-growing Python web framework — and for good reason. In this hands-on project you'll build a fully functional REST API with auto-generated documentation, database persistence, and deployment on Render, all in a single afternoon.
Project: Build a Data Dashboard with Python and Streamlit
Streamlit turns a Python script into an interactive web app in minutes — no frontend knowledge required. In this project you'll build a live sales dashboard with filters, KPI metrics, and Plotly charts from a CSV dataset, then share it online for free.
Learn Python Through Cricket Statistics
Cricket generates rich data — runs, wickets, overs, strike rates, economy rates. This project uses real IPL-style match data to teach you pandas, matplotlib, and data analysis in a context that actually interests you. No dry tutorials — just cricket and code.
RAG Explained: Retrieval-Augmented Generation
RAG is how you give an LLM access to your own private data without training a new model. This guide explains the full pipeline — chunking, embeddings, vector search, and augmented generation — with a working Python example using open-source tools.
The 2026 AI Engineer Roadmap: Skills, Tools, and Career Path
AI Engineer is one of the fastest-growing roles in tech — and it's more accessible than traditional ML engineering. This guide maps the exact skills, tools, and learning sequence for becoming an AI engineer in 2026, from Python basics to deploying production RAG and agent systems.
Object-Oriented Programming in Python: A Practical Guide
OOP is how Python codebases stay organised as they grow. This guide explains classes, inheritance, encapsulation, and polymorphism with real examples — and tells you honestly when to use OOP and when plain functions are the better choice.
Async Python: asyncio Explained for Beginners
Async Python lets a single thread handle hundreds of concurrent I/O operations — making it essential for web APIs, database calls, and AI integrations. This guide explains coroutines, the event loop, await, gather, and real patterns you'll use in FastAPI, httpx, and LLM streaming.
Python Decorators: A Practical Guide for Beginners
Decorators are one of Python's most powerful features — they let you wrap functions with reusable logic without modifying the original. This guide explains how they work from first principles, builds several practical decorators (timing, caching, authentication), and covers class-based decorators and decorator factories.
From Cricket Fan to Python Developer: An Illustrative Learning Journey
This is a composite illustrative journey — based on the real paths taken by many self- taught developers — showing how a passionate cricket fan used IPL data to learn Python, pandas, and data visualisation, and landed a data analyst role in 8 months.
Python Error Handling: try, except, finally Explained
Errors are inevitable; crashes are not. This guide explains Python's exception system from first principles: how try/except/finally works, which exceptions to catch (and which to let propagate), how to raise your own exceptions, and how to write error handling that helps debugging rather than hiding bugs.
Python Virtual Environments: venv, conda, and poetry Explained
Installing packages globally is fine until it isn't — then you have version conflicts, broken projects, and chaos. This guide explains virtual environments from first principles and shows you how to use venv, pip, poetry, and conda to keep your projects isolated and reproducible.
Python List Comprehensions Made Easy
List comprehensions are one of Python's most beloved features — they let you create lists with concise, readable one-liners instead of multi-line for loops. This guide explains the syntax, filtering, nesting, dict and set comprehensions, and when to use (and avoid) them.
Testing Python Code with pytest: A Beginner's Guide
Untested code is legacy code from the moment it's written. This guide explains how to write effective Python tests with pytest — from your first test function through fixtures, parametrize, mocking, and measuring coverage.
From Teacher to Data Analyst: An Illustrative 8-Month Transition
This composite illustrative story follows how a secondary school maths teacher used her existing analytical skills to transition into a data analyst role — starting with Excel, moving to SQL and Python, and landing her first data role in 8 months.
Regular Expressions in Python: A Practical Guide
Regular expressions are one of the most powerful text-processing tools in programming — and one of the most avoided, because the syntax looks intimidating. This guide demystifies regex by building from first principles, with real patterns for emails, phone numbers, dates, and log parsing.
Python File I/O: Reading and Writing Files
Almost every real Python program reads or writes files — logs, configs, CSVs, JSON, reports. This guide covers text files, CSV, JSON, binary files, and the modern pathlib approach, with best practices for safe file handling.
NumPy for Data Science: Arrays and Vectorisation
NumPy is the foundation of Python's scientific computing stack. This guide covers ndarrays, vectorised operations, broadcasting, linear algebra, and why NumPy is 10-100x faster than equivalent Python loops — with practical examples for data science work.
Learn Data Science Through Bollywood Box Office Analytics
Bollywood produces hundreds of films a year and generates rich box office data. This project uses real film data to teach pandas groupby, matplotlib charting, correlation analysis, and time-series trends in a context that film fans genuinely find interesting.
Matplotlib and Seaborn: Data Visualisation in Python
The best data insight is worthless if no one understands the chart. This guide covers matplotlib's core API, Seaborn's statistical plots, best practices for clear design, and how to produce publication-quality figures — from first plot to polished dashboard chart.
Scikit-Learn for Beginners: Machine Learning in Python
Scikit-learn is the most widely used Python library for classical machine learning. This guide covers the fit-predict workflow, train/test splits, classification, regression, model evaluation, feature engineering, and pipelines — everything you need to build and evaluate your first ML models.