Hello Everyone, I used to process data manually… one row at a time 😅 Then I learned loops—and everything became faster. 👉 Why repeat work, when Python can do it for you? In this step, I learned: ⚡ for loop → iterate through data (lists, datasets) (page 4–6) ⚡ while loop → run until condition is met (page 7–8) ⚡ break, continue, pass → control loop behavior (page 10–12) ⚡ Combine loops with conditions → real data filtering (page 13–14) Big realization: 👉 Loops turn manual work into automation. Now I can process thousands of records in seconds instead of hours 📊 💬 Do you still use loops, or mostly pandas now? #Python #DataAnalytics #LearningJourney #Programming #DataScience #Upskilling

Every data science person installs packages in Notebooks and offcourse we always start at !pip install. This should be quick. Twenty minutes later, still at 78%. ERROR: Failed building wheel for difficult-package. If you have never wanted to flip a desk over a failed package installation, have you even coded? When this happens, here is what actually fixes it: Update pip first: python -m pip install --upgrade pip Install wheel: pip install wheel Google the exact error message. Someone has already solved it. Installing packages is not glamorous. But knowing how to fix it when it breaks is a real developer skill. What is the most frustrating package you have ever tried to install? #Python #DataScience #LearnToCode #Debugging #PipInstall #StudentLife

Week 4 of #100DaysOfCode — done! 🎉 Last week I learned how to build classes. This week I learned how to make them talk to each other. Topics covered: 🧹 Inheritance → Superclass, subclass, base class — and what they actually mean → How Python finds attributes (spoiler: it walks up the chain) → Overriding methods — and extending them with super() → isinstance, issubclass, type — when to use which → Multiple inheritance + MRO (Method Resolution Order) 🏗️ Abstract Classes & Interfaces → ABC + @abstractmethod — enforcing a contract on subclasses → Duck typing — "if it has a speak() method, it speaks" → Subclassing built-ins (list, dict, iterator) → Mixins — plugging in behaviour without full inheritance I’ve structured my learning into notes and practical examples to better understand the concepts : https://lnkd.in/epaBymnJ #100DaysOfCode #Python #OOP #LearningInPublic #Programming

Just wrapped up a classic! 🎮 I built a functional Hangman game using Python to practice core programming concepts like loop structures, conditional logic, and set operations for tracking user input. It’s a simple project, but it’s these building blocks that make tackling complex Data Science problems possible later on. Check out the clip to see it in action! 🐍 https://lnkd.in/gkDfGfT3 CodeAlpha #codeAlpha #Python #Coding #BTech #DataScience #BuildInPublic #SoftwareDevelopment

LLMs are useful on their own, but things get much more interesting when you can work with them directly from your code. Tomorrow, Myles Mitchell, Principal Data Scientist at Jumping Rivers, is leading a webinar on Programming with LLMs in R & Python. He’ll cover how LLMs work, how they’re priced, where they’re useful, where they fall short, and how to start using them programmatically. The examples will focus mainly on R with {ellmer}, including how to send prompts, use system prompts, request structured outputs, and summarise images and PDFs. There’ll also be a brief look at {chatlas} for Python users. Date: Thursday 23 April 2026 Time: 1:15 PM UK time Venue: Online Cost: Free to attend You can still register here: https://lnkd.in/dKBMZXKX

🚀 Day 83 of #100DaysOfCode 📌 Problem Solved: Letter Combinations of a Phone Number (LeetCode 17) Today’s challenge was all about exploring backtracking and how recursive decision-making builds combinations efficiently. 🔍 Given a string of digits (2–9), the goal is to generate all possible letter combinations based on the classic phone keypad mapping. 💡 Key Learning: Instead of trying every possible string blindly, backtracking helps us build combinations step-by-step and explore only valid paths — making the solution clean and efficient. ⚡ Highlights: ✔️ Used recursion to explore all possibilities ✔️ Implemented a digit-to-letter mapping ✔️ Built combinations incrementally ✔️ Achieved optimal runtime performance 📈 Result: ✅ All test cases passed ⚡ 0 ms runtime (Beats 100%) Consistency is starting to compound — one problem at a time. 💪 #LeetCode #DSA #Python #CodingJourney #Backtracking #100DaysOfCode

🚀 Day 3/100: Mastering Logic Flow & Decision Making! 🏝️ The #100DaysOfCode journey is heating up! Today was all about Control Flow and Conditional Logic in Python. I built a "Treasure Island" text adventure game to practice: ✅ Nested if/elif/else statements ✅ Complex logical operators (AND / OR) ✅ Managing user input edge cases Understanding branching logic is a massive step toward building robust automation scripts and handling real-world data scenarios. ⚔️ Check out my code here: 🔗 https://lnkd.in/gxyRjpGh Onward to Day 4! 🚀 #Python #100DaysOfCode #LogicBuilding #Programming #DevLife #GrowthMindset #CodeNewbie

I used to think tuples were just “lists with stricter rules”… but today showed me they have their own vibe. 🐍 Day 06 of my #30DaysOfPython journey was all about tuples, and this topic made one thing really clear: sometimes the best data structure is the one that stays put. A tuple is an ordered and unchangeable collection of different data types, created using round brackets (). Today I explored: 1. Creating tuples with tuple() 2. Accessing items using positive and negative indexing 3. Slicing tuples with positive and negative indexes 4. Checking whether an item exists using in 5. Counting items with count() 6. Finding item positions with index() 7. Joining tuples using + operator 8. Converting tuples to lists with list() 9. Deleting the whole tuple using del What stood out to me today was how tuples are built for stability. They are not meant to be edited over and over again — and that actually makes them really useful when you want data to stay consistent. One more day, one more topic, one more layer of Python making sense. Github Link - https://lnkd.in/gHwugKTU #Python #LearnPython #CodingJourney #30DaysOfPython #Programming #DeveloperJourney

Looping Through Logic 🔄 This infographic illustrates the lifecycle of a Python for loop, transforming a block of code into a clear, step-by-step physical process. By visualizing the list as a circular path, it's easier to see how Python "visits" every element without you having to write individual lines for each one. The Breakdown • Code: The simple syntax that tells Python what to do. • Flowchart: The logic gate that decides whether to keep going or stop. • Iteration: The actual journey each item takes from the list to your console. #PythonProgramming #Coding101 #DataScience #SoftwareDevelopment #LearnToCode #PythonLoops #ProgrammingLogic #TechEducation #CodeNewbie #Automation

🚀 Excited to share my latest project: File System Recovery and Optimization Tool In this project, I designed a system that: ✔️ Simulates real-world file system operations ✔️ Recovers data after crashes or accidental deletion ✔️ Optimizes storage using efficient allocation techniques ✔️ Reduces fragmentation and improves performance 💡 Key Learning: Bridged the gap between Operating System theory and practical implementation 🔧 Tech Used: Python, OS concepts, file handling Would love your feedback! 👇 #OperatingSystems #Projects #ComputerScience #DataRecovery #TechProjects #StudentDeveloper #LearningByDoing