Amity Institute of Biotechnology organized lecture on Data Science and its Industrial Applications on 15th April 2021.
The event's objective was for the students to overview the real-life applications of data science. The event gave the students an ample opportunity to interact with the industry experts from the Data Science domain. Needless to mention that the domain is becoming a significant discipline for mining, managing, and analysing the large volume of data.
The speakers shared their experiences and discussed the need or requirements in students to become data scientists. They discussed their business models in their organizations and talked about data analysis methods and algorithms. The speakers also briefed the scenarios and problems where data science can offer a better solution.
Mr. Rakesh Tripathi, Principal Data Scientist at Embibe, Bengaluru talked about their business models and how different algorithms are helpful for data analysis.
Dr. Krishan Kumar, Manager R&D, Gennova Biopharmaceuticals, Pune introduced the Pre Hospital Thrombolyse Model they have developed. He talked several examples of Data Science and problem.
Mr. Siddhartha S, Associate Director, Data & Analytics Leader, Global Delivery Services, EY Knowledge, Ernest and Young, Gurugram introduced the conceptual problem of knowledge culture. He talked about Knowledge Management Ecosystems, and also discussed several guidelines and advices for students.
Dr. Surendranath Reddy, Assistant Professor, School of Mathematical Sciences, SRTM University, Nanded, Maharashtra. demonstrated the application of singular value decomposition in recommendation systems and also discussed content and collaborative based filtering methods while establishing associations in large datasets.
Mr. Chandan Sharmai, Senior Group Manager – WNS Global Services, Gurugram talk was quite interactive and demonstrated the application of NLP in healthcare and life science systems.
Mr. Saurabh Gupta, Data Science Manager Maven Wave Partners – An Atos Company, Gurugram. talked about several use cases of data science, and discussed the complete life cycle of Machine learning approach. He also emphasized the areas where one should focus while building machine learning models
Total 83 faculties and 33students participated in the session.