JEMTEC

  Quantum Machine Learning (QML) is an emerging interdisciplinary field that combines the computational principles of quantum computing with modern machine learning (ML). While classical ML relies on traditional digital computing models, QML utilizes quantum mechanical phenomena such as superposition , entanglement , and quantum parallelism to potentially accelerate learning and inference processes. With the rapid advancement of quantum processors by companies such as IBM, Google, and others, QML has become one of the most promising frontiers in Artificial Intelligence research. At its core, QML seeks to use quantum computers to perform ML tasks faster than classical systems or to solve problems that are computationally intractable today. Classical algorithms often suffer from the “curse of dimensionality,” especially when dealing with extremely large datasets or high-dimensional feature spaces. Quantum systems, however, operate naturally in high-dimensional Hilbert spaces, whi...

  Balancing professional courses like CA, CS, or CMA along with a B.Com degree can feel like juggling fire, books, and expectations all at once. But the truth is, thousands of students do it every year — and succeed beautifully. With the right plan, mindset, and daily habits, you can manage both without burning out. Here’s a practical guide to help you navigate this double journey. 1. Start With a Realistic Plan The first step is to understand one simple thing: you can’t study everything at once. Each of these courses—CA, CS, and CMA—has multiple levels and demands serious preparation. Make a schedule that divides your day clearly into college studies, coaching/self-study, and revision hours. For example: Morning: Concept study for CA/CS/CMA Afternoon: College classes Evening: Revision + Assignments Consistency matters more than spending 10 hours in one stretch. 2. Choose One Professional Course First Many students try to enroll in all thre...