Organizer: Department of Artificial Intelligence & Machine Learning Engineering
Introduction:
The Department of Artificial Intelligence and Machine Learning Engineering, Zeal Polytechnic, Narhe, Pune organized an industrial visit on 20th January 2026 for Third Year Diploma AIML students at SevenMentor. The visit was arranged with the objective of providing students with practical exposure to industry practices related to the Machine Learning Life Cycle / Data Science Life Cycle.
A total of 68 students from Third Year Diploma in Artificial Intelligence and Machine Learning participated in the industrial visit. The visit aimed to help students understand how theoretical concepts learned in the classroom are applied in real-world industry scenarios.
During the visit, industry experts from SevenMentor explained the Machine Learning Life Cycle and Data Science Life Cycle, covering various stages such as problem definition, data collection, data preprocessing, exploratory data analysis, model building, evaluation, deployment, and maintenance. Students were also introduced to industry tools, workflows, and best practices followed in real-time projects.
The session was interactive, allowing students to actively engage with the experts and clarify their doubts related to data handling, model selection, industry expectations, and career opportunities in the fields of machine learning and data science. This industrial visit was part of the department’s continuous efforts to bridge the gap between academic learning and industrial applications.
The primary objective of the industrial visit was to expose students to real-world applications of machine learning and data science concepts. The visit focused on enhancing students’ understanding of industry workflows, practical challenges, and professional expectations, thereby improving their technical readiness and employability.
Objective/Purpose:
The primary objective of the industrial visit was to provide Third Year Diploma AIML students with practical exposure to the Machine Learning Life Cycle and Data Science Life Cycle as followed in the industry. The visit aimed to help students understand real-world applications of data collection, preprocessing, model development, evaluation, and deployment. It also focused on familiarizing students with industry tools, workflows, and professional practices, thereby bridging the gap between academic learning and industrial requirements and enhancing students’ career readiness.
Outcomes:
- Students gained practical understanding of the Machine Learning Life Cycle and Data Science Life Cycle followed in the industry.
- The visit helped students connect theoretical concepts with real-world applications and industry practices.
- Students received valuable insights into tools, technologies, and skills required for machine learning and data science roles.
- Active student participation reflected increased interest, awareness, and confidence regarding careers in AIML and data science domains.
Conclusion:
The industrial visit to SevenMentor was successfully conducted and achieved its objectives by providing students with hands-on exposure to industry workflows and practices. The interaction with industry professionals helped students gain clarity on technical concepts, career pathways, and industry expectations. Overall, the visit was informative and beneficial, emphasizing the importance of organizing similar industrial visits in the future to strengthen students’ practical knowledge and industry readiness.
