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Hacker IDE | New tool for learning Programming | Computer Science | AI | Framework 🤝 visit - https://lnkd.in/g-4f_D3P #programming #compiler #aiTutor #cs #math

Visualizing Dijkstra’s Algorithm makes it so much easier to understand how the shortest path is calculated in real time. From maps to network routing, this algorithm is everywhere in our daily tech life. Grateful to keep learning and exploring the beauty of algorithms step by step. 💻📍 Hashtags: #DijkstrasAlgorithm #DataStructures #Algorithms #ComputerScience #LearningJourney #TechStudent #Programming #VisualLearning #LinkedInTech

Computer programming is the art of precision. Not just because computers execute instructions literally. A missing character, an incorrect condition, or a misunderstood data type can change behavior completely or cause failure. At the same time, programming is not only about syntactic exactness. It also requires conceptual precision: choosing the right abstractions (and the right amount of them), defining clear interfaces, and reasoning carefully about edge cases, performance, and correctness over time. Code can be syntactically perfect and still be wrong if the underlying idea is vague or flawed. Programming is an art of precision at multiple levels: the symbols we write, the logic they encode, and the mental models we use to understand complex systems. Precision is not just a constraint imposed by machines, but a discipline that programmers actively cultivate. Till next time 😊 #Computing #SoftwareDevelopment #SoftwareEngineering #Coding #ComputerProgramming #Programming

Traditional Programming vs Machine Learning ⚙️🤖 • Rules-driven vs Data-driven • Fixed logic vs Learning systems • Simple problems vs Complex patterns Choosing the right approach makes all the difference. #Programming #MachineLearning #ArtificialIntelligence #TechLearning #DataDriven #SoftwareEngineering

**From Hand Calculations to Code Loops** In the past, mathematical series were calculated by hand. Scholars like Archimedes and later Newton spent days or months summing terms to approximate values such as π. Every extra term meant more time, more paper, and a higher risk of error. Some mathematical theories took years or decades to complete before programming languages and computers. A well-known example is The Four Color Theorem, which is a clear case: proposed in 1852, it resisted proof for over 120 years. In 1976, it was finally proven using a computer program that checked thousands of cases in a short time, something impossible to finish by hand. Lina Alsawadi #Mathematics #Programming

“The emerging picture from such studies is that ten thousand hours of practice is required to achieve the level of mastery associated with being a world-class expert—in anything,” writes the neurologist Daniel Levitin. — p. 40 www.arzugil.com https://lnkd.in/gag8C9BT https://lnkd.in/gH6wfGv8 #10000hours #cloudcomputing #professionalmode #programming

micro:bit is one of the most widely adopted coding platforms for children, with exposure across nearly 80% of primary schools. It lowers the barrier to entry with block-based coding, while offering a clear progression to Python and JavaScript — helping students focus on logic and problem-solving. One common misconception: micro:bit does not natively control motors or external sensors. To address this, we: - developed a custom in-house PCB - built a simplified API layer This allows students to remain in a familiar micro:bit environment while working on real robotic behaviours — without dealing with low-level electronics. The result: learning that is accessible, transferable, and closer to real-world product thinking.

#Day454_DSA:📘 Today’s Learning – DSA Insight Today I learned an interesting DSA concept while solving the “Add Digits” problem. Instead of repeatedly summing digits, there’s a mathematical pattern (Digital Root) that allows the solution to be found in constant time. It was a great reminder that sometimes the most efficient solutions come from understanding the math behind the problem, not just brute force logic. Small problems, but valuable insights 🚀 Consistently learning and improving one problem at a time. #DSA #ProblemSolving #LearningEveryday #LeetCode #Programming #Consistency #RajVikramaditya #TakeUForward

📘 Finding the LCM of Two Numbers – Made Simple! The LCM (Least Common Multiple) of two numbers is the smallest number that is a multiple of both. 🔢 Example: Find the LCM of 12 and 18 Multiples of 12 → 12, 24, 36, 48… Multiples of 18 → 18, 36, 54… ✅ The smallest common multiple is 36 👉 LCM(12, 18) = 36 💡 Why LCM matters? Used in scheduling problems Helps in adding fractions Important in mathematics, programming, and competitive exams Learning the basics step by step makes complex problems easier! 🚀 #Mathematics #LearningEveryday #LCM #ProblemSolving #Education #STEM

Learning Update: Core Memory Management Concepts in C++ I have completed learning and implementing key C++ memory management concepts through hands-on programming Shallow Copy – Copies object data by sharing the same memory reference. Deep Copy – Creates an independent copy with separate memory allocation. Inbuilt Shallow Copy – Default copy behavior provided by the compiler. Dynamic Array – Uses dynamic memory allocation to manage arrays at runtime. Swapping Techniques – Implemented multiple methods to exchange data efficiently. These concepts improved my understanding of memory behavior, copy control, and efficient data handling in C++.Continuing to strengthen my C++ fundamentals with practical problem solving. links: https://lnkd.in/gzcTfezE deep copy and inbuilt shallow copy https://lnkd.in/gixdMUHX dynamic array #CPlusPlus #CPP #MemoryManagement #ShallowCopy #DeepCopy #DynamicArray #Programming #LearningJourney