Week 2 of #100DaysOfCode — done. 🎉 This week I focused on going deeper into Python. I started thinking less about just writing code, and more about writing better code. Focused on: 📊 Data Structures → Sets → Dictionaries ⚠️ Exceptions → Understanding errors → Handling them properly 🧪 Test-Driven Development → Writing tests before code → Thinking more about code reliability I’ve structured my learning into notes and practical examples to better understand the concepts : https://lnkd.in/epaBymnJ 14 days down. Staying consistent. 💻 #100DaysOfCode #Python #LearningInPublic #CodingJourney

90% people get this WRONG… will you? This looks easy… but there’s a twist hidden in the logic 😏 Only real Python pros will catch it 🧠💻 👉 Drop your answer (A/B/C/D) in comments No cheating ❌ Try first! 🚀 Follow us for more mind-bending Python challenges 📚 Want to learn Advanced Python step-by-step? Check out our books — Link in Bio #Python #PythonChallenge #CodingChallenge #LearnPython #PythonProgramming

💡 What I Learned About Python Basics Today When I started Python, I thought it was just a simple language. But I realized — simplicity is its biggest strength. 🔹 Easy syntax 🔹 Powerful libraries 🔹 Used in AI, Web, Automation Example: Instead of writing complex code, Python lets you solve problems in fewer lines. 👉 That’s why beginners AND professionals love it. 📌 My takeaway: Focus on logic, not just syntax. #Python #Coding #SoftwareDevelopment #Beginners #LearnToCode

Today I focused on strengthening my Python fundamentals, and here’s what I learned: 🔹 Tuple Ordered & immutable collection Allows duplicate values Useful for fixed data 🔹 Set Unordered collection of unique elements Automatically removes duplicates Helpful in data cleaning 🔹 Set Operations Union → Combine all elements Intersection → Find common elements Difference → Unique elements from one set Symmetric Difference → Non-common elements 💡 Key Learning: Data cleaning and comparison become much easier using sets in Python. 👉 Small step every day = Big growth in future 👉 Open to feedback and suggestions 👏 #Python #DataAnalytics #LearningJourney #100DaysOfCode #BeginnerToPro

Writing working Python code is easy. Building resilient systems is not. Brian Allbee, author of Hands-On Software Engineering with Python, joins Deep Engineering live for a conversation on what it actually takes to build Python systems that hold up under real-world pressure. From systems thinking and architectural decisions to testing, CI/CD, and cloud-ready design, this is a session for Python developers who are ready to grow beyond implementation. 📅 Saturday, 18 April ⏰ 12 PM ET 🎟 Free to attend Register here: https://lnkd.in/g-gE9gnu #Python #SoftwareEngineering #DeepEngineering #

𝗗𝗮𝘆 𝟵/𝟯𝟬 Instead of forcing my old coding habits into Python, I’m leaning into how the language handles data natively. Why write four lines of code when you can write one? 1. 𝗧𝗵𝗲 𝗦𝘁𝗮𝗻𝗱𝗮𝗿𝗱 𝗪𝗮𝘆 (Looping & Appending): nums = [1, 2, 3, 4] squared = [] for n in nums: squared.append(n * n) 2. 𝗧𝗵𝗲 𝗠𝗼𝗱𝗲𝗿𝗻 Approach 🚀: squared = [n * n for n in nums] 👉🏻It’s cleaner, faster, and much more intuitive. These are the small details that make the Python journey so satisfying🤌🏻 At what point do you find List Comprehensions become too complex? Do you stick to them for simple one-liners, or use them for nested logic too? #Python #30daysofcode #CodingJourney #Day9 #SoftwareDevelopment

🚀 Day 2/100 – Python & DSA Journey Today I focused on applying basics to a real problem. 🔹 Problem: Find the area of a triangle Instead of just memorizing the formula, I implemented it using Python by taking user input and performing calculations. Formula used: Area = (1/2) × base × height What I learned today: ✔ How to take multiple inputs from the user ✔ Converting input into the correct data type (float) ✔ Performing mathematical operations in Python ✔ Writing cleaner output using f-strings This may look simple, but it’s helping me build the foundation for problem solving.

🚀 Day 2: Understanding Decision-Making in Python (if-else) Continuing my journey in Data Science with Python, today I focused on one of the most fundamental concepts in programming — control structures (if-else). 📌 Topics Covered Today: ->if statements ->if-else conditions ->if-elif-else ladder ->Comparison operators (>, <, ==, !=) ->💻 Practiced writing conditions to make decisions based on input values. ⚠️ One challenge I faced: I initially found it confusing to structure multiple conditions using elif, but practicing different examples helped clarify the logic. 📊 Key Takeaways: Programming is not just about syntax — it’s about logical thinking if-else helps in making decisions based on conditions Small mistakes (like indentation) can affect output significantly 🎯 Next Step: Moving towards loops and understanding repetition in programming. 📌 Would appreciate suggestions: What are the best ways to improve logic-building in Python? #Day2 #Python #DataScience #LearningJourney #Coding #JupyterNotebook

Master the art of 2D arrays/lists in Python with ease. Discover everything you need to know to create 2D arrays and lists from scratch in Python. Learn how to define, index, and manipulate 2D data structures in Python to enhance your coding skills. Read the full article 👉 https://lnkd.in/dWGgRENZ #Python #ITfreshers #PythonLists #Datastructures #TechLab Code. Learn. Build. — TechLab by Neeraj

🔁 Python Fundamentals Revision Continuing my Python revision to strengthen core concepts 🐍 In this session, I focused on: ✔️ Syntax & Semantics ✔️ Variables ✔️ Data Types ✔️ Operators Revisiting these fundamentals is helping me improve code clarity and avoid common mistakes. I’ve documented my practice in a Jupyter Notebook and shared it as a PDF to keep track of my learning journey. Strong basics = Better problem solving 💡 Next step: diving deeper into control flow and real-world problem solving 🚀 #Python #Revision #Programming #DataAnalytics #LearningJourney #Coding