Choosing Python or JavaScript for your first programming language

You can know Python. You can know Flask. You can even know databases, REST, and Docker... And still not land a backend job. Here’s the hard truth no tutorial tells you 🧵 Most developers confuse consuming information with gaining experience. But recruiters don’t hire what you know — they hire what you’ve done. You can’t “tutorial” your way into a real job. You need projects. Knowing what an API is is not the same as building one that scales Knowing what authentication means is not the same as implementing JWT securely Knowing SQL is not the same as designing schemas that actually work You dont learn those from videos. U learn them by shipping code Why most never make it past this stage Because building from scratch is hard. It’s confusing. It’s messy. You’ll fail a lot. But that’s exactly what prepares you for real backend work. The solution - Build one project a day. - Even small ones. - Each one teaches you something new: databases, routes, errors, and deployment. Do this for 30 days, and you’ll feel the shift. From “learner” → “engineer.” That’s why we built the Python30 Challenge ✅ 30 projects in 30 days ✅ DSA interview prep ✅ Job-ready backend toolkit ✅ Access to resume, mock interviews & community Stop studying like a beginner. Start shipping like a backend engineer https://lnkd.in/dEsaR2bN

State of Python 2025: Web Development Makes a Comeback! The latest Python Developers Survey, a collaboration between the Python Software Foundation and  JetBrains, has captured insights from over 30,000 developers worldwide — revealing some surprising  shifts in how Python is being used in 2025. Key Highlights: 50% of Python devs have less than 2 years of professional coding experience — showing Python’s unmatched accessibility for newcomers. Data science remains dominant, with 51% using Python for data exploration & processing. Web development is back! Usage jumped from 42% in 2023 to 46% in 2025, fueled by frameworks  like FastAPI, now adopted by 38% of developers. Outdated Python versions are costing businesses millions — upgrading could boost performance by up to 42%. Rust is now powering up Python: nearly 1/3 of new native code on PyPI uses Rust for speed and efficiency.  What’s next for Python: Free-threaded Python (v3.14) is coming — removing the GIL and unlocking true parallel processing. AI coding assistants are going mainstream — 49% of devs plan to use them soon.  Native mobile apps with Python are becoming a reality, with official iOS and Android support in the works! “Python’s future is being written by a new generation — one that’s curious, bold, and ready to take Python everywhere.” — Michael Kennedy, Python Software Foundation Fellow From AI and data to web and mobile, Python continues to evolve — proving once again why it remains the heartbeat of modern development. #Python #WebDevelopment #DataScience #AI #Developers #Programming #JetBrains #PythonSoftwareFoundation #Rust #Technology #Innovation #Coding

🚀 JavaScript vs Python vs C — Same Logic, Different Worlds 🌍 Ever noticed how every programmer has that one favorite language? For some, it’s C — the tough, no-nonsense classic. For others, Python — clean, chill, and beginner-friendly. And then there’s JavaScript — the wild web genius that runs everything online 😄 Let’s break them down 👇 ⚙️ C Language – The OG of Programming 🧠 Think of C as the grandfather of modern languages — strict, fast, and very close to the computer’s hardware. Used in: Operating systems (like Linux & Windows) Embedded systems (like cars, smartwatches, machines) 💡 If computers had a heartbeat, it’d probably be coded in C. 🐍 Python – The Smooth Talker ✨ Python is that friendly language that says: “Don’t worry, I got you.” It’s simple to read, almost like English, and super powerful for: AI & Machine Learning Data Science & Automation Web apps (Django, Flask) 💡 If coding was conversation, Python would be the best listener. 🌐 JavaScript – The Web Magician 💻 JavaScript makes the internet move! Every button, animation, or interactive website — JS is working behind the scenes. With Node.js, it can even run on servers too. 💡 If the web was a concert, JavaScript would be the lead guitarist 🎸 🔁 What’s Common Among Them Even though they look different, all three share the same brain: Variables Loops (for, while) Conditions (if, else) Functions (to reuse code) In short — the logic stays the same, the syntax just changes. Learning programming isn’t about choosing one language — it’s about learning how to think. Once you master logic, switching languages feels like changing keyboards — the music stays the same 🎶 What’s your favorite language — the powerful C, the smooth Python, or the creative JavaScript? Drop it below 👇 #CodingJourney #ProgrammersLife #CProgramming #Python #JavaScript #Developers #Learning #TechHumor #StudentCoder #STEM

You’ve learned backend. - You’ve watched tutorials. - You’ve built a few mini-projects. But you’re still not getting backend job offers Let’s fix that 👇 The real problem isn’t your skill. It’s proof. Recruiters don’t hire you for what you “know.” They hire you for what you can show. If you can’t point to deployed APIs, databases, and production-ready logic, they can’t trust you yet. Learning is not equal to Doing. You’ve probably built projects inside tutorials. But did you ever build something on your own — from scratch, with your own decisions, bugs, and refactors? That’s how you become a real backend engineer. Here’s the roadmap that works. ✅ Build 30 backend projects in 30 days. ✅ Each project focuses on one key concept (APIs, authentication, file upload, caching, etc.) ✅ Then, optimize your resume and learn DSA for interviews. Do this for 90 days — and you’ll be unstoppable. We built a challenge to guide you step-by-step. It’s a 90-Day Python challenge You’ll: - Ship 30 projects in 30 days - Study DSA & system design - Prepare with resume kits, mock interviews & community 2K+ have escaped “tutorial hell” through this: https://lnkd.in/d5iN7AX6

Thousands of developers know Python. But only a handful get hired for backend roles. Here’s the truth: → Companies don’t hire Python learners. → They hire Python builders. Let’s talk about how to stand out — even without a CS degree 🧵 Stop chasing random tutorials. Every hour spent watching a “Python for Beginners” video is an hour not spent building. Tutorials give you knowledge. Projects give you proof. And in hiring, proof beats knowledge every time. Build what companies actually use. Skip the “guess-the-number” games. Start with projects that mirror real systems: ✅ Authentication APIs ✅ CRUD apps with databases ✅ File upload services ✅ Notification systems ✅ Job board or blog APIs When you can build those, your GitHub becomes your portfolio, not just code storage. Document everything. Each project should come with: - A README - Clear setup steps - API documentation Why? Because engineers who write and explain well are rare. And rare = valuable. Turn learning into momentum. Don’t overthink your next step. - Pick a project. - Ship it. - Repeat. That’s exactly how Python30 works — 30 real Python backend projects in 30 days. You don’t just learn — you transform. By the end of it, you’ll have: → 30+ projects to show recruiters → Confidence in backend fundamentals → A clear, job-ready portfolio Start your 90-day path to a Python backend role 👇 👉 https://lnkd.in/dEsaR2bN

🚀 𝟭𝟮 𝗣𝘆𝘁𝗵𝗼𝗻 𝗦𝗸𝗶𝗹𝗹𝘀 𝗘𝘃𝗲𝗿𝘆 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿 𝗦𝗵𝗼𝘂𝗹𝗱 𝗠𝗮𝘀𝘁𝗲𝗿 𝗶𝗻 𝟮𝟬𝟮𝟱 Python isn’t just a programming language. It’s a problem-solving superpower when wielded the right way. There are two kinds of Python developers: Those who just write code Those who build, scale, and solve real-world problems The difference? Skills. 𝗛𝗲𝗿𝗲 𝗮𝗿𝗲 𝘁𝗵𝗲 𝟭𝟮 𝘀𝗸𝗶𝗹𝗹𝘀 𝘁𝗵𝗮𝘁 𝘀𝗲𝗽𝗮𝗿𝗮𝘁𝗲 𝗴𝗿𝗲𝗮𝘁 𝗣𝘆𝘁𝗵𝗼𝗻 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿𝘀: 1️⃣ Multi-Process Architecture 2️⃣ Python Framework Mastery (Django, Flask, FastAPI…) 3️⃣ Essential Python Libraries (Pandas, NumPy, Requests…) 4️⃣ Front-End Technologies (React, Angular, Vue…) 5️⃣ Machine Learning & AI 6️⃣ Deep Learning 7️⃣ Communication Skills 8️⃣ Version Control (Git, GitHub, GitLab…) 9️⃣ ORM Libraries (SQLAlchemy, Django ORM…) 🔟 Analytical Thinking 1️⃣1️⃣ Design Skills (System Design, Software Architecture) 1️⃣2️⃣ Core Python Expertise 💡 Pro tip: You don’t master everything overnight. Focus on one skill at a time, go deep, then move to the next. #Python #PythonDevelopment #FullStackDeveloper #MachineLearning #AI #DeepLearning #SoftwareEngineering #CodingLife #TechSkills #ClientSolutions #PythonTips #CareerGrowth #Programming #Innovation #TechForBusiness

Master Web Development in Python—Unlock Your Tech Potential. Are you ready to build powerful, scalable, and dynamic websites using one of the world’s most versatile programming languages? Whether you’re an aspiring developer, a tech professional upgrading your skills, or an organisation looking to train your team, it’s time to master web development in Python. 🌐 Learn how to: ✅ Build modern web apps with frameworks like Django & Flask ✅ Integrate APIs and databases seamlessly ✅ Optimise performance for real-world projects ✅ Gain the practical skills employers value most With Python leading the digital transformation wave, mastering it opens doors to limitless career opportunities in tech, AI, and automation. 📈 Don’t just code—create, innovate, and lead with Python. Start your journey today! 👉 #MasterWebDevelopmentInPython #PythonDevelopment #WebDevelopment #Programming #Coding #TechCareers #DigitalTransformation #PythonLearning #Upskill #CareerGrowth

Python vs JavaScript: What’s the Real Difference? A lot of students ask, Should I learn Python or JavaScript first? Here’s a simple breakdown: 1. Purpose & Use Cases:   --> Python → Used for AI, Data Science, Machine Learning, Automation, and backend (Django, Flask).   --> JavaScript → Used for Web Development, Frontend & Backend (Node.js), and interactive UIs. 2. Syntax & Learning Curve:    --> Python → Simple, beginner-friendly syntax (almost like English).   --> JavaScript → Slightly more complex with curly braces {} and function handling. --> If you’re new to coding, Python feels smoother. But JavaScript builds your web logic faster. 4. Runtime Environment:   --> Python runs on its own interpreter (CPython).   --> JavaScript runs inside browsers or Node.js — making it perfect for web apps. 5. Speed & Performance:    --> JavaScript (Node.js) is generally faster for web-related tasks.   --> Python can be slower but shines in data-heavy operations and research use cases. 6. Libraries & Ecosystem:   --> Python → Massive ecosystem for AI/ML (TensorFlow, Pandas, NumPy).   --> JavaScript → Huge web ecosystem with React, Express, Next.js, and more. 7. Community & Job Market: Both have huge global communities.   --> Python → More roles in AI, ML, Data Analytics, and Automation.   --> JavaScript → More jobs in Full Stack, Frontend, and Web Development. Finally, If you want to get into Web Development → Learn JavaScript. If you want to get into AI, Data, or Automation → Start with Python. Both are powerful. The real difference is in what you want to build. #NomadSkills #Python #JavaScript #FullStackDevelopment #DataScience #WebDevelopment #AI #MachineLearning #CodingJourney #LearnToCode #ProgrammingForBeginners #JobReadySkills #CareerGrowth #SkillDevelopment #InternshipOpportunities #StudentLearning

Python 3.13 is here, and it's bringing performance improvements that will change how we think about Python in production environments. The experimental JIT (Just-In-Time) compiler shows promising results with up to 2-9% performance gains in real-world applications. While this might seem modest, for data-intensive AI/ML workloads and backend services, this translates to significant cost savings and improved user experience. What excites me most: - Better error messages that actually help you debug faster - Improved type hinting support for more robust codebases - Enhanced asyncio performance for building scalable web services For full-stack developers using Python with frameworks like FastAPI or Django, these improvements mean your APIs can handle more concurrent requests with the same infrastructure. The typing improvements also make Python codebases more maintainable, especially in large teams where JavaScript developers transitioning to Python will find the experience more familiar and predictable. As Python continues to dominate in AI, data science, and backend development, these performance enhancements solidify its position as a language that can scale from prototyping to production seamlessly.