Computer Engineering

SEM 3

*Courses in Semester III (Computer Engineering):*
1. *Data Structures & Algorithms*
2. *Object-Oriented Programming (OOP)*
3. *Digital Logic Design*
4. *Discrete Mathematics*
5. *Computer Organization & Architecture*
6. *Electronic Circuits & Systems*
7. *Lab Courses* (e.g., OOP Lab, Digital Logic Lab, Electronics Lab

*Program Outcomes (POs) for Semester III*
By the end of Semester III, students should achieve the following learning outcomes:

1. *Engineering Knowledge*
– Apply mathematical foundations (e.g., discrete mathematics) and engineering principles to solve computational problems.

2. *Problem Analysis*
– Identify and formulate problems in areas like data structures, digital logic, and algorithms.

3. *Design/Development of Solutions*
– Design efficient algorithms and data structures for real-world problems.
– Develop digital circuits using logic gates and sequential circuits.

4. *Programming Skills*
– Implement object-oriented programming concepts (e.g., classes, inheritance, polymorphism) in languages like Java/C++.

5. *Hardware Fundamentals*
– Analyze and design combinational/sequential circuits (e.g., adders, multiplexers, flip-flops).
– Understand the basics of computer organization (e.g., CPU, memory, I/O systems).

6. *Mathematical Proficiency*
– Apply discrete mathematics (e.g., graph theory, combinatorics) to computer science problems.

7. *Lab Competency*
– Simulate and test digital circuits using tools like Logisim or Proteus.
– Demonstrate hands-on skills in electronics and programming labs.

8. *Ethics and Sustainability*
– Recognize ethical and environmental impacts of engineering solutions.

SEM 4

Program Outcomes (POs)

Graduates of the Computer Engineering program will be able to:

1. Engineering Knowledge: Apply knowledge of mathematics, science, and engineering fundamentals to solve complex problems.

2. Problem Analysis: Identify, formulate, and analyze engineering problems using principles of computing and engineering sciences.

3. Design & Development: Design solutions for complex engineering problems that meet specific requirements while considering public health, safety, and environmental concerns.

4. Investigation of Complex Problems: Use research-based knowledge and methods to analyze and interpret data to provide valid conclusions.

5. Modern Tool Usage: Apply modern engineering and IT tools to complex engineering activities with an understanding of their limitations.

6. Engineer & Society: Apply reasoning to assess societal, health, safety, legal, and cultural issues relevant to professional engineering practice.

7. Environment & Sustainability: Understand the impact of engineering solutions on society and the environment and promote sustainable development.

8. Ethics: Apply ethical principles and commit to professional ethics and responsibilities in engineering practices.

9. Individual & Team Work: Function effectively as an individual and as a team member or leader in diverse and multidisciplinary settings.

10. Communication: Communicate effectively on complex engineering activities with the engineering community and society at large through reports, presentations, and documentation.

11. Project Management & Finance: Apply engineering and management principles to handle projects in a multidisciplinary environment.

12. Life-long Learning: Recognize the need for lifelong learning and the ability to engage in independent learning in the field of technology.

SEM 3

*subject-wise breakdown of Program Specific Outcomes (PSOs)* for *Semester III (Revised Syllabus 2019)* of *Computer Engineering* at *Mumbai University*, aligned with the curriculum structure and learning objectives:

### *1. Data Structures*
*Course Code*: CSDL307 (Theory + Lab)
*PSOs*:
– Design and implement *linear/non-linear data structures* (stacks, queues, linked lists, trees, graphs) for efficient data organization.
– Analyze *time and space complexity* of algorithms (sorting, searching, recursion) to optimize computational efficiency.
– Apply *algorithmic paradigms* (greedy, divide-and-conquer) to solve real-world problems (e.g., shortest path, scheduling).

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### *2. Object-Oriented Programming (OOP)*
*Course Code*: CSPC307 (Theory + Lab)
*PSOs*:
– Develop *modular, reusable software* using OOP principles (encapsulation, inheritance, polymorphism) in Java/C++.
– Implement *exception handling, multithreading, and file I/O* to build robust applications (e.g., GUI-based systems).
– Model software systems using *UML diagrams* (class, sequence, use-case).

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### *3. Discrete Structures*
*Course Code*: CSDL302
*PSOs*:
– Apply *graph theory* (trees, shortest path algorithms) and *combinatorics* to solve computational problems.
– Use *propositional/predicate logic* for formal verification of algorithms and system design.
– Analyze *recurrence relations* and algebraic structures (groups, rings) for cryptography and algorithm optimization.

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### *4. Computer Organization and Architecture*
*Course Code*: CSDL303
*PSOs*:
– Understand *CPU architecture* (registers, ALU, control unit) and *memory hierarchy* (cache, RAM, virtual memory).
– Design *instruction sets* and analyze performance metrics (clock cycles, CPI, Amdahl’s Law).
– Interface *I/O devices* using interrupt-driven and DMA techniques.

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### *5. Database Management Systems (DBMS)*
*Course Code*: CSDL304 (Theory + Lab)
*PSOs*:
– Design *normalized relational databases* using ER diagrams and SQL (DDL, DML, queries).
– Implement *ACID properties, indexing, and transaction management* for robust database systems.
– Compare *NoSQL vs. SQL databases* for scalability and application-specific requirements.

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### *6. Environmental Studies*
*Course Code*: CSDL306
*PSOs*:
– Analyze the *environmental impact* of computing technologies (e-waste, energy consumption).
– Propose sustainable engineering solutions aligned with *SDGs (Sustainable Development Goals)*.
– Advocate for *green computing practices* (recycling, energy-efficient algorithms).

SEM 4

1. Software Development & Applications: Apply computing principles, programming techniques, and software engineering methodologies to develop efficient software applications.

2. Networking & Security: Understand and implement secure network architectures, protocols, and cybersecurity measures in real-world applications.

3. Emerging Technologies & Innovation: Adapt to evolving technologies such as AI, Machine Learning, IoT, Cloud Computing, and Blockchain for innovative solutions.

4. Entrepreneurship & Industry Readiness: Develop problem-solving skills, leadership qualities, and an entrepreneurial mindset to contribute effectively to the industry.