This document provides information about the Master of Computer Application (MCA) program for the second semester. It outlines the course structure, details of the second semester courses, assessments and examination criteria. The second semester will include courses in data structures and algorithms, network security, research methodology, and two electives. Students will be assessed through internal and end-term examinations, and must obtain minimum marks in each to pass. Important dates for assessments and the examination are also provided.

1. MASTER OF COMPUTER APPLICATION
SEMESTER- II
Presented by: Ms. Nisha Ahuja

2. Key Takeaways
• Program Structure
• Second Semester course details
• Assessments & Examination
• Passing Criteria
• Important Dates
• Q&A

3. MCA Educational Objectives
Apply knowledge of mathematics, science,
computing and engineering for research, design
and development of novel products.
Apply research knowledge and research methods
including design of experiments, analysis and
interpretation of data
Ability to examine the impact of engineering
solutions in societal, health, safety, legal, cultural
and environmental contexts.

4. MCA Structure
Semester I
• Graph Theory and
Combinatorics
• Core Java
• Advanced Database
Management
Systems
• Advanced Software
Engineering
Principles
• Professional
Communication
Semester II
• Data Structures and
Algorithm Design
• Research
Methodology
• Network Security
and Cryptography
• Electives: Select 2
courses out of 5
Semester III
• Unix /Linux
Programming
• Cloud Infrastructure
and Services
• Professional ethics
• Seminar
• Quantitative
Aptitude
• Electives: Select 2
courses out of 4
Semester IV
• Major Project
2 years | 4 semesters | 103 Credits

5. Semester II Details

6. Semester II Structure
Cognitive Analytics &
Social Skills for
Professionals (New
Course)
Data Structure &
Algorithm Design
(CSE601)
Network Security &
Cryptography
(CSIT654)
Research
Methodology
(CSIT745)
ELECTIVE SUBJECTS

7. ELECTIVE SUBJECTS
 Artificial Intelligence and Robotics
 Image Processing Techniques
 Routing & Switching Essentials(Networking specialization)
 Statistics Using R
 Introduction to Data Analytics

8. Course Objectives and Outcomes
Course 1: Cognitive Analytics & Social Skills for Professionals
Learning Objectives
• To understand the Cognitive Analytics and Social Cognition.
• To apply emotional intelligence in decision making.
• To develop leadership skills for effective management.
• To practice resilience during uncertainty.
Learning Outcomes:
• On the completion of the course the participants will be able to
demonstrate cognitive and social skills in problem solving.

9. Course Objectives and Outcomes
Course 2: Data Structure & Algorithm Design
Learning Objectives
• Introduction to the use, design, and analysis of data structures in
computer programs.
• Detailed discussion of commonly used data structures like arrays, stacks,
queues, lists, trees, and graphs along with their time and space
complexity analysis.
Learning Outcome
• The student of the course will be able to develop a better
understanding of solving problems through algorithm analysis.

10. Course Objectives and Outcomes
Course 3: Network Security & Cryptography
Learning Objectives
• Concept of Network security issues, challenges and mechanisms.
• Security of Network architecture & various Cryptographic Algorithms.
• Common network vulnerabilities and attacks.
• Requirements of real-time communication security.
Learning Outcome
• To develop the Technical Skills necessary to fully manage sophisticated
and vulnerable Computer Network Environment.

11. Course Objectives and Outcomes
Course 4: Research Methodology
Learning Objectives
• To recognize the steps involved in doing research.
• To collect data using various media and using the best possible sample
available.
• To propose their Hypothesis and build models for the problem.
• To correctly document their findings in the form of a report.
Learning Outcome
• Students can recognize the various steps involved in research and explain
the entire process in the form of a report.

12. Assessments & Examination

13. ASSESSMENTS
End Term
Assessments-
70% Weightage
Internal
Assessments-
30% Weightage
Assessment Pattern

14. Internal Assessments
INTERNAL
ASSESSMENT
30% WEIGHTAGE
Assignment 1-
5 module Assessments
15% Weightage
1st Module Assessment
2nd Module Assessment
3rd Module Assessment
4th Module Assessment
5th Module Assessment
Assignment 2-
Full Syllabus Assessment
15% Weightage

15. End Term Assessments/ End Term Examination (ETE)
Section Description
Questions To
Attempt Marks
Section A
Four subjective questions of 7.5 marks
each; attempt any two with detailed
answers to be typed by the learner in
the dialogue box provided
2 Essay Questions ×
7.5 Marks each
15
Section B
Case study followed by Two Questions
of 7.5 marks each
2 Essay Questions ×
7.5 Marks each
15
Section C
Twenty MCQs of Two marks each based
on course syllabus
20 MCQs × 2 Marks
each
40
Total Marks 70 Marks
End Term Assessment: 70% Weightage

16. To qualify in examination a learner must obtain the following
Marks:-
• Minimum 30% marks in Internal Assessment.
• Minimum 30% marks in End Term Examination (ETE)
For Post Graduate Minimum 40% overall aggregate i.e. both
Internal Assessment & End Term Examination put together.
Minimum 5 SGPA for every semester
Minimum 6 CGPA for overall course
Passing Criteria

17. Important Dates
Activities Date(s)*
Dates of Course Access 4th October 2021 (Onwards)
Assessment (Assignment Opening Date) 5th Nov 2021
Last date for Submission of Internal Assessment 25th Jan 2022
End Term Examination (ETE) 22nd Feb 2022 to 11th March 2022(Tentative)
Result Declaration of ETE 11th April 2022 (Onwards)(Tentative)
* ALL WEEK(S)/ DATE(S) SCHEDULED ARE SUBJECT TO CHANGE WILL BE NOTIFIED SEPARATELY IN STUDENT
ZONE/LEARNING PORTAL

18. Post query section (Student Zone)
Mail – studentsupport@amityonline.com
Support No.- 8826334455