The Department of Computer Science organized a session on “Practical Approach to Data Science” on 4th March 2023, from 10.30 am to 1.30 pm for the faculty members and TYBCA, TYB.Voc(ST) students. The Resource Person was Mr. Abhijeet Mhamal, Senior Data Scientist, Worley Enterprise Services, Worley.
The session began with a welcome by TY BCA student Ruchika Chaudhary, followed by an address of the Principal, who emphasized the importance of such sessions in helping students stay updated with the latest trends and advancements in technology. Student Prachi Naik from TYB.Voc(ST) then introduced the Resource Person, who has several years of experience in the data science field.
Mr. Mhamal commenced the session by discussing the importance of data science in the current world, and how it is transforming the way businesses operate. He then spoke about various courses available in the data science field and shared his experiences of working in the industry. He explained the roadmap in data science and spoke about various job roles available for data science professionals.
He highlighted different tools and techniques used in the field. He also added that students have to undergo various certifications in Data Science for better career prospects in the field. During his interaction with the students, he focused on the importance of various domains in the field, such as AI and Machine Learning.
In the second half of the session, Mr. Mhamal gave a demo lesson on Power BI, a business analytics service by Microsoft. He explained how it can be used to analyze and visualize data, and how it can help businesses make data-driven decisions. He gave examples of how Power BI is used in the industry and showed the students how to create a dashboard using the tool.
The session concluded with a Vote of Thanks proposed by the student Miss. Clancy Fernandes from TYBCA. 64 participants (students& teachers) benefited by attending this session. Overall, the session was informative and engaging, and it helped students understand the practical aspects of data science.
