M.Sc. in Computer Science with specialization in Data Analytics.


Data Analytics is one of the emerging areas of IT industry and can be applied across disciples ranging from science, technology, business or even arts. Big Data Analytics is a phrase tossed recently to tackle sheer volume of data generated in the modern world. Data Science and Big Data Analytics combine statistical methods for inferring patterns from crude data; database technologies for storing and retrieval of data; intelligent technologies to extract knowledge and visualization for easy analysis and better understanding. Data analytics enables one to generate information and thereby knowledge from large quantities of incomprehensive data. The post graduate programme in data analytics is intended to offer the foundations of data analytics, data mining and knowledge discovery methods and their application to practical problems.

 Aim and Objective

  • To impart theoretical knowledge related to Computer Science
  • To impart theoretical & practical knowledge in the specialized areas of Data Analytics
  • To cater the needs of government, industry and scientific organizations in the Computer Science and Data Analytics related areas.
  • Develops professionals and leaders of high caliber imbued with values of entrepreneurship, ethics and social responsibility.
  • To motivate for research in Computer Science with specific emphasis on Data Analytics
  • To train computer scientists who can work on real life challenging problems.

Course Description

Master of Science in Computer Science with specialization in Data Analytics will be a restructured course offered by the Indian Institute of Information Technology and Management-Kerala, aims at offering a high standard curriculum in allied disciplines of Computer Science. The programme focuses on a broad grasp of foundations in Computer Science, deep understanding of the area of specialization, an innovative ability to solve new problems, and a capacity to learn continually and interact with trans-disciplinary groups. The technology enhanced e-learning methodologies with web based course management system and on-line learning system enriches the programme, allow to broaden their horizons.

The duration of the programme is 2 years and the courses are carefully designed to attain technical aspects that enable the students to grow into competent Data Analytics professionals. There are 11 core courses, 4 electives and five lab courses. The students are required to do a minor project of 2 credits each during 2nd and 3rd semester. The students are also required to take one elective course during second semester and three elective courses during the third semester of 3 credits. The 4th semester is for project/internship of 18 credits. Students are required to undergo an industry or research oriented project in any leading IT or R &D organizations. The total requirement for the programme is 72 credits.


Entry-level requirement is a minimum score of 60 percentage marks OR CPI/CGPA of 6.5  or above in 10 points in the    Bachelor’s degree in any branch  of Engineering/Technology/Science  with  Mathematics as  a Subject of study


Students are selected through an All India entrance examination and an interview under the supervision of CUSAT. GATE/NET score holders with valid score are exempted from the test. Rank holders of CAT conducted by CUSAT are also exempted from the Institute conducted test. Reservation of seats for SC/ST, OBC etc. is applicable as per CUSAT rules. The final selection of the candidates is done through an interview from the short listed candidates of written test. The total intake of the students for the stream is 30 .

Assessment, Evaluation and Grading System
A student would be considered to have progresses satisfactorily at the end of a semester if he / she has a minimum of 75 % attendance.

There will be 40% for internal examination and 60% external examination marks for all courses except the minor projects and lab courses. The minor projects and lab exams will have only internal evaluations. There will be a continuous assessment for classroom performance, lab exercises, seminars and discussions. The evaluation scheme for each semester has internal assessment, End Semester Examinations and lab examinations.

The Question paper for the end semester external examination shall have Part A having 15 Questions of 2 marks each and Part B having 5 Questions of 6 marks each with a total of 60 marks. In order to secure a pass in any subject, the candidate should score 45% marks in external examination and an aggregate of 50% of the total of end semester examination and internal assessment marks.

The evaluation of a student’s performance at the end of the semester results in a grade, and a grade card will be issued on completion of each semester. The grade pattern is given below:

Requirement Credits
Core Courses 33
Elective Courses 12
Mini Projects 4
Lab Courses 5
Internship/Project 18
Total Credits 72

Core Courses

The student is required to earn 33 credits from the following 11core courses:

  1. Computer Architecture and Organization
  2. Problem Solving and Programming in C
  3. Data Structure and Algorithm
  4. Machine Learning
  5. Foundations of data analytics
  6. Operating system
  7. Computer Networking
  8. Database Management System
  9. Object Oriented Programming
  10. Soft Computing
  11. Internet Technologies

Elective Courses

The elective courses are offered in the 2nd and the 3rd semesters. There will be only one elective in the second semester and three electives in the third semester.

Electives for semester :

  1. Data Analytics
  2. Language Technologies & Information Retrieval
  3. Advanced Data Analytics
  4. Big Data Technologies
  5. AI & Knowledge representation
  6. Time Series Analysis and SEM Modeling
  7. Web analytics
  8. Predictive Data Analytics
  9. Computational Modeling
  10. Spatial Data Analytics
  11. Theory of Computation

Mini Projects

A student is required to do one mini project each during the Semester 2 and Semester 3 independently under the guidance of any faculty member of the institute. This facilitates the student to get familiarize with the latest research and development trends in the field. At the end of the semester the student is required to submit a report of the mini project and give an oral presentation of the mini project carried out by him/her. The project report and the oral presentation will be evaluated by a 3 member committee comprising of the faculty members of the institute including the project guide. The project report and the oral presentation carry 25 marks each. There will not be any external evaluation for the mini projects. The mini-project in all semesters carry 2 credit each.

Core Labs

A student is required to do two labs in the first & second semesters and one in the third semester. The lab report and lab examination carries 25 marks each.


A student is required to do a project during the Semester 4, independently under the guidance of any faculty member of the institute or as an internship project in an industry or any reputed academic/research institute. If a student is opting for an internship project in an industry or any other reputed academic/research institute, he is required to have an internal guide from the institute. The project/internship aims to provide the student an opportunity to participate and work in a major research/development activity. Typically, the industry internship helps the student to learn about work culture, business processes, technologies, marketing strategies, etc. At the end of the semester the student is required to submit a report of the project/internship and give an oral presentation of the project/internship carried out by him/her. The project report and the oral presentation will be evaluated by both an internal committee comprising of the faculty members of the institute including the project guide as well as an external committee constituted by the university. The internal and external evaluation of the project report and the oral presentation carries 250 marks each. The project/internship carries 18 credits.

Number of Seats :

The number of seats for this program is 30