Department of Computer Science & Engineering ( Data Science )

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Department of Computer Science & Engineering ( Data Science )

  •  
    Started
    2020
  •  
    Intake
    120
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    DTE Choice Code
    517291210

Dr. U. M. Patil

Head of Department

The Department of Computer Science & Engineering (Data Science) at R. C. Patel Institute of Technology (RCPIT), Shirpur was established in 2020 to address the rapidly growing global demand for skilled data science professionals. The department offers an undergraduate program in Data Science designed to provide students with comprehensive knowledge in data analysis, algorithmic thinking, and statistical modeling—equipping them to transform data into actionable insights.

Data Science is an interdisciplinary domain combining mathematics, statistics, computer science, information science, and domain-specific knowledge to analyze both structured and unstructured data. It encompasses key areas such as data mining, machine learning, big data analytics, business intelligence, and artificial intelligence.

As industries across sectors—finance, marketing, healthcare, IT, banking, and e- commerce—increasingly rely on data-driven decision making, Data Science has become one of the most in-demand careers globally. The role of a Data Scientist is recognized by leading companies like IBM as the “21st century’s most attractive job,” offering high growth potential and global career opportunities.

Vision

To become a center of excellence in Data Science education and research by nurturing technically proficient professionals with strong ethical values.

Mission

  • M1: To impart quality education in Data Science using state-of-the-art technologies and methodologies.
  • M2: To foster analytical thinking, innovation, and industry-oriented skill development.
  • M3: To create responsible professionals who can contribute to society through data-driven solutions.

Program Educational Objectives (PEOs)

  • PEO1: To enhance their knowledge and skills through certifications, research, or self-learning to stay current with evolving technologies.
  • PEO2: To data-driven decision-making and digital transformation in industry and society, adhering to ethical and sustainable practices.
  • PEO3: To demonstrate leadership, teamwork, and effective communication in multidisciplinary environments.

Program Specific Outcomes (PSOs)

  • PSO 1: Design and develop scalable data-driven systems and AI-enabled applications using modern programming languages, tools, and cloud platforms.
  • PSO 2: Integrate ethical practices and societal concerns into the development of data science and AI solutions to ensure fairness, transparency, and accountability.

Key Highlights of the Department

  • Qualified Faculty: 4 out of 12 faculty members hold Ph.D. degrees with specializations in data science, machine learning, or artificial intelligence.
  • Graduate Success: Over 268 students have enrolled since inception, with placements in data-driven and tech-driven companies.
  • Research & Publications: 34 + research papers published; 2 + patents filed or granted.
  • Industry Alignment: Curriculum includes industry-relevant tools and platforms such as Python, R, TensorFlow, Tableau, Power BI, and Hadoop.
  • Hands-On Learning: Practical exposure through mini projects, capstone projects, and industry assignments in every semester.
  • 6+ Modern Laboratories Well-equipped laboratories for Data Science.
  • Certifications: Support for students pursuing certifications in NPTEL, SWAYAM, IBM, Microsoft Learn, Google Cloud, etc.
  • Career-Oriented Training:
    • Regular aptitude and soft skill sessions
    • Mock interviews, resume building, and career guidance
    • Internship and placement support through central T&P cell
  • Hackathons & Competitions: Participation in national and regional level coding challenges, hackathons, and data-thons.
  • Modern Infrastructure: Labs equipped with high-performance computing systems, licensed software, and data analytics platforms.
  • Alumni & Industry Connect: Frequent guest sessions and mentoring from professionals working in top tech and analytics companies.
  • Global Relevance: Students trained to meet international standards for careers in AI, ML, data analytics, business intelligence, and research.

Student Development & Learning Culture

  • Emphasis on project-based learning, real-time case studies, and industry-led capstone projects.
  • Encouragement to pursue internships in data-centric companies and startups.
  • Active student clubs and coding communities to foster peer learning and innovation.
  • Focus on ethics in data handling, privacy, and responsible AI.

The Department of Computer Science & Engineering (Data Science) at RCPIT is a future-focused department that empowers students with deep analytical skills, technological expertise, and ethical responsibility. With strong academic foundations and active industry engagement, the department prepares students to excel as data scientists, AI specialists, and analytics professionals in a data-driven world.