Computer Engineering
| Year | Course | Description | Score |
|---|---|---|---|
| I | Engineering Mathematics I | Linear Eqn and their application in engg fields. Eigen values and vectors, algebraic and transcendental eqns, error analysis and approximations, partial differential eqns and optimization problems. | 87 |
| I | Engineering Mathematics II | Design and analysis of continuous and discrete system using Fourier series and harmonic analysis. Differential and Integral Calculus. Multiple integrals. | 83 |
| II | Discrete Structures | Permutations and Combinations, Discrete Probability | 70 |
| II | Engineering Mathematics III | Linear Differential Equations and applications. Fourier Transform, Z transform. Statistics and Probability- central tendency, std deviation, variance and covariance, Probabiltiy density functions, prob distributions, and test of hypothesis. Vector Differential and Integral Calculus and applications. Complex variables. | 78 |
| III | Emplo. Ski. Deve. Lab | Employability Skills Development Lab
Technical competence required for problem solving. Understanding employers requirements and translating business decisions to code. Understanding professional and group behavioral ethics. |
96 |
| IV | Design & Analysis of Algo |
Design and Analysis of Algorithms Complexity theory, programming paradigms, parallel and concurrent algorithms. Case studies. |
80 |
| IV | Prin. of Modern Compl. Design |
Principles of Modern Compiler Design Parsing- Syntax analysis, grammars, parsers. Syntax Translation Schemes. Code Generation and optimizations. Language specific (OOP languages) compilation. Parallel and distributed compilers. |
86 |
| IV | High Performance Computing | Parallel programming. Paradigms in HPC. Synchronization and related algorithms. HPC case studies, applications and tools. | 75 |
| IV | Project |
Final Year Project Unsupervised Machine Learning, Natural Language Processing, Text Mining and analysis, Design and Implementation in a functional programming language-Python |
95 |
| IV | Data Mining Tech. & Appl. |
Data Mining Technologies and Applications |
66 |
Notes
I have no idea why the abbreviations are so unintellegible.
Data Mining Tech. & Appl. was a subject which was graded very poorly.