Machine Intelligence

Machine Intelligence

Master of Science in Computer Science with  specialization in Machine Intelligence 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 Machine Intelligence 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. The students of Machine Intelligence specialization are expected to have studied Mathematics during the +2/pre-university also.

A candidate with CGPA less than 6.5 will also be eligible if the equivalent percentage for graduation is above 60% as per the respective university norms for conversion from CGPA to percentage. In such a case, the candidate will have to produce the official document or percentage equivalence certificate from the respective university showing CGPA to percentage conversion norms, at the time of admission. Students who have scored less than 60% in their graduation degree are not eligible for admission to the courses of IIITM-K.

Candidates belonging to SC/ST communities are eligible for applying if they have minimum pass marks in the qualifying examination. SEBC candidates of Kerala State who are certified as belonging to non-creamy layer are eligible for 5% relaxation in the minimum required marks for qualifying examination, provided that the candidates have passed the examination.

Number of Seats

The number of seats for this program is 30.


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

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.

Core courses

      • Computer Architecture and Organization
      • Computer Architecture and Operating Systems
      • Problem Solving with Python
      • Data Structures and Algorithms
      • Machine Learning
      • Mathematics for Machine Learning
      • Web Technologies
      • Information Retrieval
      • Database Management System
      • Object Oriented Analysis and Design
      • Big Data Technologies
      • Software Engineering
      • MI Lab I ( Semester I )
      • MI Lab II ( Semester II )
      • MI Lab III ( Semester III )
      • Programming Lab (Python – Semester I)
      • Programming Lab II (Python, OO – Semester II )
      • Mini Project I ( Semester II )
      • Mini Project II ( Semester III )
      • Project & Viva Voce

Electives for semester II

  • Predictive Analytics
  • Digital Image Processing
  • Natural Language Processing

Electives for semester III

  • Soft Computing
  • Multimedia Signal Processing
  • Advanced Data Analytics
  • Computer Vision
  • Blockchain Technology
  • Artificial General Intelligence


Electives for semester II


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