Department of Computer Engineering (CE)

About the Program

Computer Engineering course was launched in the academic year 2011-12 with a total intake of 60 seats and gradually increased to 120 seats in AY 2021-22 and to 180 seats in AY 2023-24. The Department has well-established state-of-the-art computer laboratories and classrooms that are equipped with ICT tools and computing facilities. Other than academics, the department provides its students with opportunities to participate in co-curricular and extra-curricular activities to showcase their talents and skills. The program aims towards the all-round development of students to mould them into becoming competent for the industry, academia and / or research.

  1. Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialisation for the solution of complex engineering problems.
  2. Problem analysis: Identify, formulate, research literature, and analyse complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.
  3. Design/development of solutions: Design solutions for complex engineering problems and design system components or processes that meet t h e specified needs with appropriate consideration for public health and safety, and cultural, societal, and environmental considerations.
  4. Conduct investigations of complex problems: Use research based knowledge and research methods including design of experiments, analysis and interpretation of data and synthesis of information to provide valid conclusions.
  5. Modern tool usage: Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools, including prediction and modelling to complex engineering activities, with an understanding of the limitations.
  6. The engineer and society: Apply reasoning informed by the contextual knowledge to assess societal, health, safety, legal, and cultural issues and the consequent responsibilities relevant to the professional engineering practice.
  1. Environment and sustainability: Understand the impact of the professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development.
  2. Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
  3. Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
  4. Communication: Communicate effectively on complex engineering activities with the engineering community and with t h e society at large, such as, being able to comprehend and write effective reports and design documentation, make effective presentations, and give and receive clear instructions.
  5. Project management and finance: Demonstrate knowledge and understanding of t h e engineering and management principles and apply these to one’s own work, as a member and leader in a team, to manage projects and in multidisciplinary environments.
  6. Life-long learning: Recognise the need for, and have the preparation and ability to engage in independent and life-long learning in the broadest context of technological change.

The Program educational objectives for the Department of Computer Engineering are –

  1. To develop technically competent Computer Engineers with proficient domain knowledge, research attitude and innovative thinking.

  2. To foster committed graduates with a life-long learning attitude and entrepreneurship spirit for a successful career.

  3. To inculcate professional ethics, managerial and communication skills to accomplish a worthy career in all spheres of Computer Engineering.

  4. To nurture socially aware engineers who can develop effective solutions for the betterment of the community and the nation.

PSO1:   Professional  Skills –The ability to understand, analyze  and  develop  computer programs in the areas related  to algorithms, system software, multimedia, web design, big data  analytics, and networking for efficient design of computer-based systems of varying complexities

PSO2:   Problem Solving Skills – The ability to apply standard practices  and  strategies in software project development using open-ended programming environments to deliver quality products for business success

PSO3:   Successful Career and  Entrepreneurship – The ability to employ modern computer languages, environments, and platforms in creating innovative career paths to be an entrepreneur, and to have a zest for higher studies

Second Year

Sem  III –

25  Credits

Sem  IV –

25  Credits

Semester III Semester IV
Discrete Mathematics Engineering  Mathematics III
Fundamental of Data Structures Data Structures & Algorithm
Object Oriented Programming (OOP) Software Engineering
Computer Graphics Microprocessor
Digital Electronics & Logic Design Principles of Programming Languages
Data  Structures Laboratory Data Structures & Algorithm Laboratory
OOP & Computer Graphics Laboratory Microprocessor Laboratory
Digital Electronics Laboratory Project Based Learning- II
Business Communication Skills Code of Conduct
Humanity & Social Science
Audit Course  3 Audit Course  4
 

 

 

 

Third Year

 

Sem  V-

23  Credits

 

Sem  VI –

23  Credits

Semester V Semester VI
Database Management Systems Data Science and Big Data Analytics
Theory of Computation Web Technology
Systems Programming and Operating System  Artificial Intelligence
Computer Networks and Security Elective II
Elective I Internship
Database Management Systems Laboratory Data Science and Big Data Analytics Laboratory
Computer Networks and Security Laboratory Web Technology Laboratory
Laboratory Practice I Laboratory Practice II
Seminar and Technical Communication Audit Course 6
 Audit Course 5
 

 

 

 

 

 

 

 

 

 

 

 

Final  Year

 

Sem  VII –

22  Credits

 

Sem  VIII –

22  Credits

Semester VII Semester VIII
Design and Analysis of Algorithms High Performance Computing
Machine Learning Deep Learning
Blockchain Technology Elective V
Elective III Elective VI
Elective IV Laboratory Practice V
Laboratory Practice III Laboratory Practice VI
Laboratory Practice IV Project Work Stage II
Project Work Stage I Audit Course  7 Audit Course  8
List of  Elective III (Choose any  one) List of  Elective  V (Choose any  one)
Pervasive Computing Natural Language Processing
Multimedia Techniques Image Processing
Cyber Security and Digital Forensics Software Defined Networks
Object oriented Modeling and Design Advanced Digital Signal Processing
Digital Signal Processing Open Elective I
List of  Elective IV (Choose any  one) List of  Elective VI (Choose any  one)
Information Retrieval Pattern Recognition
GPU Programming and Architecture Soft Computing
Mobile Computing Business Intelligence
Software Testing and Quality Assurance Quantum Computing
Compilers Open Elective II
cse-01

Cascading Style Sheet

Prof. Kimi Ramteke

Cascading Style Sheet

Advanced Data Structures

Prof. Ajitkumar Shitole

Advanced Data Structures

Software Design Methodologies and Testing

Prof. Prashant Gadakh

Software Design Methodologies and Testing

Big Data Hadoop

Prof. Deptii Chaudhari

Big Data Hadoop

Memory Organization in 80386

Prof. Sandeep Patil

Memory Organization in 80386

DAA Introduction

Dr. Sashikala Mishra

DAA Introduction

Equivalence Calculation under inflation

Prof. Kimi Ramteke

Equivalence Calculation under inflation

Overview of LEX and YACC

Prof. Deptii Chaudhari

Overview of LEX and YACC

Distributed Systems

Prof. Prashant Gadakh

Distributed Systems

Equivalence Calculations under Inflation

Prof. Kimi Ramteke

Equivalence Calculations under Inflation

Scheduling Algorithms

Prof. Deptii Chaudhari

Scheduling Algorithms

Transaction Serializability

Prof. Deptii Chaudhari

Transaction Serializability

ESIOT

Prof. Ashwini Jarali

ESIOT

Fusion

Dr. Sashikala Mishra

Fusion

Memory Organization

Prof. Bailappa Bhovi

Memory Organization

Data Preprocessing

Prof. Sadeep Patil

Data Preprocessing

WT Validation

Dr. Sashikala Mishra

WT Validation

Colour Models

Prof. Bailappa Bhovi

Colour Models

DevOps

Prof. Pradip Chougule

DevOps

DTD

Prof. Kimi Ramteke

DTD

DMW

Prof. Ajitkumar Shitole

DMW

Data Structure- Linked List

Prof. Prashant Gadakh

DATA STRUCTURE – LINKED LIST

Code Coverage

Prof. Ramkrushna Maheshwar

Code Coverage

Introduction to IoT

Prof. Yogita N

Introduction to IoT

DCE

Prof. Sandeep Patil

DCE

Database Query Optimization

Prof. Ramkrushna M

Database Query Optimization

Lex & yacc

Prof. Ashwini Jarali

Lex & yacc

Smart Closet Organizer

Prof. Prashant Gadakh

Smart Closet Organizer

Industrial Internet of Things

Mr. Pradip Ashok Chougule

Industrial Internet of Things

Programming with LEX & YACC

Prof. Prashant Gadakh

Programming with LEX & YACC

Fog Computing

Prof. Pradip Chougule

Fog Computing

Hypothesis Testing

Prof. Deptii Chaudhari

Hypothesis Testing

Type of Artificial Intelligence

Prof. Sandeep Patil

Types of Artificial Intelligence

FSM in Theory of Computations

Prof. Sunil A. Sushir

FSM in Theory of Computations

Final Cloud Computing

Prof. Mukesh More

 Final Cloud Computing

High Performance Computing

Prof. Nitin Alzande

 High Performance Computing

Difference between AI,ML,DL and DS

Prof. Shilpa Jadhao

Difference between AI,ML,DL and DS

JAVA as OOP PPT

Prof. Shilpa Jadhao

JAVA as OOP PPT