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Sunday, 30 September 2018

MCA from jss noida

MCA: Masters of Computer Application


Update: it's been 9 months since i have been sturding in jss 
passed my first semester the second semesters exams are about to begain.

Today I am going to talk about my three-month experience about this college like every other college it has a huge campus and a lot of student sturdy here. The college hostel has limited number of accommodation  that why Postgraduate students like MCA and MBA have to find and another hostel outside the campus which make 

Merits of studying in JSS Noida.

  • Classes go on every day (75% attendance is mandatory)
  • The facility like the library is opened till 8o clock till evening you can come any time you want and sit and sturdy in the reference section
  • Delhi is a cyber hub, so getting any internship from any prestigious company is quite easy.
  • Your past numbers do matter if you have fewer marks in your graduation less than 60% you will face a lot of problem at the time of placement.

Demerits of the college 

  • The fee structure for the course is very high more than the B-tech student 
  • MCA students have to compete with B-tech (CS) student.
  • The number of students is decreasing every year out of 60 seats only 27 students took admission in 2018.
  • The highest salary package for mca student from the college is 5 lakh.
So, if you are thinking to come to this college I would suggest you think about every pro and cons.


Why take admission here? 


if you love computers and want to get a degree and did not qualify the entrance exam of any prestigious colleges like JNU, NIMCET, BHU then you should definitely go for it.


Subjects in the first Semester:

  1. Computer concept And Programming in C.
  2. Professional Communication.
  3. Accounting and Financial Management
  4. Computer Organization and Architecture.
  5. Discrete Mathematics 

Subjects of Second Semester:

  1. Entrepreneurship & Development 
  2. Human Values
  3. Theory OF Computer Science 
  4. Computer-Based Numerical & Statistical Techniques
  5. Data Structure 


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