B.Sc Computer Science

Curriculum

Curriculum

B.Sc Computer Science

  • Course Name

    Credits

  • Foundation Course (FC)

    24

  • Department Core Courses (DC)

    32

  • Departmental Elective Courses (DE)

    32

  • Allied Department Course - 1 (AC - 1)

    8

  • Allied Department Course - 2 (AC - 2)

    8

  • Degree requirement (FC+DC+DE+AC1+AC2)

    104

  • Semester 1

    Credits

  • Foundation Course 1

    4

  • Foundation Course 2

    4

  • Introduction to Computer Programming using C

    4

Introduction to computing through writing programs. Concepts like loops, functions, etc. will be introduced.

  • Data Structures and Algorithms using C

    4

Topics include lists, trees, graphs, polymorphism, etc.

  • 16

  • Semester 2

    Credits

  • Foundation Course 3

    4

  • Foundation Course 4

    4

  • Computer Organization & Architecture

    4

Basic machine organization, including processors, instruction sets, assembly-language programming, pipelining, memory, and input/output architecture. Basics of the memory hierarchy, including virtual memory and caches; Core concepts of operating systems, including processes, threads, synchronization, virtual memory policies, and file management

  • Operating Systems

    4

Topics include process synchronization and inter-process communication, processor scheduling, memory management, virtual memory, interrupt handling, device management, I/O, and file systems.

  • 16

  • Semester 3

    Credits

  • Foundation Course 5

    4

  • Object Oriented Programming using Python

    4

Data structures (e.g. lists and dictionaries) and characteristic pythonic conventions such as anonymous functions, iterables, and powerful built-ins (e.g. map, filter, zip). We will also cover object-oriented design, the standard library, and common third-party packages.

  • Open Source Software

    4

  • AC 1- Allied Department Course - 1.a

    4

  • AC 1- Allied Department Course - 1.b

    4
  • 20

  • Semester 4

    Credits

  • Foundation Course 6

    4

  • Database Management Systems

    4

Basic concepts of the relational model and its mathematical foundation, SQL language to define, query and manipulate a relational database, database design and conceptual modelling using entity-relationship model and diagrams, indexed organization, normalization, transaction processing and management.

  • Principles of Web Design and Web Technologies

    4

Programming websites, hypertext markup language (HTML5), Cascading Style Sheets (CSS3), and Common Gateway Interface (CGI) scripts (using PHP).

  • AC 2- Allied Department Course - 2

    4

  • AC 2- Allied Department Course - 2

    4
  • 20

  • Semester 5

    Credits

  • Machine Learning

    4

Perceptron and other online algorithms; boosting; graphical models and message passing; dimensionality reduction and manifold learning; SVMs and other kernel methods; artificial neural networks.

  • Cyber Security

    4

Overview of cryptography, common vulnerabilities, web security, network security, Malware, denial of service, mobile platform security, coding secure systems, security testing and tools, security and human factors; privacy: history, tracking, and survey of legal issues, programming projects for analysis/test of software for vulnerabilities.

  • Software Engineering

    4

Requirements engineering, system analysis, low-level and high-level design and architecture, coding, integration, design and code reviews, documentation, testing and quality assurance, maintenance, project management and configuration management.

  • Data Science

    4

All aspects of a data analysis process, from posing questions, designing data collection strategies, management+storing and processing of data, exploratory tools and visualization, statistical inference, prediction, interpretation and communication of results; RStudio.

  • 16

  • Semester 6

    Credits

  • Data Warehouse and Mining

    4

Data selection, cleaning, coding, using different statistical and machine learning techniques, and visualization of the generated structures; data warehousing and on-line analytical processing (OLAP).

  • Mobile Application Development

    4

Deals with creating apps for both iOS and Android by using Javascript and existing web + mobile development paradigms.

  • Cloud Computing

    4

Examines the most important APIs used in the Amazon and Microsoft Cloud, including the techniques for building, deploying, and maintaining machine images and applications; how to use Cloud as the infrastructure for existing and new services.

  • Artificial Intelligence

    4

Topics include learning and inference, speech and language, vision and robotics, search and reasoning.

  • 16

  • Other Courses not covered above

  • Introduction courses
  • Programming
  • Translators, compilers, interpreters
  • Computing
  • Algorithms
  • Systems
  • Java
  • Language processing
  • Gaming
  • Cryptography
  • Maths and LR
  • Robotics
  • Miscellaneous
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