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Program Overview

DA-IICT offers two unique four-year undergraduate programs leading to the Degrees of Bachelor of Technology in Information and Communication Technology – B.Tech (ICT) and Bachelor of Technology (Honours in ICT with minor in Computational Science) – B.Tech (Honours in ICT with minor in CS).

DA-IICT launched the B.Tech (Honours in ICT with minor in CS) program from 2013-14 academic session to impart the necessary knowledge and insight to the students to build computational models to understand, analyze and address fundamental problems in the areas of societal importance. Computational science involves use of mathematical models, numerical methods, quantitative analysis techniques, advanced computing capabilities and IT knowledge to understand and solve complex science, engineering and social problems aimed in improving products, processes, and work-flows. DA-IICT is the first institute in the country to design and offer teaching program in the area of Computational Science at undergraduate level.

The program is focused on two main lines – theoretical learning and practical implementation. The students must take core/group-elective courses in the areas of Mathematics, Physics, Numerical and Computational Methods, Modeling and Simulation, High Performance Computing, Parallel Programming, Data analysis and Visualization. The electives are further designed to sharpen this skill-set by providing domain knowledge in interdisciplinary areas ranging from engineering to biological applications.

The minor in CS provides an opportunity to pursue a focused set of courses that emphasize all main aspects of Computational Science. The program has significant research and development components as part of the course structure. The minor requires extra core credits (compulsory core courses and electives from the list given in table below) in addition to what an ICT undergraduate takes.

 

Core Courses Group Electives
·         Introductory Computational Physics

·         Computational and Numerical Methods

·         High Performance Computing

·         Modelling and Simulation

 

·         Introduction to Algorithms

·         Parallel Programming

·         Data Analysis and Visualization

 

 

Science Electives Technical Electives
  • Nonlinear Science
  • Computational Optimization
  • Computational Electromagnetics
  • Synthetic Biology
  • Computational Drug Discovery
  • Advanced Numerical Methods

 

  •  Computational Finance
  •  Introduction to Complex Networks
  • Foundations of Computational and Systems Biology
  • Introduction to Bioinformatics and Computational Biology
  • Stochastic Processes and Simulation
  • Computational Coding Theory
  • Natural Computing
  • Computational Data Science
  • Topics in Neutral Networks