Python Ka Chilla Day 12: Learning with Dr. Ammar Tufail

Today, I’m sharing my latest article on Medium where I explored some of the most common mistakes beginners make while learning Python basics. As part of my continuous learning journey in Python, I recently explored some of the most common mistakes beginners make while learning the basics of programming. Through this article, I’ve highlighted key beginner-level pitfalls and how overcoming them can enhance both confidence and logical thinking — which are essential when moving towards advanced domains like Artificial Intelligence and Data Science. Sharing this as part of my learning journey and growth in the tech space #Python #Programming #LearningJourney #BeginnerProgrammer #TechGrowth #CodingSkills #ArtificialIntelligence #FutureSkills #ContinuousLearning #WomenInTech #MediumWriter

Python | Operator | Master Learning Full youtube video link in description Python Operators are the foundation of programming. Without understanding operators, you cannot perform calculations, comparisons, or logical decisions in your code. 🐍 Beginners – Python Operators 🎯 Where, When & How to Apply Operators in Coding In this beginner-friendly guide, I have explained **Python Operators in simple language with clear examples**, specially designed for foundation learners. 📌 Most Important Rule in Coding In programming, it’s not just about knowing operators. It’s about understanding: 👉 Which operator to use 👉 Where to apply it 👉 How to use it correctly 👉 When it is required in logic or conditions This clarity makes your code accurate, efficient, and error-free. 📚 What You Will Learn 🤔 What are Python Operators? 🖊️ 6 major types of operators ✔ Arithmetic Operators (+, -, *, /) ✔ Comparison Operators ✔ Logical Operators (and, or, not) ✔ Assignment Operators ✔ Identity Operator ✔ Membership Operator 🧐How operators work inside conditions? ✔🖊️Practical code examples for better understanding #PythonBeginners #PythonOperators #LearnPython #CodingBasics #ProgrammingForBeginners #DeveloperJourney #PythonLearning https://lnkd.in/gKPyH7aG

Common Beginner Mistakes with Python Lists, Dictionaries & Sets When I started learning Python, Lists, Dictionaries, and Sets looked simple. But small misunderstandings caused big confusion. Here are some common beginner mistakes (and fixes): 🔹 Lists 1. Modifying a list while iterating Removing items inside a loop can skip elements. Fix: Use list comprehension instead. 2. Confusing append() vs extend() append() adds one item extend() adds multiple elements 🔹 Dictionaries 1. Accessing a non-existent key Using dict["key"] can cause a KeyError. Fix: Use dict.get("key", default_value) 2. Using mutable objects as keys Lists ❌ Tuples ✅ (Dictionary keys must be immutable) 🔹 Sets 1. Expecting ordered output Sets are unordered — they are not automatically sorted. Use sorted(set_name) if needed. 2. Trying to access by index Sets don’t support indexing. Convert to list if indexing is required. Mistakes are part of learning. Understanding these small details helps write cleaner and more reliable Python code. Keep learning. Keep building. 💡🚀 #Python #Coding #Beginners #Learning #Programming #innomaticsresearchlabs

Python Basics – FAQs (Week 2 Learning Recap) 🐍 Strengthening fundamentals is the key to mastering Python. Here are some important Python FAQs that every beginner should know: 🔹 Lists & Indexing Indexing always starts from 0, even in nested (sub-level) lists Lists are mutable – values can be changed remove() deletes only the first occurrence pop() removes and returns the element 🔹 Tuples & Sets Tuples are immutable Combined tuples don’t update automatically unless stored Sets are unordered, unique, and don’t allow duplicates 🔹 Strings Strings are immutable sequences of Unicode characters Can be created using single, double, or triple quotes Printed easily using print() 🔹 range() Function Used mainly for looping Works with start, stop, and step Ends at stop – 1 🔹 Tools & Setup Spyder can be installed via Anaconda Navigator Lecture slides & videos are available under the respective download tabs 📌 These small concepts make a big difference when writing clean and efficient Python code. 💡 Keep learning. Keep coding. One concept at a time! #Python #PythonBasics #Programming #LearningPython #CodingJourney #ECE #StudentLife #TechSkills #FAQs #Anaconda

Python Tip for Beginners: Mastering Imports (The Right Way!) One of the biggest “aha!” moments for new Python learners is realizing that you don’t have to write everything from scratch. Python comes with powerful built in modules and you can even create your own and reuse them across projects. At Everybody’s Code Academy, this is one of the first concepts we teach our students because it unlocks clean code, faster development, and real-world project building. Here’s a simple breakdown What is a module? A module is simply a Python file that contains reusable code (functions, variables, classes). Example: math → for calculations random → for generating random numbers datetime → for date & time Common ways to import in Python import math → use as math.sqrt(16) from math import sqrt → use as sqrt(16) import datetime as dt → use as dt.now() Import your own file: import calculator Why imports matter Helps organize your code Encourages code reuse Makes your programs cleaner and more professional Prepares beginners for real-world projects and teamwork Beginner Tip: Avoid from module import * in real projects—it can cause confusion and bugs later. We’re building our Python curriculum in a way that’s: 📌 Beginner-friendly 📌 Practical 📌 Project-based 📌 Fun and engaging for kids & teens If you’re learning Python or teaching beginners, save this post and try the examples today. Consistency + small daily practice = big growth in coding #Python #LearnPython #ProgrammingForBeginners #CodingForKids #EverybodyCodes #TechEducation #100DaysOfCode #STEM #CodeNewbies #SoftwareDevelopment

Day 10 – Python Functions & Reusability 🚀 (Learning Log) Today I spent time understanding functions in Python and how they help in writing clean, reusable, and structured code. Key takeaways from today’s learning: A block is a set of instructions or tasks written together When a block is used multiple times → it’s just a block When a block is reused with different inputs → it becomes a reusable block Functions help: Reduce code length Avoid unnecessary repetition Improve readability and organization Understanding Python Functions: A function is a reusable block of code that performs a specific task If a function does not return anything explicitly, it returns None by default Functions are stored in memory first and executed only when called Types of Functions Practiced: Static functions (same output, no input) Dynamic functions (output depends on input) Functions with: Positional arguments Default parameters Arbitrary arguments (*args) Keyword arguments Keyword arbitrary arguments (**kwargs) Advanced concepts explored: Recursion (a function calling itself under a condition) Understanding how parameters and arguments work internally Importance of argument order and matching parameter count This session helped me clearly understand how Python handles function calls, arguments, and reusability, which is a core concept for writing scalable programs. Consistently learning and building step by step. 💻📚 #Python #PythonProgramming #FunctionsInPython #CodingJourney #LearningPython #ProgrammingBasics #SoftwareDevelopment #StudentDeveloper #DailyLearning #CodeReusability

🐍 #Day6 of Python Learning 🚀 📚 Topic: Conditional Statements in Python Trainer: Manivardhan Jakka Today’s session focused on Conditional Statements, which allow Python programs to make decisions and execute code based on specific conditions. This is a core concept that adds logic and intelligence to our programs. 🔹 What are Conditional Statements? Conditional statements help control the flow of execution by checking whether a condition is True or False. 🔹 Types of Conditional Statements in Python ✅ if statement – Executes code when a condition is true 🔁 if–else statement – Provides an alternative path when the condition is false 🧠 if–elif–else ladder – Checks multiple conditions sequentially 🔄 Nested if – if statements inside another if block 🔹 Key Concepts Learned ✔ Conditions are evaluated using comparison operators ✔ Indentation plays a crucial role in Python logic ✔ Helps in decision-making and real-world problem solving 💡 Key Takeaway: Mastering conditional statements is essential for building dynamic, logical, and user-friendly Python applications. Feeling more confident in controlling program flow today! 💪🐍 10000 Coders #Day6OfPythonLearning #PythonConditionalStatements #PythonBasics #IfElseInPython #LearningPython #CodingJourney #10000Coders

🚀 Excited to Share My Python Learning Series on GitHub! 🐍 I’ve been working on building a structured Python course series, where I’m documenting concepts day by day along with notes and practice examples. This repository is designed to help beginners build a strong foundation in Python through consistent daily learning. 🔗 GitHub Repository: https://lnkd.in/gmDZgKhT I’ll continue updating it with more topics and improvements. If you’re learning Python or just starting out, feel free to check it out. I would truly appreciate your feedback and suggestions to make it better! #Python #Programming #OpenSource #Learning

Common Beginner Mistakes with Python Lists, Dictionaries & Sets 🐍 When I started learning Python, Lists, Dictionaries, and Sets looked simple. But small misunderstandings caused big confusion. Here are some common beginner mistakes (and fixes): 🔹 Lists 1. Modifying a list while iterating Removing items inside a loop can skip elements. ✅ Fix: Use list comprehension instead. 2. Confusing append() vs extend() append() adds one item extend() adds multiple elements 🔹 Dictionaries 1. Accessing a non existent key Using dict["key"] can cause a KeyError. ✅ Fix: Use dict.get("key", default_value) 2. Using mutable objects as keys Lists ❌ Tuples ✅ (Dictionary keys must be immutable) 🔹 Sets 1. Expecting ordered output Sets are unordered — they are not automatically sorted. ✅ Use sorted(set_name) if needed. 2. Trying to access by index Sets don’t support indexing. ✅ Convert to list if indexing is required. Mistakes are part of learning. Understanding these small details helps write cleaner and more reliable Python code. Keep learning. Keep building. 💡🚀 #Python #Coding #Beginners #Learning #Programming

🚀 Day of Learning Python Functions 🐍 Today, I practiced one of the most important concepts in Python — Functions. Functions help us write clean, reusable, and well-structured code, which is very important as programs grow bigger. Creating a function to calculate the average of numbers Understanding how return works in Python ✨ Example Highlight I created a function that calculates the average of three numbers: def avg_sum(a, b, c): sum = a + b + c avg = sum / 3 return avg This made it clear how data flows into a function (parameters) and comes back (return value). 📌 Types of Functions in Python I Learned Today: 1️⃣ Function with no parameters and no return value 👉 Used mainly for printing or displaying messages Example: printHello() 2️⃣ Function with parameters but no return value 👉 Takes input but only performs an action 3️⃣ Function with parameters and return value ✅ 👉 Most commonly used in real-world programs Example: avg_sum(a, b, c) 4️⃣ Built-in Functions 👉 Like print(), len(), sum() 5️⃣ User-defined Functions 👉 Functions created by us to solve specific problems 💡 Key Takeaway: Functions make code modular, readable, and reusable, which is a must-have skill for every programmer. Excited to learn more and apply this in real projects 🚀 #Python #PythonFunctions #LearningPython #CodingJourney #BCAStudent #Programming #DeveloperLife #PythonBasics