BSc Computer Science, Mathematics, Statistics - Overview
It is a three-year degree programme, conducted in affiliation to Bengaluru North University, spread over six semesters. The course offers three subjects computer science, mathematics and physics, with equal emphasis given to each of these three majors. English language and optional languages are also part of this curriculum, which can be pursued during semesters 1 to 4. Practical-based laboratory sessions are an integral part of the curriculum, as shown in the course structure.
The main objectives of this course are: to provide a comprehensive understanding of programming concepts and software development as a part of computer science; to provide an understanding of advanced mathematics; to impart knowledge on the fundamentals of probability theory, statistical reasoning and inferential methods, statistical computing, statistical modeling and its limitations, and development of skills for description, interpretation and exploratory analysis of data by graphical and other means, under statistics
Computer science encompasses scientific and practical approaches to computation and its applications. It is the systematic study of the feasibility, structure, expression, and mechanisation of the methodical procedures or algorithms that underlie the acquisition, representation, processing, storage and communication of information, and access to information. The course covers various aspects of programming concepts using C, data structures, database management system, software engineering, operating system, UNIX, object-oriented programming using Java, visual programming, web programming, computer networks, and software project development.
Mathematics is a science of numbers, quantity, and space, either as abstract concepts or as applied to other disciplines such as physics and engineering. The course covers various aspects of algebra, calculus, geometry, differential equations, real analysis and numerical methods.
Statistics is a branch of mathematics concerned with the collection, classification, analysis, and interpretation of numerical facts, for drawing inferences on the basis of their quantifiable likelihood (probability). The course covers various aspects of basic statistics, sampling theory and estimation, testing of hypotheses, applied statistics, and design and analysis of experimental and operational research.
