MSc Computer Science Syllabus

MSc Computer Science is a two-year postgraduate programme that aims to develop advanced programming skills and strategies for solving various logical challenges using various programming languages.

MSc Computer Science, also known as MSc CS, focuses on developing software and networking skills. After obtaining an M.Sc. in Computer Science, you can work as a Networking Master, Software Developer and Tester, Web Developer, Cryptography, etc.

MSc in Computer Science is one of India's most sought-after computer courses. According to a census, 81.3 thousand male and 79.2 thousand female candidates graduated with degrees in computer science in 2016.

The scope of computer science cannot be measured because everyone uses it. While Btech and BE Computer Science are the most popular courses, some students choose BSc Computer Science to gain more theoretical knowledge on the subject. However, what do these students do after they finish their bachelor's degrees? Many people get jobs, while others pursue higher education. The MSc Computer Science programme is ideal for such students. Before enrolling in a degree programme, it is critical to understand the course content. As a result, we have created this blog on the MSc Computer Science syllabus to assist students!

MSc Computer Science in Detail

Syllabus of MSc Computer Science

The MSc Computer Science Syllabus includes a variety of core and elective subjects that cover all of the major topics. Because the actual course curriculum may differ depending on the university, we have listed all of the major subjects covered by the MSc computer science syllabus:

The course syllabus will differ depending on the specialisation chosen by the student and the university. Certain topics are covered in almost all courses. 

Aside from final year projects and internships, the following are the common subjects:

• Basic Programming Laboratory
• Programming Languages
• Theory of Computation
• Design and Analysis of Algorithms
• Mathematical Logic
• Discrete Mathematics
• Distributed Systems
• Computer Systems Verification
• Complexity Theory
• Operations Research
• Data Mining and Machine Learning
• Cryptography and Computer Security
• Probability and Statistics

Quick Read: Computer Science Engineering Subjects

Basic Programming Laboratory

The goal of the Basic Programming Laboratory is to provide a learning environment and a better understanding of the fundamental concepts and methods of computer programming. Instead of focusing on programming languages, this lab encourages students to focus on developing programming skills. Students investigate object-oriented programming features in C++/JAVA/Python.

Programming Languages

A programming language is a computer language used to interact with computers by programmers (developers). It is a set of instructions written in any language (C, C++, Java, Python) to accomplish a specific task.A programming language is primarily used to create desktop applications, websites, and mobile apps.

Theory of Computation

Regular and context-free languages, decidable and undecidable problems, reducibility, recursive function theory, time and space computation measures, completeness, hierarchy theorems, inherently complex problems, oracles, probabilistic computation, and interactive proof systems are some of the topics covered.

Design and Analysis of Algorithms

Algorithm design fundamentals include top-down design, divide and conquer, average and worst-case criteria, and asymptotic costs. Asymptotic cost recurrence relations with simple recurrence relations. Arrays, lists, stacks, queues, trees, heaps, priority queues, and graphs are examples of appropriate data structures.

Mathematical Logic

This course will provide a graduate-level introduction to mathematical logic with a strong emphasis on various mathematical applications. There is no presumption of prior knowledge of mathematical logic. However, some mathematical sophistication and knowledge of abstract algebra will be beneficial.

Discrete Mathematics

Computer algorithms and systems have been using logical notation to define and reason mathematically about the fundamental data types and structures (such as numbers and sets) being used.

Distributed Systems

In its most basic form, a distributed system is a group of computers that work together to appear to the end-user as a single computer. These machines share a state, run concurrently, and can fail independently without affecting the overall system's uptime.

Computer Systems Verification

To evaluate process types, designs, layouts, analysis, product forecasting, capacity planning, and knowledge of current manufacturing technologies and automation.

Complexity Theory

Complexity strategy, also known as complex adaptive organisations, applies complex system research to strategic management and organisational studies. It is based on natural science research into uncertainty and non-linearity.

Operations Research

Operations Research, also known as Decision Science or Operations Analysis, is the study of how to apply mathematics to business problems. As a subfield of Applied Mathematics, it occupies an intriguing position alongside fields such as Data Science and Machine Learning.

Data Mining and Machine Learning

It is related to artificial intelligence (AI), which provides frameworks with the ability to learn and improve machine systems by explicitly customising them. The iterative aspect of AI is important because models can freely adjust as new information is presented to them. They learn from previous calculations to produce repeatable choices and outcomes. It is not a new science but rather one that has gained new traction.

Cryptography and Computer Security

Cryptography is a method of securing information and communications by using codes that only the people who are supposed to understand and process the information can understand and process. As a result, unauthorised access to information is prevented. The topic is about the security of data and interpretations. There is a role for mathematical operations and data analysis in cryptography.

Probability and Statistics

Probability and statistics are branches of mathematics concerned with the laws governing random events and the collection, analysis, interpretation, and presentation of numerical data.

List of Electives

Every university has different criteria while selecting their elective subject that depends on students and faculty.

• Information Security
• Data Compression
• Soft Computing
• Distributing Computing
• Mobile Computing
• Web Services
• Data Mining
• Statistics and Data Analytics

MSc Computer Science Syllabus - 1st Year

MSc Computer Science Syllabus - 2nd Year

TOP Universities to Study MSc Computer Science in Abroad

Ms in computer science has become the most popular programme among students worldwide. The reason for this is obvious. Technology pervades every aspect of life, and it is only getting better in the coming years. As a result, obtaining an MS in computer science will provide you with the skills needed for a lucrative career in a field that shows no signs of slowing down. The course introduces students to software development and computer science disciplines such as networking, systems, programming, algorithms, and theory. By the end of the course, the student has acquired the necessary skills and knowledge to work with computer technologies and is qualified for well-paying positions such as software engineer, software developer, programme analyst, and many other job profiles.

When you study computer science abroad, you will have the opportunity to select from a wide range of programmes offered by some of the world's most prestigious universities and colleges. It will also expose you to a new culture and approach to the subject, which may broaden your understanding of it.

• Stanford University, USA
  
• Massachusetts Institute of Technology, USA
• University of California, Berkeley
• The University of Illinois,
• Cornell University
• Georgia Institute of Technology
• University of Washington
• Carnegie Mellon University
• Columbia University
• Boston University
• University of Windsor, Canada
• Western University, Canada
• University of Ottawa, Canada
• University of Alberta, Canada
• University of Toronto, Canada
• University of Salford, UK
• University of Glasgow, UK
• University of Nottingham, UK
• University of Birmingham, UK
• Durham University, UK
• Coventry University, UK
• Birkbeck, University of London, UK

Recommended MSc Computer Science Books

Every subject has assigned reading, and Computer Science is no exception. Like any other field of study, computer science has a history, various processes, and enough opposing viewpoints to fill a library.

MSc Computer Science Reference Books: Reference books are useful for quickly searching topics. Candidates taking the exam will need reference books in order to study properly. The competition in the Entrance exam is so fierce that the candidate must put in a lot of effort, planning, and concentration for the exam. 

Reference books can help you improve your problem-solving skills and practice thoroughly.

• Mcqs In Computer Science -Williams
  
• Core Java: An Integrated Approach, New: Includes All Versions up to Java 8 - R. Nageswara Rao and DT Editorial Services
• Computer Networking: A Top-Down Approach - Kurose James F. and Ross Keith W
• Fundamentals of Database System - Elmasri Ramez and Navathe Shamkant
• C in Depth - Deepali Srivastava and S. K. Srivastava
• DATA COMMUNICATIONS AND NETWORKING (SIE) - Behrouz A. Forouzan
• Data Structures and Algorithms - Michael T. Goodrich and Roberto Tamassia
• Data Structures Through C In Depth - Deepali Srivastava and S. K. Srivastava
• Computer Fundamentals - P. K. Sinha
• Theory of Computer Science: Automata, Languages, and Computation - Mishra K.L.P

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