M.Tech in Computational Engineering and Networking(PDE Constrained Optimisation)Amrita Vishwa Vidyapeetham
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Computational Engineering uses techniques of applied mathematics and computer science for development of problem-solving methodologies and robust tools. These, in turn, become building blocks for solutions to scientific and engineering problems of ever-increasing complexity.
Computational Engineering differs from mathematics and computer science in that analysis and methodologies are directed specifically at the solution of problem classes from science and engineering. Detailed knowledge of and substantial collaboration with these disciplines is generally required.
Computation simulations enable the study of complex systems and natural phenomena that would be almost impossible to study by direct experimentation. The quest for ever-higher levels of detail and realism in such simulations requires enormous computational capacity. This has provided the impetus for dramatic breakthroughs in computer algorithms and architectures. Due to these advances computational scientists and engineers are now able to solve large-scale problems that were once thought intractable.
Computational Linear Algebra and Applications
Engineering Modeling and Partial Differential Equations
Computational Optimization Theory - Linear and Non-Linear Methods
Advanced Data Structures and Algorithms
Computational Statistics and Data Mining
Iterative Methods for Sparse Linear Systems
Essentials of Computer Architecture and Software Engineering
Advanced Signal Processing using Wavelets
Computer Networks and High Performance Computing
Natural Language Processing