Data Science

Departmental Profile

Prof. M. M. Raghuwanshi, received Ph.D. in Computer Science Engineering from VNIT, Nagpur and M. Tech. in Computer Science and DP from IIT, Kharagpur. He is having more than 30 years of experience in academic institutions as a Principal and faculty member. As a Principal, he has successfully established a new engineering college at Nagpur and got NBA and NAC in the first six years. Also, fortunate to set-up and lead magnificently the Computer Technology department for more than 15 years at Chandrapur.

He has published about 100 papers in reputed Journals and Conferences. 11 scholars (3 from SVNIT, Surat and 8 from RTMNU, Nagpur) completed Ph. D. under his supervision. From the last 15 years he is actively involved and contributed in research (Citation Index: 878, h-index=13 and i-10 index=19). He has published book on Algorithm and Data Structures, published by Narosa Publishing House, New Delhi, India, with ISBN 978-81-8487-425-9. He is having 12 book chapters to his credit. He is reviewer for IEEE Transaction on Evolutionary Computing, International Journal of Computation and Intelligence review (IJCIR) and Reviewer for IEEE Congress on Evolutionary Computation, IEEE CEC. Session chair and reviewer for many conferences. He is having 5 copyrights to his name.

He worked as a software developer for Siemens – Sietec, Berlin (Germany) and completed M.Tech. thesis work with CDAC, Pune on parallel computing. He headed a team of 50 members to manage 12 centers of RIIT-ART, Chandrapur. RIIT-ART is a C-DAC authorized training center to conduct computer courses in Chandrapur & Gadchiroli. As a software developer he has developed Software’s for Pharmaceutical Distributor, Pathologist, Petrol pump owner, Coal Transporter, Cement Transporter, hotel management, inventory and finance.

He has pPlanned, installed and configured many LAN-WAN based systems in industries (like L&T, Ballarpur Paper Industries, Chandrapur Super Thermal Power Station etc), educational institutions, newspaper publishers, coal & cement transporters. Also worked as TV repair engineer and computer maintenance engineer.

Visited universities in USA, Scotland and UK to get global exposure on higher technical education system. Also worked as a subject expert in NBA committee. he worked on board of studies and various committees of RTM Nagpur University and SGB Amravati University. Conducted workshops on Machine learning, Data science, parallel computing, TOC and evolutionary computing

He is a passionate teacher, who loves to teach & share knowledge with people and eager to learn & practice new technologies. As a motivating leader, he has inspired people to scale new heights in their life. He can gel & work with people to achieve success in life.

Areas of Interest: Evolutionary computing, Genetic Algorithm, Data structures, Algorithm, Compilers, Programming Languages, Parallel computing, Data science, Machine Learning, cloud computing.

Dr. M. M. Raghuwanshi


Data Science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from many structural and unstructured data. Data science is all about using data to solve problems. Data science is bringing together all aspects of technology required for gathering, storing, analysing, and understanding data. This includes storage technology, distributed computing, data-driven modelling, data analytics and mining, visualization, and security, among others.

Data-driven businesses are worth $1.2 trillion collectively in 2020. India has welcomed technology with open arms and with initiatives like ‘Digital India’, it will only encourage the integration of technology in all spheres of life. India had over 564.5 million Internet users in 2020 and the number is consistently increasing. According to a study of the data science job market, 40% of global companies struggle to hire and retain data scientists. 1/3 of the top 400 Indian companies lack state-of-the-art data analysis tools and personnel. Further, the study estimate that 364,000 new jobs will be created in data by 2020 in India. According to a report from NASSCOM, by 2021, the total Data science & AI job openings in India is estimated to go by 2,30,000. But the fresh employable talent or university talent available will be just 90,000, leaving a huge gap of 1,40,000.

GHRCEM, Pune offering a B-Tech program in DATA SCIENCE from session 2020-21. The key highlight of the course would be a core competence in data science, computational mathematics, and statistics, minor specialization in finance, business, health care, retail, medical field. We have designed state-of-the-art syllabus in consultation with a data science expert, the IT industry and academia drew from diverse domains. The proposed B. Tech program is to have a strong emphasis on data science and data engineering for industry perspective, which differentiates it from other computer science and IT program.

The student will be studying basic science and standard engineering subjects along with programming tools required for data science in the first year. In the second and third year, they will be specializing in data science-related topics, along with the required computational mathematics and statistical skills. The core subjects taught include fundamental subjects from computer science along with data analytics, cloud computing & management, machine learning, big data, and deep learning. In the last two semesters, students will specialize in the particular domain area of their interest by studying domain-specific subjects and doing a full semester project in the industry on the domain-related problem. Students taking the course will also intern at companies and take up projects in data science. This program provides ample opportunity for students to specialize in a particular aspect of data science through the electives and the project.

  • To impart quality education and conduct research in data science relevant to needs of the industry, national and international community that will help to improve the quality of human life related to Data Science.

  • To prepare human resource with technical and management skills to meet the contemporary and futuristic Data Science demands of the industry and society at large by delivering relevant curriculum, using the state-of-the-art pedagogical innovations, and undertake relevant research and especially practical on field applications of technology.

Program Offered

Sr. No Sr. No. Programme Level Name of Course Course Type Medium of Instruction Course Establishment Sanctioned Intake
1 UG Data Science Regular English 2020 60


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Program Outcomes (PO)

  • PO 1: Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.
  • PO 2: 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.
  • PO 3: 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.
  • PO 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 the information to provide valid conclusions
  • PO 5: 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
  • PO 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
  • PO 7: 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.
  • PO 8: Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
  • PO 9: Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings
  • PO 10: 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.
  • PO 11: 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.
  • PO 12: 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 Outcome (PSOs)

  • PSO1:The ability to analyse, design and develop software systems applying the knowledge acquired in core courses such as data science, database, machine learning cloud computing big data and software engineering.
  • PSO2:The utilization of skills assimilated in basic Data Science Courses to build up expertise in advanced areas of deep learning, NLP, Cloud security, Image & Vision processing etc.
  • PSO3:Oneself as a global standard Data Science professional with good morals, ethics and sensitivity towards mankind and as a responsible team member.

Program Educational Objectives(PEOs)

Our Graduates in Computer Engineering will be able to demonstrate:

  • PEO 1: To analyse, design and develop cost effective solutions to the real life problems by applying the acquired knowledge.
  • PEO 2: Adoptability to learn latest technological advancement and interdisciplinary approaches by engaging in lifelong learning process.
  • PEO 3: Willingness to pursue higher education, entrepreneurship and research in the field of computer engineering.
  • PEO 4: Being responsible towards society, environment, and ethical responsible team member with interpersonal and leadership skills.

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