Mastering Python with Problem-Solving Skills

Using #AI while studying #Python? Don’t let it do the thinking for you. Here are some tips from Mark Smith on how to use LLMs while actually learning Python: • Don’t ask it to write your code. • Try solving problems yourself first. • Use it to get you unstuck, not replace your efforts. • Ask for explanations or critique (but don’t trust blindly). When learning, use AI as a teacher – not a pair programmer. Don’t let it do the thinking for you. Watch the full talk: https://lnkd.in/ex9yu4TM

Most people don’t fail at learning Python… they fail at following a clear roadmap. Most people start learning Python with excitement… and quit within a few weeks. Not because Python is hard — but because there’s no clear direction. What I found interesting is this: a simple 15-day roadmap can completely change how you learn. Instead of overthinking, it focuses on execution: Day 1 → Basics & setup Day 3 → Logic building with loops Day 7 → Real data structures Day 10+ → OOP & real-world concepts Day 15 → Intro to Machine Learning No fluff. Just progress. The biggest shift? You stop “watching tutorials” and start solving problems daily. Because in tech, your growth is directly proportional to the problems you solve. If you're stuck in tutorial hell, try this: Learn less. Practice more. Repeat daily. That’s how beginners turn into developers. Connect with Himanshu Choure for more #PythonLearning #CodeNewbie #LearnProgramming #DevelopersLife #TechCareer #CodingMotivation #BuildInPublic #AI #MachineLearning #SkillBasedLearning

Most beginners think learning Python = learning how to code. That used to be true. Now AI can write a big part of your code. But it still can’t decide: what to build, how to structure it, and what trade-offs to make. That’s what I showed students today — how Python actually works in real products. Because developers who only write code will struggle. Developers who think will stand out. #python #backend #softwareengineering #ai #programming #itcareer #students #learning #tech #development

Python continues to be one of the most in-demand languages, especially in the context of AI. For those at the beginning of their careers, building strong fundamentals is key to using it confidently in practice. This selection of five highly rated Python books helps develop that foundation through clear explanations and hands-on learning. Each book takes a different approach — from structured lessons to real projects, automation tasks, and disciplined practice. The right choice depends on how you learn best and what you want to build. Pick one that fits your goals, stay consistent, and start coding. https://lnkd.in/dX-JS2bM #Pyton #AI #books

Nobody told me learning Python would feel this personal. I started because I was frustrated. The tools around me were outdated, the processes were slow, and I kept thinking there has to be a better way. So I taught myself. After work. On weekends. With no one checking on me. Here's what I learned: motivation that comes from frustration is actually very powerful. It doesn't fade the way excitement does. If you're learning something new right now and it's hard — check if frustration is driving you. It might be the most sustainable fuel you have. #SelfLearning #Python #DataScience

Learning Python has shown me that coding is not only about syntax — it is about solving problems step by step. One thing I appreciate about Python is how readable and beginner-friendly it is, while still being powerful enough for automation, data analysis, testing, and AI. Today’s reminder: even writing a small script that saves 10 minutes of manual work is progress. Small improvements create big results over time. Currently focusing on growing my skills in Python and automation, one day at a time. 🚀 #Python #CodingJourney #Automation #LearningEveryday #TechSkills #SoftwareTesting #CareerGrowth

🚀Python became easier the moment I stopped just watching and started writing. While learning Python, I realized passive learning wasn't helping much. So I switched to creating my own handwritten notes - and that changed everything. Here's how I approached it: Simplified every concept in my own words Focused on writing logic instead of memorizing syntax Practiced with small, clear examples My notes include: Variables & Data Types ✔ Loops & Conditional Statements ✓ Functions ✓ Lists, Tuples, Sets & Dictionaries ✓ Exception Handling ✔ Basic OOP concepts This one habit helped me: ✓ Build strong fundamentals ✓ Retain concepts for longer ✔ Revise quickly before interviews Sometimes, going back to basics is the smartest move you can make. If you're learning Python, try this approach - it might work for you too. Follow Neeraj Tiwari for more content. #Python #Programming #CodingJourney #Learning #TechSkills #CareerGrowth

Most people fail in Python not because it’s hard… but because they ignore the basics. I’ve realized one simple thing — strong foundation = fast growth 🚀 If you’re starting your Python journey, this is the phase that matters the most 👇 You begin with understanding what Python really is and why it’s used everywhere today. Then comes setting up your environment — VS Code or PyCharm, whatever feels comfortable. But the real learning starts here: You understand how variables work How different data types behave (int, float, string, boolean) How type casting changes data from one form to another How input and output actually make programs interactive And how operators (arithmetic, logical, comparison, assignment) control the logic These are not just topics… they are the building blocks of every program you’ll ever write. And here’s the truth 👇 If you skip this part, you’ll struggle later. If you master this part, everything else becomes easier. So instead of rushing, start practicing small: Try building a simple calculator Try writing an even/odd checker These may look basic, but they sharpen your thinking and problem-solving. 💡 My takeaway: Don’t chase advanced topics too early. Focus on clarity, not speed. Because in coding, slow learning at the start = faster growth later. Are you still building your basics or already jumped ahead? 👇 #Python #CodingJourney #LearnToCode #ProgrammingBasics #TechLearning #CareerGrowth

If you’re still learning Python without these AI repos… you’re already behind in 2026 Everyone is learning Python. But very few people are learning how to build real AI systems. The difference? Top developers today are not coding from scratch anymore. They’re using: - Multi-agent frameworks - Typed AI pipelines - CPU-efficient models These Python AI repos are doing 80% of the heavy lifting or actually learning how to build products? Because in 2026, companies don’t hire people who “know Python”. They hire people who can ship AI systems If you want to go beyond tutorials and actually build real projects, join our 1:1 Python Mentorship Program: https://lnkd.in/dpHv3i4p #Zerotoknowing #Python #AI #coding

Most people start learning Python… but quit halfway. Python isn’t difficult — the real problem is unstructured learning. Instead of jumping between random tutorials, I focused on building strong fundamentals like variables, loops, functions, and consistent practice. That’s when things finally clicked. Good notes are underrated. When you write and revise your own Python notes, concepts stay with you longer, and coding becomes much easier. From basic syntax to real-world use cases like web development, automation, and AI — Python opens doors everywhere. If you’re just starting, don’t rush. Focus on clarity, practice daily, and build small projects. Remember: consistency beats intensity. I’ve shared my Python notes to help you learn faster and avoid common mistakes. 📌 Connect with Himanshu Choure for more #Python #Coding #Programming #LearnToCode #PythonNotes #Developer #Tech #100DaysOfCode #CodingJourney #SoftwareDevelopment