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Software-Defined Networking (SDN) is a modern networking approach that separates the control plane from the data plane, allowing centralized and programmable network management. Traditional networks rely heavily on manual configurations and hardware-based control, which limits flexibility and increases operational complexity. SDN introduces a centralized controller that dynamically manages network behavior through software-based policies. This architectural shift enables network administrators to design, deploy, and modify network services quickly and efficiently. By using open protocols and standardized interfaces, SDN improves interoperability between network devices from different vendors. These features make SDN a strong foundation for building autonomous network systems that can adapt to changing traffic conditions without constant human intervention. Autonomous network management refers to networks that can monitor, analyze, and optimize their own performance with minimal hum...

Data Science and Machine Learning are closely connected fields but serve different purposes in the world of technology and analytics. Data Science focuses on gathering, cleaning, analyzing, and visualizing data to extract meaningful insights that support decision-making. Machine Learning, on the other hand, is a subset of artificial intelligence designed to create systems that learn patterns from data and make predictions. While Machine Learning algorithms are often used within Data Science projects, Data Science also includes statistics, data engineering, domain knowledge, and storytelling. Understanding the differences between these two fields helps organizations and students choose the right approach for problem-solving, innovation, and career specialization.     Data Science has a broad scope that covers the entire data lifecycle—from data collection and preparation to interpretation and communication of results. It aims to uncover hidden trends and answer analytical ques...