- EAPCET / ECET / ICET Code: VMEG
CSE (AI & ML)
Department of Computer Science and Engineering (Artificial Intelligence & Machine Learning)
Department of Computer Science and Engineering (Artificial Intelligence & Machine Learning)
The Industry–Institute Interaction (III) Cell of the Department of Computer Science & Engineering (Artificial Intelligence & Machine Learning) serves as a vital platform connecting academia with the rapidly advancing AI-driven industry ecosystem. It fosters strategic collaborations with leading technology organizations to enrich academic learning with practical exposure in areas such as Artificial Intelligence, Machine Learning, Data Science, Deep Learning, and Intelligent Systems. The cell organizes internships, industrial visits, expert talks, hackathons, technical workshops, and collaborative projects focused on cutting-edge domains like Natural Language Processing, Computer Vision, Generative AI, and Big Data Analytics. By involving industry experts in curriculum design, mentoring, and guest lectures, the III Cell ensures that the program remains aligned with evolving industry standards and workforce expectations. Through industry-sponsored projects, live problem statements, and applied research initiatives, students gain hands-on experience in designing, developing, and deploying AI-based solutions. This exposure enhances their problem-solving ability, analytical thinking, and innovation skills. Furthermore, the cell promotes interdisciplinary learning, teamwork, ethical AI practices, and professional competencies, preparing students to become skilled AI engineers, data scientists, and technology leaders capable of addressing real-world challenges in a digitally transforming global landscape.
The Department of Computer Science and Engineering (AI & ML) has established robust academic–industry collaborations through Memoranda of Understanding (MoUs) with leading IT firms, AI-driven enterprises, research laboratories, and technology organizations. These partnerships provide students with opportunities for internships, industrial training, expert lectures, AI/ML-focused workshops, hackathons, and hands-on experience in domains such as Machine Learning, Deep Learning, Data Science, Natural Language Processing and Computer Vision. The MoUs further facilitate collaborative research, consultancy services, innovation-driven projects, and the development of intelligent systems aligned with emerging industry requirements. Special emphasis is placed on real-world problem-solving using AI technologies, enabling students and faculty to work on industry-relevant datasets, tools, and platforms. Such collaborations effectively bridge the gap between theoretical foundations and practical AI applications, enhancing analytical thinking, technical expertise, and employability in cutting-edge domains. They also foster a strong culture of research, innovation, and entrepreneurship within the department. Through these sustained partnerships, the department ensures continuous knowledge exchange, integration of contemporary AI/ML advancements into the curriculum, and long-term collaborative growth between academia and the intelligent technology ecosystem.
| # | Name of the Industry | Nature of MoU | Activities & Outcomes |
|---|---|---|---|
| 1 | AltSense | Student and Faculty Training | Mentorship programs, Workshops, Seminars, Hackathons, Internships and Training programs |
| 2 | MassMutual, RR District, Telangana | Centre of Excellence | Mentorship programs, Workshops, Seminars, Hackathons, Internships and Training programs |
| 3 | Evernorth Health Services | Centre of Excellence | Mentorship programs, Workshops, Seminars, Hackathons, Internships and Training programs |
| 4 | Google Cloud | Student and Faculty Training | Google Cloud Associate certification |
| 5 | India Drone Academy | Student and Faculty Training | Mentorship programs, Workshops, Seminars, Hackathons, Internships and Training programs |
| 6 | Infisum Modeling Pvt Ltd | Student and Faculty Training | Mentorship programs, Workshops, Seminars, Hackathons, Internships and Training programs |
| 7 | Ui-Path | Student and Faculty Training | RPA course as 3-credit elective |
| 8 | Oracle Academy | Software Support | License free Oracle Software & Oracle Sun Corporation Courses for student and faculty |
| 9 | AWS Educate | Free tier AWS Cloud | Free Access to AWS Cloud, AWS and RPA certification |
| 10 | Indian Servers Pvt Ltd, Vijayawada, A.P | Internships | Student Training and Internships |
| 11 | Cisco Networking Academy, India | Career Development | Faculty and Student Training and Certifications |
| 12 | Red Hat India Private Limited | Career Development | Faculty and Student Training and Certifications |
| 13 | ARK Info Solutions | AR/VR Projects | AR/VR workshop, training programs and projects |
| 14 | Cyber Security Centre of Excellence Telangana (DSCI) | Innovation and Training | Research, Innovation, Incubation, marketing, hackathons, corporate innovation and Training programs |
| 15 | Talent Sprint Pvt Ltd, Hyderabad, Telangana | Innovative Projects | Innovative teaching methods which carry an emphasis on fast changing technological trends |
The Department of Computer Science and Engineering (AI & ML) actively facilitates internships with leading IT companies, AI-focused enterprises, startups, and research organizations to strengthen students’ practical exposure and industry readiness in intelligent technologies. Through these opportunities, students gain hands-on experience in real-world projects involving Machine Learning models, Deep Learning frameworks, Data Analytics pipelines, Natural Language Processing, Computer Vision, and AI-driven applications. This experiential learning enables students to apply theoretical AI/ML concepts to practical challenges, develop strong analytical and problem-solving abilities, and gain proficiency in industry-standard tools and platforms such as Python-based ecosystems, Cloud AI services, and data engineering frameworks. It also helps students understand model development life cycles, data handling, deployment practices, teamwork, and professional ethics in AI-based environments. Internships significantly enhance students’ employability, technical competence, and confidence while offering valuable exposure to emerging career roles such as AI Engineer, Data Scientist, ML Developer, and Research Associate. Overall, these experiences prepare students to meet the rapidly evolving demands of the global AI and data-driven technology landscape.
Industrial visits are an integral component of the learning ecosystem in the Department of Computer Science and Engineering (AI & ML), providing students with valuable exposure to real-world AI-driven industries and intelligent system deployments. These visits enable students to observe the practical implementation of Machine Learning Models, Data Analytics pipelines, AI-powered applications, cloud-based AI services, and large-scale data processing environments in leading technology companies, startups, and innovation centers. By witnessing how theoretical AI/ML concepts are applied in real scenarios, students gain deeper insights into model development life cycles, data preprocessing, algorithm selection, deployment strategies, and performance evaluation. Exposure to areas such as natural language processing, computer vision systems, recommendation engines, and automation solutions further enriches their understanding of modern intelligent technologies. Interaction with industry experts during these visits enhances students’ technical awareness, analytical thinking, and professional perspective. It also provides clarity on current industry trends, tools, and career pathways in AI and data-driven domains. Such experiential learning effectively bridges the gap between academic knowledge and industrial practices, equipping students with the skills, confidence, and adaptability required to excel in the rapidly evolving field of Artificial Intelligence and Machine Learning.
