Our lab provides a diverse range of programming or algorithm modules which focuses on Competitive Programming and research-oriented implementation in Computer Vision. All of these courses are considered as internal training for motivated students.

This course concentrates on learning the basics of programming languages which is the foundations for further studies in IT. The course enables students to get familiar with C/C++ programming language in UNIX environment. The course covers all basic C/C++ data structures, control flows, simple data structures as well as other advanced topics which include pointers, bit operators, file processing, dynamic data types.

**Note:** You are recommended to complete a problem set of 177 basic exercises to complete this course.

This course is oriented to those undergraduate students who require a working knowledge of numerical methods. Topics to be covered include solving nonlinear equations and linear systems, interpolation and least square method, numerical evaluation of derivatives, integral and solution of differential equation. The focus will be on understanding the solving techniques and the engineering meaning of diver problems, and not on rigorous profs.

**Note:** You are recommended to implement these numerical methods with a programming language.

This is a practical hands-on course that is intended for students who are interested in competitive programming and algorithmic challenges. In this course you will learn the techniques and skills needed to solve algorithmic programming problems.

**Note:** There are lots of practice contests associating with this course.
You are recommended to practice more on Codeforces,
CodeChef and other online judges.
Be calm and keep fighting !!

This course provides students the basic components and important principles of programming languages. It covers the subjects on programming language paradigms, logicprogramming languages, subprograms and Software processes. Students can improve their programming and software engineering skills, increase ability to express ideas and further their research activities.

Provides the student with a thorough understanding of varying methodologies and techniques in analysis, design and implementation of information system by using UML.

**Note:** There is no text-book referenced in this course.

This course helps students discuss on digital image processing fundamentals; review of Digital Signal Processing algorithms such as Discrete Fourier Transform; intensity transforms, frequency domain filtering; image restoration and reconstruction; color image processing; multiresolution processing; image compression; morphological image processing.

**Note:** This is a research-oriented course for motivated students.