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About Department Research/ INDUSTRY INTERACTION Placements Key Features of curriculum Events/Activities Carrers Prospects Students Achievements About Department Research/ INDUSTRY INTERACTION Placements Key Features of curriculum Events/Activities Carrers Prospects Students Achievements Sr. No. Name Company Names 1 Shruti Fadnavis IBM, Accenture 2 Akhilesh Mishra IBM 3 Akhilesh Dhoot IBM 4 Rutuja Thakre IBM 5 Mrunal Lad IBM 6 Vedansh Jaiswal IBM 7 Vanshita Lalwani IBM 8 Ishan Chinchghare IBM, Accenture 9 Anvi Burde Vconstruct , Accenture 10 Chirag Lalwani Vconstruct , Accenture 11 Sanskriti Gupta Vconstruct 12 Vishakha Sharma IBM 13 Mohammed Saad Hussain IBM 14 Mohammed Zubair Hussain IBM 15 Revanta Tomar IBM 16 Sonakshi Sahu IBM 17 Rohit Chandak Accenture 18 Vedant Mahajan Accenture 19 Sunishka Malviya Accenture 20 Vanshita Chandarana Accenture 21 Manasi Pampattiwar Accenture 22 Kushal Gujar Accenture 23 Pratik Bhattacharya Accenture 24 Gaurav Iyer Accenture 25 Arya Harde Accenture 26 Suyash Gabhane Accenture 27 Piyush Hatewar Accenture 28 Devyani Kalamkar Accenture 29 Shrey Gupta Accenture 30 Khushi Kasat Accenture 31 Harsh Gupta Accenture 32 Harsh P. Upadhye Accenture 33 Prashant Prithyani Softlink 34 Tanmay Jain Accenture

About Department Research/ INDUSTRY INTERACTION Placements Key Features of curriculum Events/Activities Carrers Prospects Students Achievements About Department Research/ INDUSTRY INTERACTION Placements Key Features of curriculum Events/Activities Carrers Prospects Students Achievements July-September 2023 2022-23

About Department Research/ INDUSTRY INTERACTION Placements Key Features of curriculum Events/Activities Carrers Prospects Students Achievements About Department Research/ INDUSTRY INTERACTION Placements Key Features of curriculum Events/Activities Carrers Prospects Students Achievements Career Prospects Data Science graduates have a broad range of career opportunities in virtually every industry, such as finance and insurance, professional services, IT and many other sectors. Some of the Data Science job roles in demand are Data Scientist, Statistician, Data Analysts, Business Analysts, Data Engineer, Machine Learning Engineer, Quantitative Analyst, Data Warehouse Architect, Business Intelligence Analyst, Systems Analyst, Marketing Analyst, Operations Analyst. Some top-notch data science companies across the globe working in the field of data science are : Numerator, Cloudera, Splunk, SPINS, Alteryx, Civis Analytics, Sisense, Oracle, Looker, Teradata. In the Indian market, some prominent recruiters are : Equifax, Gramener, Accenture, Fractal Analytics, Amazon, Deloitte, LinkedIn, MuSigma, Flipkart, IBM, Citrix, Myntra, Juniper Network, Niki.AI, Absentia VR, Sig Tuple, Supertext.ai, Dell, Juniper.

About Department Research/ INDUSTRY INTERACTION Placements Key Features of curriculum Events/Activities Carrers Prospects Students Achievements About Department Research/ INDUSTRY INTERACTION Placements Key Features of curriculum Events/Activities Carrers Prospects Students Achievements Key Features of Curriculum The curriculum is designed to meet the growing demands of the data-driven economy of the future. The theoretical foundations are drawn primarily from Statistics, Computer Science, and Mathematics. A hands-on and case base approach is followed so as to enable the students to have a deeper understanding of the subjects so that they can be better informed about real life applications and it’s implementation. The core computing discipline-specific Knowledge Areas for Data Science incorporated in the curriculum are : Computer Science Fundamentals; Programming, Data Structures, and Algorithms; Artificial Intelligence; Data Handling and Visualization; Machine Learning; Information Security and Privacy; Software Engineering and Testing Methodologies; Deep Learning; Large Scale Data Analytics. Beyond this, through Program Electives students are given the opportunity to study topics in more details. Open Electives and MOOCs provide an opportunity for interdisciplinary learning. The programme offers one full semester industry internship facility to final year students which provides the students an hands-on opportunity to work in their desired field, to develop and refine skills, and to gain valuable work experience. For Syllabus Check here

About Department Key Features of curriculum Carrers Prospects Events/Activities Faculty Placements Research/ INDUSTRY INTERACTION About Department Research/ INDUSTRY INTERACTION Placements Key Features of curriculum Events/Activities Carrers Prospects Students Achievements About Department Research/ INDUSTRY INTERACTION Placements Key Features of curriculum Events/Activities Carrers Prospects Students Achievements Programme Details UG: Under graduate program   B.Tech Computer Science & Engineering(Data Science) Year of Commencement: 2020-21 Intake : 60 increase to 180 in year(2023-2024)   Prof. Aarti Karandikar (HOD) Vision : To continually improve the education environment, in order to develop graduates with strong academic and technical background needed to achieve distinction in the discipline. Excellence is expected in various domains like workforce, higher studies or lifelong learning. To strengthen links between industry through partnership and collaborative development works. Mission : To develop a strong foundation of theory and practices of computer science amongst the students to enable them to develop into knowledgeable, responsible professionals, lifelong learners and implement the latest computing technologies for the betterment of the society. Programme Outcomes of Computer Science & Engineering are: Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems. 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. 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. 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. Modern tool usage: Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools including prediction and modeling to complex engineering activities with an understanding of the limitations. 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. 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. Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice. Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings. 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. 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. Life-long learning: Recognize the need for, and have the preparation and ability to engage in independent and lifelong learning in the broadest context of technological change. PROGRAM EDUCATION OBJECTIVES: Graduates will have a strong foundation of knowledge and skills in mathematics, statistics,programming and computer science to solve problems in data science. Graduates will have the ability and attitude to adapt to emerging technological changes with life long learning skills. Graduates will demonstrate collaborative learning and spirit of team work through multidisciplinary Data Science projects ensure ethical and moral values. Graduates will demonstrate professionalism, ethical attitude, teamwork and leadership skills with lifelong learning in the career. PROGRAM SPECIFIC OUTCOMES (PSOs) : PSO-I) Apply the concepts and practical knowledge of data science in analysis, design and development of computing systems and applications to multi-disciplinary problems. PSO-II) Acquaint with the contemporary trends in industrial/research settings and thereby innovate novel solutions to existing problems.

Career Prospects This Programme aims to bridge the demands of the industry and to produce the high-end and skill oriented AI scientists and engineers for the betterment of the society. Artificial intelligence and machine learning is identified as one of the top areas for jobs and research. The jobs in AI include Soft analysts and developers, computer scientists and computer engineers, AI Algorithm specialists, research scientists, AI & ML Engineer, Business Intelligence Developer, Machine Learning and Artificial Intelligence Scientist, AI Software Engineer etc. Top Companies Operating in AI and ML GOOGLE IBM Intel Alibaba Cloud VMware Yodlee Zs Infosys Amazon Web Services Microsoft Azure NVidia Apple Twitter Informatica Wipro TCS