| UG Degree course offered | Bachelor of Engineering (Computer Science & Engineering (Data Science)) |
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| UG Course Duration | 4 Years |
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| UG Year of Establishment | 2020 |
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| UG Intake | 60 |
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| Approved by | AICTE, New Delhi |
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| Affiliated to | Shivaji University, Kolhapur |
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| College DTE Code | EN 6839 |
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| DTE General Choice Code | 683924210 |
Department Information
Today, when we look around, the technological advances in recent years have been immense. We can see driverless cars, hands-free devices that can turn on the lights, and robots working in factories, which prove that intelligent machines are possible. In the last four years in the Indian startup ecosystem, the terms that were used (overused rather) more than funding, valuation, and exit were Artificial Intelligence (AI) and Data Science.
Every sector of the economy now has access to more data than would have been imaginable even a decade ago. Businesses today are accumulating new data at a rate that exceeds their capacity to extract value from it. The question facing every organization that wants to attract a community is how to use data effectively, not just their own data, but all of the data that’s available and relevant. But there is a talent gap that helps in the implementation of Big Data.
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Artificial Intelligence market is expected to grow exponentially, it globally recognized as a key driver of digital transformation. AI has now penetrated in entire service sector. There is rarely any field which is untouched by Artificial Intelligence hence generating lakhs of vacancies for skilled professionals by 2025.
Data Science is the future of Artificial Intelligence which has grown significantly in last few years. This Program enables students to develop smart systems with a leading-edge combination of AI & Data Science technologies like, Artificial Intelligence, Machine Learning, Data Science and Statistics, Big Data Analytics, Computer Vision, Business Intelligence, Deep Learning and Reinforce learning, Robotics, Robotic Process Automation, Genetic Algorithms, Natural Language Processing.
Expected vision can be achieved by an approach involving rigorous and comprehensive academic course work covering theory, fundamentals and hands-on experience with real-world applications. The Program is strongly oriented towards industry and emphasizes industry internship, projects, and entrepreneurship. It is expected that the graduates of the proposed program will mostly join the fast growing Data Analytics industry as technical experts and few will even launch their own IT start-ups in this field. This will be based on curriculum specified by Shivaji University.
- • Data is the oil for today’s world. With the right tools, technologies, algorithms, we can use data and convert it into a distinctive business advantage
- •Data Science can help you to detect fraud using advanced machine learning algorithms
- • It helps you to prevent any significant monetary losses
- • Allows to build intelligence ability in machines
- You can perform sentiment analysis to gauge customer brand loyalty
- It enables you to take better and faster decisions
- • Helps you to recommend the right product to the right customer to enhance your business
Vision
To become a pioneer department in the field of computer science & engineering with a specialization in the data science domain with a focus to produce professional & socially responsible engineers.
Mission
M1:Â To adopt the best practices for outcome-based learning.
M2: To enable the graduates to use modern tools, to design  and develop data science-based applications.
M3:Â To ensure the responsible use of data to benefit society.
Program Educational Objectives (PEOs)
PEO-1: To enhance fundamental understanding of mathematics, science, and computer science in engineering students.
PEO-2: To prepare the students as per the industry needs.
PEO-3: To train students to function and communicate effectively, both individually and with multidisciplinary teams.
PEO-4: To engage students in postgraduate education & certification courses.
Programme Outcomes (POs)
Computer Science and Engineering graduates will be able toÂ
PO1: Engineering knowledge: Apply the knowledge of mathematics, science, engineering Fundamentals and an engineering specialization to the solution of complex engineering Problems.
PO2: Problem analysis: Identify, formulate, review research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.
PO3: Design/development of solutions: Design solutions for complex engineering problems and design system components or processes that meet the specified needs with appropriate consideration for the public health and safety, and the cultural, societal, and environmental considerations.
PO4: Conduct investigations of complex 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.
PO5: 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.
PO6: 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.
PO7: 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.
PO8: Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
PO9: Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
PO10: Communication: Communicate effectively on complex engineering activities with the engineering community and with 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.
PO11: Project management and finance: Demonstrate knowledge and understanding of the 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.
PO12: Life-long learning: Recognize the need for, and have the preparation and ability to engage in independent and life-long learning in the broadest context of technological change.
Program-Specific Outcomes (PSOs)
PSO1: Professional Skills:Â Apply the concepts and practical knowledge in analysis, design and development of data systems and applications to multi-disciplinary problems.Â
PSO2: Competency: To provide a concrete foundation and enrich their abilities to qualify for Employment, Higher studies and Research in Data science with ethical values.
DEPARTMENTAL ADVISORY BOARD (DAB)
           The Departmental Advisory Board (DAB) has been framed with the objective of remaining up to date with the latest requirements of the industry and incorporating necessary components in the curriculum as much as possible.
           The DAB is composed of members from eminent institutions as well as members from industry, alumni and members of faculty of the department. The present composition of the DAB is as follows
S.No | Name of the Member | Designation | Role |
1 | Dr. Suresh D. Mane | Principal | Chairman |
2 | Dr. Chetan Arage | Professor & Head | Convener |
3 | Mr. S. D. Bhopale | Associate Professor | Co-Convener |
4 | Dr. Shivprasad More | Associate Professor in AIML DKTE, Ichalkaranji | Academic Expert |
5 | Mr.Ashutosh Powar | Revolution IT Solutions,Kolhapur | Industrial Expert |
6 | Mr. Jagannath. V. Ware | Dean (Academics), Assistant Professor | Member (Faculty) |
7 | Mr. Sanjiv S Deshpande | Assistant Professor( Electrical Department) | Member (Faculty) |
8 | Mrs. Preeti. M. Bhosle | Training & Placement Officer (TPO) | Member (TPO) |
9 | Nandaniwala Zaid Kausar | Final year Student | Member (Student) |
10 | Revati Sarjerao Patil | Final year Student | Member (Student) |
11 | Mr. Uttam Sajane | Â | Member (Parent) |
12 | Mr. Padmakar Modak | Â | Member (Parent) |
Sr. No. | Type of Innovative Teaching Methods | Description | Remarks of Comments etc. |
1 | Google Classroom | Faculty Members delivers important Concepts using this mode also | Source: Google Inc. |
2 | MOODLE | Student feedback, Assignments & information is available to students on MOODLE for use | Â |
3 | ICT / PPTs   | Use of ICT is also employed by faculty | Source: Self Prepared PPTs |
4 | Virtual Labs | Use of Virtual Lab is also employed by faculty | Source: COEP,IITs etc. |
5 | NPTEL Videos | Effective Teaching is carried out with help of NPTEL Videos also. | Source : IITs |
6 | Spoken Tutorials | Students are made available with Spoken Tutorials Lectures | Â |
7 | Group Discussion/Pair-Think-Share | In classroom Group Discussion is carried out for effective learning | Â |
8 | Industrial Visits/seminars/Workshop   | Industrial Visits, Seminars, Expert Lecture & Workshop are conducted in order to help students to learn beyond syllabus |   Resource Persons from Vast Area of Expertization |