Computer science engineering is concerned with the study of the basic structure of how the software and hardware collaboratively perform its tasks. It is the task of computer science engineers to make sense of the mathematical formulae of the real world and convert it into a series of steps that the computer can follow. Computer science is traditionally more concerned with the theoretical underpinnings of computation and programming; thus one typically finds courses in programming, algorithms, numerical analysis (how do you guarantee a number produce by a computer program is accurate), and the theory of computation (what can and cannot in principle be computed). Computer science engineering is concerned with the theory of computing, programming languages, operating system, artificial intelligence, scientific computing, cryptography and computational complexity. Computer science is more about the theory of software, algorithms, data structures, networks, databases, etc.
Computer Science is one of the most profitable and competitive course to study. In comparison to other sectors, computer science graduates fetch higher salaries in the beginning.
Computer Engineering and Information Technology Labs are creatively and ergonomically designed, where students get an opportunity to develop their skills. The labs are fully networked. All computers have sophisticated and high-end-configurations, computing resources and software facility. Some of the labs are:
1. INTERNET LAB.
2. MAJOR PROJECT WORK LAB.
3. PROGRAMMING LAB.
4. JAVA PROGRAMMING LAB.
• It includes the knowledge of programming, data structures, digital logic, theoretical computer science, algorithms, computer networks, operating systems, web technologies, databases, computer architecture, etc.
• Study of how data and instructions are processed, stored, communicated by computing devices
• It deals with the algorithms for processing data, symbolic representation of data and instructions, design of instruction languages for processing data.
• 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
• Algorithmic analysis- creation, optimization and debugging of algorithms
• Software systems- the implementation of software, different environments, compilers and operating systems
• Theory- the basic theory of which tasks can be completed in computational manner and which cannot be completed
• Practice as computer professionals, conducting research and leading, designing, developing or maintaining projects in various technical areas
• Ability to design and conduct experiments, as well as to analyze and interpret data
• Ability to analyze a problem, and identify and define the computing requirements appropriate to its solution
• Ability to apply design and development principles in the construction of software systems of varying complexity
• Ability to identify, formulate and solve computer science and engineering problems and define the computing requirements appropriate to their solutions.