What is the difference between computer engineering & computer science and technology?

Computer Engineering is the marriage of Computer Science and Electrical Engineering. It focuses on computing in all forms, from microprocessors to embedded computing devices to laptop and desktop systems to supercomputers. As such, it concerns the electrical engineering considerations of how microprocessors function, are designed, and are optimized; how data is communicated among electronic components; how integrated systems of electronic components are designed Computer Science is the study of how data and instructions are processed, stored, communicated by computing devices. A modern descendant of Applied Mathematics and Electrical Engineering, Computer Science deals with algorithms for processing data, the symbolic representation of data and instructions, the design of instruction languages for processing data, techniques for writing software that process data on a variety of computing platforms, protocols for communicating data reliably and securely across networks, the organization of data in databases of various types and scales, the emulation of human intelligence and learning through computer algorithms, statistical modeling of data in large databases to support inference of trends.

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Computer Engineering is the combination of Computer Science and Electrical Engineering. It focuses on computing in all forms, from microprocessors to embedded computing devices to laptop and desktop systems to supercomputer. Computer Science is the study of how data and instructions are processed, stored, communicated by computing devices. A modern descendant of Applied Mathematics and Electrical Engineering, Computer Science deals with algorithms for processing data, the symbolic representation of data and instructions, the design of instruction languages for processing data, techniques for writing software that process data on a variety of computing platforms, protocols for communicating data reliably and securely across networks, the organization of data in databases of various types and scales, the emulation of human intelligence and learning through computer algorithms, statistical modeling of data in large databases to support inference of trends, and techniques for protecting the content and authenticity of data.

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