Python Learning: AI Tools vs Real Skill Acquisition

🐍📰 PyTorch vs Tensorflow for Your Python Deep Learning Project PyTorch vs Tensorflow: Which one should you use? Learn about these two popular deep learning libraries and how to choose the best one for your project #python

A year ago, learning Python meant writing scripts and building APIs. Today, it feels like I’m learning how to build systems that can think. That shift is real. With Agentic AI, Python is no longer just about: • functions • classes • frameworks It’s about creating workflows where: • an agent understands a problem • decides what to do next • calls APIs or tools • adapts based on results ⸻ I recently started exploring this space, and one thing stood out: 👉 You’re not just coding anymore 👉 You’re designing behavior ⸻ There are moments where: You write a piece of code… and the system responds in a way you didn’t explicitly program. That’s powerful. And honestly, a bit uncomfortable too. ⸻ Because now the challenge is not just: “How do I build this?” It becomes: • How do I guide this system? • How do I control its decisions? • How do I trust its output? ⸻ As someone working in integration and architecture, this feels like a major shift. We’re moving from: 👉 predictable systems to 👉 adaptive systems ⸻ And Python is right at the center of this change. ⸻ Curious — Are you still learning Python the traditional way, or exploring it through AI and agentic workflows? ⸻ #AgenticAI #Python #AI #SoftwareArchitecture #TechLearning #FutureOfTech

Just Published: Mastering Python for Machine Learning: A Practical, No-Nonsense Roadmap If you're someone who feels confused about where to start in Machine Learning, this guide is for you. I’ve broken down the journey into simple, practical steps 💡 No unnecessary theory. No confusion. Just a clear roadmap you can actually follow. Whether you're a beginner or someone restarting your ML journey, this will help you build a strong, real-world foundation. 👉 Read here: https://lnkd.in/gBKzWiUK I’d love to hear your thoughts and feedback! 🙌 #Python #MachineLearning #DataScience #AI #Learning #CareerGrowth

I started learning Python. Here's everything I've built into my brain so far day by day, concept by concept. → if / else statements Teaching the computer to make decisions. The moment this clicked, I felt like I was actually writing logic not just typing commands. → for loops & while loops Automation starts here. Instead of repeating myself, I let the code do the work. → logical operators Combining conditions with and, or, not. Simple but incredibly powerful once you see it in action. → arithmetic & comparison operators The foundation of every calculation and every decision in code. → operator precedence Python follows rules just like math. Understanding this saved me from confusing bugs. → formatted strings (f-strings) My favourite discovery so far. Clean, readable, dynamic text output in one line. → string methods .upper() .strip() .replace() .split() tools that make working with text feel effortless. → math functions Built-in tools like round(), abs(), pow() — Python does the heavy lifting. The biggest lesson so far? Confusion is not a sign you're failing. It's a sign you're learning. Every single concept above confused me at first. I stayed with it. I kept going. I'm sharing this publicly to hold myself accountable and because I know many people are quietly upskilling on the side without telling anyone. If that's you you're not alone. Keep going. 💪 What skill are you currently learning? Drop it in the comments. Let's inspire each other. 👇 #Python #LearningInPublic #CareerGrowth #SelfDevelopment #CodingJourney #GrowthMindset #ProfessionalDevelopment #TechSkills #100DaysOfCode #CodeNewbie

Everyone is learning Python. But almost no one knows how to use it with AI. That’s where the real opportunity is. Python isn’t just about syntax anymore. It’s the backbone of AI products. If you're learning Python, do this instead: → Build with AI from day one → Use tools like ChatGPT & Claude to speed up coding → Focus on solving real problems, not just tutorials Start with simple but powerful ideas: • Resume analyzer with AI feedback • Chatbot trained on your own data • Auto email writer for outreach • YouTube/blog summarizer • AI-powered finance tracker Learn APIs. That’s the real game. Python + APIs = Real-world AI apps Don’t chase perfection. Ship fast. 1 live project > 10 unfinished courses Document everything publicly. Your work will speak before you do. Right now, the edge is simple: Python + AI + Projects = Opportunities Don’t just learn Python. Build something with it. Connect Pushpendra Tripathi for more such content  Comment “Python70” and I’ll send the resource.

Tell your AI that you are beginner when learning Python! I recently asked AI to generate some simple code to reverse two virtual spreadsheet columns called ‘Name’ and ‘Type’. Instead of simply suggesting code in which the column list [‘Name’, ‘Type] is replaced by [‘Type’, ‘Name’], AI suggested a complex indexing trick that looks like [::-1]. Succinct coding, to be sure, but I could not decipher it without additional prompts! In another case, my AI provided some sample code in which a variable was defined after that variable was used! The Horror! When I asked why it made such a fundamental mistake, the AI complimented me on my “good eye” for catching the error and that it did not necessarily provide code in execution order. So, if you are just learning Python, always start your session with a good prompt to set the stage such as the following: "I am a total beginner learning Python. Please follow these rules for ALL Python code you write for me: 1. Write code in execution order. 2. Break every task into small, discrete steps. 3. Use simple, obvious variable names that describe what they contain 4. Add plenty of comments explaining what it happening in plain English 5. Avoid shortcuts, clever one-liners, or condensed syntax that experienced coders use 6. If there are multiple ways to do something, choose the most readable one, not the most efficient one 7. Before showing me code, double-check it runs in the correct order from top to bottom" For more tips, consider my new book "Automate Excel with Python". My publisher @No Starch Press is offering a free review chapter in case you were interested: https://lnkd.in/eS-WAVyV Good luck and good coding! #Excel, #Python, #pandas, #dataframes,#Productivity, #DataAnalysis, #Automation

🚀 Completed a 3-Hour Workshop: Python Using AI – By AI For Techies (BE10X) Glad to share that I participated in a 3-hour intensive workshop on “Python Using AI” by BE10X! ⏱️ Even within a short time, the session delivered powerful insights into how AI can transform the way we code and learn Python. 💡 Key Highlights: - Leveraging AI tools to assist in Python coding - Faster debugging and problem-solving techniques - Writing efficient code with AI support - Exploring real-world use cases of AI in development This workshop showed me that it’s not just about learning programming anymore — it’s about learning how to learn smarter with AI. As I continue my journey in AI/ML and cybersecurity, this was a great step toward building future-ready skills. 🚀 #Python #AI #ArtificialIntelligence #BE10X #TechWorkshop #Learning #FutureSkills #Coding

Day 13 of my Python learning journey Today I worked on a classic problem that looks simple, but teaches a very powerful idea. Problem: Sort 0s, 1s, and 2s (Dutch National Flag Problem) Given an array containing only 0, 1, and 2, sort it in-place. Example: arr = [2, 0, 2, 1, 1, 0] Output: [0, 0, 1, 1, 2, 2] What I learned today: Instead of using sorting functions, we can solve this in one pass using pointers. This problem is known as the Dutch National Flag problem. What is Dutch National Flag idea? This concept was given by Edsger Dijkstra. The idea comes from the Dutch flag, which has three colors: Red, White, Blue We map them like this: 0 → Red 1 → White 2 → Blue So the goal is to arrange elements in this order, just like the flag. How the logic works: We divide the array into three parts: Left → all 0s Middle → all 1s Right → all 2s And we maintain three pointers: low → where 0 should go mid → current element high → where 2 should go Code I wrote: arr = [2, 0, 2, 1, 1, 0] low = 0 mid = 0 high = len(arr) - 1 while mid <= high: if arr[mid] == 0: arr[low], arr[mid] = arr[mid], arr[low] low += 1 mid += 1 elif arr[mid] == 1: mid += 1 else: arr[mid], arr[high] = arr[high], arr[mid] high -= 1 print(arr) Problems I faced while coding this: At first I tried using sort(), but that defeats the purpose of the problem. I was confused about why we use three pointers instead of two. The condition mid <= high was tricky to understand. I also made mistakes while swapping, which broke the logic. What I finally understood: This algorithm processes each element only once. We don’t need extra space and no nested loops. Time and Space Complexity: Time Complexity: O(n) → single pass through the array Space Complexity: O(1) → in-place sorting Question: Why do we not increase mid when we swap with high? Today’s realization: Some problems are not about coding more, but about thinking in the right structure. #Python #DSA #Coding #Programming #LearningInPublic #100DaysOfCode #PythonProgramming

Users of Python Fundamentals, 2/e on O'Reilly: The new Lesson 5, Lists and Tuples, is live, and I am sending Lesson 06, Dictionaries and Sets, for processing right now. Should be live before the end of the week. https://lnkd.in/ePMpTP5t #Python Pearson Deitel & Associates