Computer Science and Engineering (Artificial Intelligence and Data Science)
About Program
Career prospects Career prospects for Computer Science and Engineering (Artificial Intelligence and Data Science) are highly promising due to the rapid digital transformation across industries. Graduates in this field are in demand as organizations increasingly rely on data-driven decision-making. AI & DS professionals can work in roles such as Data Scientist, Machine Learning Engineer, AI Engineer, Data Analyst, and Business Intelligence Developer. These roles involve analyzing large datasets, building intelligent models, and developing predictive systems. Industries like IT, healthcare, finance, e-commerce, manufacturing, education, and cybersecurity actively hire AI & DS graduates. With the growth of technologies such as big data, cloud computing, IoT, and automation, career opportunities continue to expand. Graduates can also pursue careers in research and development, contributing to innovations in robotics, natural language processing, and computer vision. Higher studies such as M.Tech, MS, or PhD in AI, Data Science, or related fields further enhance career growth. Many graduates also explore entrepreneurship, developing AI-based startups and solutions. Overall, CSE (AI & DS) offers strong job security, high salary potential, and long-term career growth in a technology-driven future.
Message from the Head of the Department Computer Science and Engineering (Artificial Intelligence and Data Science)- Dr. Ravindra Jogekar
Welcome to the Department of Computer Science and Engineering (Artificial Intelligence and Data Science). The rapid advancements in AI and Data Science are redefining the way we live, work, and innovate, and our department is dedicated to preparing students to lead this transformation with knowledge, creativity, and integrity.
We offer a future-focused curriculum that blends strong fundamentals of computer science with cutting-edge technologies such as artificial intelligence, machine learning, data analytics, and intelligent systems. Emphasis is placed on experiential learning through modern laboratories, industry interactions, research activities, internships, and project-based learning, enabling students to gain practical exposure and problem-solving skills.
Our experienced and committed faculties strive to create an environment that encourages innovation, critical thinking, and continuous learning. Along with technical excellence, we focus on nurturing professional ethics, teamwork, leadership, and adaptability to meet global challenges.
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UG Progra
PEO
PEO1: Graduates will apply the principles of Artificial Intelligence, Data Science, and allied computing technologies to develop effective and sustainable solutions for real-world challenges.
PEO2: Graduates will build successful careers in industry, academia, research, or entrepreneurship by utilizing modern AI tools, innovative practices, and emerging technologies.
PEO3: Graduates will demonstrate professional ethics, effective communication, teamwork, leadership, and social responsibility while addressing societal, environmental, and legal issues.
PEO4: Graduates will pursue higher education, professional development, research, and lifelong learning to adapt to evolving technologies and contribute to continuous innovation.
PSO
PSO1: AI & Data Analytics Proficiency: Apply principles of Artificial Intelligence, Machine Learning, Deep Learning, Data Science, and Big Data Analytics to develop intelligent and data-driven solutions for real-world problems.
PSO2: Intelligent System Development: Design, develop, and deploy AI-enabled software applications using modern programming languages, cloud platforms, data engineering tools, and emerging technologies.
PSO3: Research, Innovation & Entrepreneurship: Analyze complex computing problems through research, innovation, interdisciplinary collaboration, and entrepreneurial practices to create sustainable and impactful solutions.
PSO4: Professional Ethics & Lifelong Learning: Demonstrate professional ethics, effective communication, teamwork, leadership, and continuous learning while considering societal, environmental, and legal aspects in AI and Data Science applications.
Faculty Profile
| Department of Computer Science and Engineering(AI&DS) | |||||||
| Sr. No. | Full Name of Faculty | Date of Birth | Qualification | Designation | Date of Joining | Experience | |
| 1 | Dr Ravindra Namdeorao Jogekar | 24.06.1979 | PhD(CSE) | Head and Associate Professor | 13.03.2024 | 24 Years | |
| 2 | Mr. Shubham Gajanan Unhale | 21.05.1997 | M. Tech. | Assistant Professor | 29.06.2026 | 6 Years | |
| 3 | Mr. Pradip Pralhad Athawale | 06.08.1982 | M. Tech. | Assistant Professor | 29.06.2026 | 3 Years | |
| 4 | Ms. Bhagyashree Durgaprasad Upadhaya | 24.06.1991 | M. Tech. | Assistant Professor | 01.07.2024 | 2 Years | |
| 5 | Mrs. Shraddha Dnyaneshwar Kawadkar | 17.02.1993 | M. Tech. | Assistant Professor | 01.07.2025 | 1 Year | |
| 6 | Mrs. Pranjali Kunal Padole | 15.01.1991 | M. Tech. | Assistant Professor | 01.07.2025 | 1 Year | |
Forum
Student Forum – CSE(AI&DS)
Achivements
Students Achievement
Abhir A. Kapse and Anshkumar S. Pandey participated in the National Financial Literacy Quiz, organized and sponsored by the National Institute of Securities Markets (NISM) and SEBI. The quiz was held on 18th July 2026 in Mumbai.
We are proud to announce that Prince Jaiswal and Lakhan Tukaram Pawar have been selected as Google Student Ambassadors for 2026. This prestigious recognition reflects their technical skills, leadership qualities, and active involvement in the student technology community. Their selection is a proud achievement for the institute and serves as an inspiration to fellow students to pursue innovation, learning, and leadership in the field of technology.
Faculty Achievement
| Sr. No, | Name of Faculty | Title of Paper | Journal | Vol. No | Issue No. | ISSN No. & Page No. | DOI | Indexing |
| 1 | Dr. Ravindra N. Jogekar | An Integrated Hybrid Artificial Intelligence Framework For Early Autism Spectrum Disorder Screening Using Random Forest Classification And Resnet18 Transfer Learning | Adolescencia e Saude | 21 | 6 | 1679-9942177-5281
Pg. 829-844 |
https://doi.org/10.67440/ahj.v21i6s.1698 | Scopus |
Placements
Batch is in 2nd Year
Overview
CSE(AI&DS) is committed to providing quality education and developing skilled professionals in emerging technologies. The department offers students a strong foundation in Artificial Intelligence, Data Science, Machine Learning, and related computing technologies.
With modern computational infrastructure, practical learning, and exposure to advanced technologies, students are encouraged to develop strong technical and problem-solving skills. The department promotes hands-on learning through projects, workshops, industry interaction, and collaborative research.
Department also focuses on innovation, professional ethics, communication, teamwork, and lifelong learning. Students are encouraged to explore research, entrepreneurship, and real-world applications of AI and Data Science to address industry and societal challenges.
With a student-centric approach and continuous focus on emerging technologies, the department strives to develop competent, innovative, and socially responsible professionals who are prepared for successful careers in industry, research, higher education, and entrepreneurship.
Vision & Mission
Vision
To emerge as a center of excellence in Artificial Intelligence and Data Science by imparting quality education, fostering innovation and research, and developing socially responsible professionals capable of addressing real-world challenges.
Mission
M1: To provide a strong foundation in Artificial Intelligence, Data Science, and allied computing technologies through outcome-based education, hands-on learning, research, and industry collaboration.
M2: To nurture ethical values, innovation, lifelong learning, leadership, and social responsibility, enabling graduates to contribute effectively to industry, academia, entrepreneurship, and society.
Salient Features
- Industry-Focused Education– Learning based on current industry needs and emerging technologies.
- Practical Learning– Hands-on experience through labs, projects, workshops, and real-world applications.
- AI & Data Science Skills– Strong focus on Artificial Intelligence, Machine Learning, Deep Learning, Data Analytics, and Big Data.
- Modern Technology Exposure– Training in programming, cloud computing, data engineering, and modern AI tools.
- Research & Innovation– Encouragement for research, innovative projects, publications, and technical competitions.
- Industry Interaction– Guest lectures, internships, industrial visits, workshops, and interaction with industry experts.
- Entrepreneurship Opportunities– Encouraging students to develop innovative ideas and explore start-up opportunities.
- Real-World Projects– Students work on practical projects that address industry and societal challenges.
- Ethics & Responsible AI– Focus on data privacy, professional ethics, responsible AI, and social responsibility.
- Skill & Career Development– Development of communication, teamwork, leadership, problem-solving, and professional skills.
- Continuous Learning– Encouraging students to learn new technologies and adapt to the rapidly changing IT industry.
- Socially Relevant Solutions– Promoting technology solutions that contribute to society, sustainability, and the environment.