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
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Is Python still worth learning in 2026? 🤔 Most students think it’s just a “beginner language”… but the truth is far more powerful. Swipe to know the real picture of Python in today’s job market 👉 #Python2026 #IsPythonWorthIt #PythonDeveloper #TechCareer #FutureProofSkills #SCOPE
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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
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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 The tools around me were outdated, the processes were slow, and I kept thinking there has to be a better way.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
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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
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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
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This changed how I think about learning. I used to set goals like: “Learn Python” “Get into AI/ML” But nothing really stuck. Because goals feel exciting. 👉 Systems feel boring. But systems are what actually move you forward. Like: - Practicing 30 minutes daily - Building small projects consistently - Reviewing mistakes regularly That’s when I realized: 👉 Progress doesn’t come from motivation 👉 It comes from structure Now I focus less on big goals… And more on small systems that repeat daily. 💬 Do you focus more on goals or systems right now? #Books #AtomicHabits #LearningInPublic #GrowthMindset #Consistency
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Python’s __slots__ — why it matters: By default, Python classes allow you to add attributes dynamically. That flexibility is powerful, but it comes at a memory cost, especially in large, object‑heavy systems. Using __slots__ restricts dynamic attribute creation, meaning your objects only hold the attributes you define. The result? Lower memory usage, faster access, and more efficient performance when scaling applications. Think of it as giving your class a blueprint that keeps things lean and optimized. Perfect for developers building systems with thousands (or millions) of objects. At IT Learning AI, we simplify these advanced concepts so you can write smarter, more efficient code without the overwhelm. Want to dive deeper into Python’s hidden gems? Explore tutorials, guides, and practical coding insights at https://itlearning.ai 🔗 Learn. Apply. Grow. With IT Learning AI. #itlearningai #pythonprogramming #learnpython #pythontips #pythonbasics #pythonforbeginners #codesmarter #codedaily #programmerslife #codingisfun #techcommunity #buildwithpython #growwithtech
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Day 6 of learning ML Still working on Python. Not rushing into models yet — trying to get comfortable with the basics first. Practicing things like: • Lists, sets and dictionaries. • Loops and conditions • Writing cleaner code Feels slow, but skipping this would probably make things harder later. Consistency > Perfection
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There are many different students in today's classrooms with many different abilities. And AI tools can make a big difference in their learning experiences. In this guide, Omotayo walks you through building a Speech-to-Text & Text-to-Speech accessibility tool in Python. https://lnkd.in/gqyk9eeU
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🚀 I built linear regression from scratch. Then I wrote about it. No libraries. Just Python, NumPy, and gradient descent. 📖 Read the full blog on Medium → https://lnkd.in/gcq7t6CW This is what deep learning really looks like, starting with one variable and understanding every line of code. #MachineLearning #FromScratch #Python #LinearRegression #Blog
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💯 on the need to write your own code. If you let the LLM do it, you're missing out on all the fun. Best advice in this clip: Don't delegate your thinking."