Optimizing Python Code with DataCamp's 'Writing Efficient Python Code' Course

🚀 Day 8/100 | #100DaysOfCode | Python String Power 🐍✨ Learning Python step by step, and today was all about understanding strings more deeply 🔍 Here’s what I practiced today 👇 🔹 String Indexing Accessing characters using positions — helped me understand how data is stored in strings. 🔹 swapcase() Turns lowercase into uppercase and vice versa — simple but very useful! 🔹 count() To check how many times a character or word appears in a string. 🔹 find() & index() Both help in finding positions of characters, but today I learned the key difference between them — great for debugging and validations. 🔹 split() & join() Breaking strings into words and joining them back — super important for real-world text processing. Small concepts, but they build a strong foundation for bigger programs 💯 Trying to stay consistent and improve a little every single day 🚀 Learning in public, learning with purpose 💻✨ #Python #100DaysOfCode #LearningPython #CodingJourney #DeveloperInMaking #TechSkills #Consistency #DailyLearning #FromBasicsToBuild

Day 31 – Data Structures Concept And Practice This week, I’m moving into Python, Data Structures, and Algorithms. Up until now, I’ve been learning how systems work. Now, I’m learning how data is organized and accessed efficiently. At the simplest level, data structures are just ways of storing and retrieving data so programs can work faster and smarter. Nothing fancy — just structure, order, and intent. In Python, one of the most powerful ways this happens is through hashing. This is what makes things like dictionaries (dict) so fast — instead of searching line by line, Python uses hashes to jump straight to the data it needs. This week will be about: Understanding what data structures really are (beyond theory) Seeing how Python implements them under the hood Learning why certain operations are fast and others are slow Writing Python with intention, not guesswork From tomorrow, I’ll start sharing: The challenges I face What confuses me What finally clicks Quick question for you 👀 Have you ever used a Python dictionary without knowing how it actually works underneath? Let’s learn it properly this time. #Day31 #LearningInPublic #Python #DataStructures #Algorithms #SoftwareEngineering #ConsistencyOverSpeed #BuildInPublic

🚀 Mastering Python isn’t about watching tutorials — it’s about solving real problems 💻🔥 I’ve been diving deep into 100+ solved & commented Python exercises that cover everything from fundamentals to advanced logic 🧠⚡ From loops and conditionals to strings, arrays, matrices, and real-world problem solving — this journey is all about learning by doing 📈🐍 If you’re serious about upgrading your Python skills, consistency + practice will always beat theory 💪📚 Build logic. Write code. Break things. Fix them. Repeat 🔁😎 Drop a 💬 if you’re learning Python or share this with someone who should start today 👇 #Python #PythonProgramming #LearnPython #CodingLife #DeveloperJourney #Programming #TechSkills #SoftwareDeveloper #CodingCommunity #100DaysOfCode #PythonProjects #CodeNewbie #DataScience #AI #MachineLearning

Day 19 | Python Learning Journey 🐍 Today, I practiced Python Sets and Set Methods, focusing on handling unique data efficiently. 🔹 What I learned: • Creating and updating sets • Adding & removing elements (add(), remove(), discard(), pop()) • Set operations: union, intersection, difference & symmetric difference • Checking subset relationships • Removing duplicates from lists using sets • Finding common elements between lists 📌 Key takeaway: Python sets make it easier and faster to work with unique values and comparisons. Consistent practice, steady progress 🚀 #Day19 #Python #PythonSets #LearningJourney #Coding

🚀 Day 11/100 | #100DaysOfCode 🐍 Learning Python Step by Step! Today I learned about Tuples in Python and practiced questions from all the topics I’ve covered till now. ✅ 🔹 Tuples are ordered collections just like lists, but they are immutable (their values cannot be changed). 🔹 Useful when we want to store data that should not be modified. 🔹 Learned and practiced:   • Creating tuples   • Accessing elements using index   • count() and index() methods   • Tuple unpacking Along with tuples, I also practiced questions on: ✔ Variables & Data Types ✔ Input & Output ✔ Operators ✔ Strings and String Functions ✔ Lists and List Operations Focusing on building strong basics before moving to advanced topics. 💪 Consistency > Speed. One concept at a time. 🚀 👉 Excited to learn more Python concepts in the coming days! #Python #100DaysOfCode #LearningInPublic #PythonBeginner #CodingJourney #DailyLearning #BuildInPublic #TechSkills #FutureDeveloper 💻🔥

🌙 Day 10/100 | #100DaysOfCode 🚀 Today I explored List Operations in Python — and honestly, lists are SUPER powerful! 🐍✨ Here’s what I learned today 👇 🔹 append() – Add an item at the end of the list 🔹 insert() – Add an item at a specific position 🔹 remove() – Remove an item by value 🔹 pop() – Remove an item by index 🔹 sort() – Arrange items in ascending order 🔹 reverse() – Reverse the whole list 🔹 len() – Find total number of items in the list Small operations, but they make data handling so much easier and cleaner 💻📊 Step by step, building strong basics in Python 💪 Consistency over perfection — always! 👉 Tomorrow, more learning, more growth 🚀 #Python #100DaysOfCode #LearningInPublic #PythonLists #CodingJourney #DeveloperLife #DailyLearning #TechSkills #Consistency

🐍py/D2🟩Python Comments, Variables & Naming Rules 🚀 Continuing my AI-Powered Python Learning Series, today I focused on the building blocks of clean, readable, and professional Python code 💻 Under the guidance of Mr. Satish Dhawale sir, Founder & CEO of SkillCourse, I learned how Python code communicates not just with machines, but also with humans through comments and well-structured variables. What I Learned Today 🧠 ✔ What comments are and why they are essential for code clarity & maintenance ✔ Single-line comments using # ✔ Multi-line comments using triple quotes (''' / """) ✔ Understanding variables and how Python stores data in memory ✔ Rules for naming variables (readable, meaningful & error-free) ✔ Best practices for writing clean and professional code 🎯 Learning these fundamentals is helping me build a strong Python foundation for Data, AI, and Automation 🚀 Excited to move ahead with D3 and apply these concepts practically! 🌟 #Day2 #Python #PythonBasics #LearningJourney #ArtificialIntelligence #SkillCourse #CleanCode #DataSkills #SatishDhawale #ContinuousLearning

🐍py/D2🟩Python Comments, Variables & Naming Rules 🚀 Continuing my AI-Powered Python Learning Series, today I focused on the building blocks of clean, readable, and professional Python code 💻 Under the guidance of Mr. Satish Dhawale sir, Founder & CEO of SkillCourse, I learned how Python code communicates not just with machines, but also with humans through comments and well-structured variables. What I Learned Today 🧠 ✔ What comments are and why they are essential for code clarity & maintenance ✔ Single-line comments using # ✔ Multi-line comments using triple quotes (''' / """) ✔ Understanding variables and how Python stores data in memory ✔ Rules for naming variables (readable, meaningful & error-free) ✔ Best practices for writing clean and professional code 🎯 Learning these fundamentals is helping me build a strong Python foundation for Data, AI, and Automation 🚀 Excited to move ahead with D3 and apply these concepts practically! 🌟 #Day2 #Python #PythonBasics #LearningJourney #ArtificialIntelligence #SkillCourse #CleanCode #DataSkills #SatishDhawale #ContinuousLearning

This Python code doesn't do what it looks like it does: 𝚗𝚊𝚖𝚎 = "𝚊𝚕𝚒𝚌𝚎" 𝚗𝚊𝚖𝚎.𝚞𝚙𝚙𝚎𝚛() 𝚙𝚛𝚒𝚗𝚝(𝚗𝚊𝚖𝚎) # Still "alice" The call to 𝚞𝚙𝚙𝚎𝚛() didn't fail. It ran perfectly. But 𝚗𝚊𝚖𝚎 is unchanged. Python strings are 𝗶𝗺𝗺𝘂𝘁𝗮𝗯𝗹𝗲. When you call 𝚞𝚙𝚙𝚎𝚛(), 𝚕𝚘𝚠𝚎𝚛(), 𝚛𝚎𝚙𝚕𝚊𝚌𝚎(), or any other string method, Python doesn't modify your string. It builds an entirely new one and hands it back. The original? Untouched. Still sitting in memory, exactly as you created it. 𝗧𝗵𝗶𝘀 𝗶𝘀 𝗶𝗻𝘁𝗲𝗻𝘁𝗶𝗼𝗻𝗮𝗹. Immutability means strings can serve as dictionary keys—because Python guarantees the key won't change out from under you. It means two threads can read the same string without a lock. It means Python can share identical strings in memory (a trick called "interning"). 𝗧𝗵𝗲 𝗳𝗶𝘅 𝗶𝘀 𝘀𝗶𝗺𝗽𝗹𝗲: 𝚗𝚊𝚖𝚎 = 𝚗𝚊𝚖𝚎.𝚞𝚙𝚙𝚎𝚛() This rebinds the variable to the new string. The old one gets garbage collected. Once you internalize this—that string methods 𝘳𝘦𝘵𝘶𝘳𝘯 new strings rather than 𝘮𝘰𝘥𝘪𝘧𝘺 existing ones—a whole category of bugs disappears from your code. 𝘍𝘳𝘰𝘮 𝘮𝘺 𝘶𝘱𝘤𝘰𝘮𝘪𝘯𝘨 𝘣𝘰𝘰𝘬 "𝘡𝘦𝘳𝘰 𝘵𝘰 𝘈𝘐 𝘌𝘯𝘨𝘪𝘯𝘦𝘦𝘳: 𝘗𝘺𝘵𝘩𝘰𝘯 𝘍𝘰𝘶𝘯𝘥𝘢𝘵𝘪𝘰𝘯𝘴." 𝘚𝘶𝘣𝘴𝘤𝘳𝘪𝘣𝘦 𝘵𝘰 𝘮𝘺 𝘚𝘶𝘣𝘴𝘵𝘢𝘤𝘬 𝘧𝘰𝘳 𝘤𝘩𝘢𝘱𝘵𝘦𝘳𝘴 𝘭𝘪𝘬𝘦 𝘵𝘩𝘪𝘴 𝘪𝘯 𝘺𝘰𝘶𝘳 𝘪𝘯𝘣𝘰𝘹. https://lnkd.in/enBk-nF4 #Python #Programming #LearnToCode #SoftwareDevelopment

Had a great session on Introduction to Lists in Python 🐍 We discussed why lists are so important, how to create them, how indexing (including negative indexing) works, and explored some useful list methods. We also practice iterating over lists and solved a few questions together. The session had active participation and engaging discussions among the 3 of us 😅 (count doesn't matter, participation does), I am glad I could help clear doubts and make the concepts easier to understand 💡🙌 🔗 Here's the Colab link for you to practice the questions discussed during the session: https://lnkd.in/gu_G4VHV 📽️ Sharing the session recording here for anyone who wants to learn or revise: https://lnkd.in/gcUh_eys 🔗 GitHub Link for the assignments: https://lnkd.in/grGDz464 If you have any questions or suggestions, feel free to drop the in the comments - happy to connect and help! #Python #Learning #Teaching #PythonLists #ProgrammingBasics