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DEPARTMENT OF COMPUTER APPLICATIONS

About the Course

With the rapid proliferation and mushrooming of social networking sites and vivid online business transactions huge data/information is generated in a bigger way possessing volume, velocity, veracity, variety as traits/attributes tagged with it. The organizations are now in a race to deploy business analytical tools that are intelligent enough to decipher the hidden business strategies, decisions, trends and patterns that can significantly steer to achieve business excellence in a competition driven era. This program is focused on helping the student to harness the potential of "big data" to make more informed decisions at all levels of your organization.

The course is built on the concept of decision-making which requires both art (experience & intuition) and science (analytics) in the present complex marketplace. This programme also explores leading-edge information management tools and organizational strategies for capturing, organizing, and acting on data. Moreover the potential of unstructured, large-volume data on new product and service offerings is examined.

DEPARTMENT OF COMPUTER APPLICATIONS
DEPARTMENT OF COMPUTER APPLICATIONS

Salient Features

  • Experiential learning with case studies and mini project
  • MOOC courses enabled Curriculum
  • Industry focused electives
  • The cutting edge curriculum has been designed to develop core competencies.
  • Strong theoretical foundations complemented with extensive practical training.
DEPARTMENT OF COMPUTER APPLICATIONS

Career Opportunities

As organizations worldwide race to implement the new era of big data applications, they quickly find that the skills they need are in short supply—and the gap is widening. Students possessing big data analytical and diagnostic skills and fundamental ideas on big data and its challenges are sure to reap maximum benefits and placement offers in the job market.

  • Data Scientist
  • Big Data Analyst
  • Business Intelligence Developer
  • Data Engineer
  • Data Architect
  • Enterprise Architect
DEPARTMENT OF COMPUTER APPLICATIONS

VISION

The department of Computer Applications aims to transform aspiring students into software professionals with a high degree of technical skills and to inculcate a research mind set.

MISSION

  • M1. To provide strong theoretical foundations complemented with extensive practical training.
  • M2. To design and deliver curricula to meet the changing needs of industry.
  • M3. To establish strong collaborations with industry, R&D and academic institutes for training and research.
  • M4. To promote all-round development of the students through interaction with alumni and industry
DEPARTMENT OF COMPUTER APPLICATIONS

PROGRAMME EDUCATIONAL OBJECTIVES (PEO)

The program is expected to enable the students to

  • PEO 1: To prepare graduates to be successful professionals in industry, government,academia, research, entrepreneurial pursuit and consulting firms.
  • PEO 2: To prepare graduates to achieve peer-recognition, as an individual and as a team player, through demonstration of good analytical, design, implementation and interpersonal skills.
  • PEO 3: To prepare graduates to contribute to society as broadly educated, expressive, ethical and responsible citizens with proven expertise.
  • PEO 4: To prepare graduates to pursue life-long learning to fulfill their goals.

PROGRAM OUTCOMES (ALIGNED WITH GRADUATE ATTRIBUTES) (PO)

At the end of this program, graduates will be able to

  • PO 1: Computational Knowledge: Apply knowledge of computing fundamentals,computing specialisation, mathematics, and domain knowledge appropriate for the computing specialisation to the abstraction and conceptualization of computing models from defined problems and requirements.
  • PO 2: Problem Analysis: Identify, formulate, research literature, and solve complex computing problems reaching substantiated conclusions using fundamental principles of mathematics, computing sciences, and relevant domain disciplines.
  • PO 3: Design /Development of Solutions: Design and evaluate solutions for complex computing problems, and design and evaluate systems, components, or processes that meet specified needs with appropriate consideration for public health and safety, cultural, societal, and environmental considerations.
  • PO 4: Conduct Investigations of Complex Computing Problems: Use research-based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions.
  • PO 5: Modern Tool Usage: Create, select, adapt and apply appropriate techniques, resources, and modern computing tools to complex computing activities, with an understanding of the limitations.
  • PO 6: Professional Ethics: Understand and commit to professional ethics and cyber regulations, responsibilities, and norms of professional computing practice.
  • PO 7: Life-long Learning: Recognize the need, and have the ability, to engage in independent learning for continual development as a computing professional.
  • PO 8: Project management and finance: Demonstrate knowledge and understanding of the computing 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.
  • PO 9: Communication Efficacy: Communicate effectively with the computing community, and with society, about complex computing activities by being able to comprehend and write effective reports, design documentation, make effective presentations, and give and understand clear instructions.
  • PO 10: Societal and Environmental Concern: Understand and assess societal, environmental,health, safety, legal, and cultural issues within local and global contexts, and the consequential responsibilities relevant to professional computing practice.
  • PO 11: Individual and Team Work: Function effectively as an individual and as a member or leader in diverse teams and in multidisciplinary environments.
  • PO 12: Innovation and Entrepreneurship: Identify a timely opportunity and using innovation to pursue that opportunity to create value and wealth for the betterment of the individual and society at large.

PROGRAM SPECIFIC OUTCOMES (PSO)

  • PSO 1: Enable the students to design suitable data models, appropriate architectures and analytics techniques for efficient implementation of complex systems
  • PSO 2: Enable the students to design and integrate systems for providing interactive solutions for healthcare applications
DEPARTMENT OF COMPUTER APPLICATIONS

SEMESTER I

SL.
NO
COURSECOURSE CODENAME OF THE COURSELTPCSTCH
1PCCAA3701Advanced Data Structures and
Algorithms using Python
302425
2PCMAA3706Statistics for Computer Science00414
3PCCAA3702Database Technology310414
4PCCAA3703Object Oriented Programming
using Java
02414
5PCCAA3704Computer Networks300313
PRACTICAL
6PCCAA3781Software Design Project006206
Total15 11021626

SEMESTER II

SL.
NO
COURSECOURSE CODENAME OF THE COURSELTPCSTCH
1PCCAA3705Web Design and Development310414
2PCCAA3706Data Warehousing and Data Mining202414
3PCCAA3707Machine Learning10414
4PCCAA3708Software Engineering310414
5PECA*****Elective-1(Specialization)00313
6PECA*****Elective-2 (Specialization)300313
PRACTICAL
7PCCAA3782Software Development Lab002103
8PCCAA3783Web Programming Lab002103
Total143624523
L – Lecture ; T – Tutorial ; P – Practical ; S- Self Study; C – Credit      

SEMESTER III

SL.
NO
COURSECOURSE CODENAME OF THE COURSELTPCSTCH
1PCCAA3709Software Testing and Quality Assurance02410
2PCCAA3710DevOps202410
3PCCAA3711MOOC (Specialization)000233
4PECA*****Elective -3 (Specialization)300303
5PECA*****Elective -4 (Specialization)300303
6OE*******Open Elective300303
PRACTICAL
7PCELA4383Presentation Skills and Academic writing002102
8PCCAA3784Project Phase-I06306

SEMESTER IV

SL.
NO
COURSECOURSE CODENAME OF THE COURSELTPCSTCH
PRACTICAL
1PCCAA3785Project Work - Phase – II002412024
Total002412024

LIST OF DEPARTMENTAL ELECTIVES WITH GROUPING - SEMESTER WISE

SL.
NO
COURSECOURSE CODENAME OF THE COURSELTPCSTCH
Elective I
4PECAB3721Web analytics300303
4PECAB3722Big Data Analytics300303
Elective II
4PECAB3723R Programming300303
4PECAB3724Big Data Framework300303
Elective III
5PECAB3725Semantic Web300303
5PECAB3726Data Visualization Techniques and Tools300303
Elective IV
5PECAB3727Data Classification Methods and Evaluation300303
5PECAB3728Principles of Deep Learning300303
DEPARTMENT OF COMPUTER APPLICATIONS