NSHM Kolkata Reviews on Placements, Faculty and Facilities

New Alipore, KolkataEstd 2006 MAKAUT, Nadia NAAC Grade A+

Why To Join NSHM Kolkata - Reviews & Rating

General
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General
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3.9
& Win Monthly Prizes Up to ₹1 Lakh/-*
5(50%)
4(39%)
3(6%)
2(4%)
1(1%)

Academic
4.2
Faculty
4.0
Infrastructure
4.2
Accommodation
3.5
Social Life
4.0
Placement
4.0

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Sushmita saha
5.0Helpful
Reviewed on Feb 19, 2025(Enrolled 2023)

Course Curriculum Overview:

Specifically I love to find chemistry between food and our body. And also love to work for communities and people those who suffers but can't find solution even with medication. And here this college makes me more confident by their frequent seminars and presentations , conferences, field work. There was exam in every month that was internal known as CAs. Then final semester. Teachers also discuss with previous year question papers .
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Brishti Bandyopadhyay
Brishti Bandyopadhyay
3.8
Reviewed on Feb 6, 2025(Enrolled 2024)

Course Curriculum Overview:

It has a clinical specialization which I needed for myself, this making me choose this course. Papers may come with respect to theories as taught in class or they may test your understanding of the concepts. Most of the resources are provided, however it will be helpful if more resources are provided. It will seem almost impossible to give continuous exams each month while attending classes. Also attendence is very strictly monitored.
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SUBHRADYUTI JANA
SUBHRADYUTI JANA
4.5
Reviewed on Oct 15, 2023(Enrolled 2023)

Student Snaps:

Course Curriculum Overview:

Course Curriculum: The course curriculum should cover a wide range of relevant topics in data science and analytics. It should include theoretical concepts, practical applications, and industry-related projects. Real-world case studies and the integration of the latest tools and technologies are essential. Reason for Choosing the Course: You might choose a data science and analytics course for its relevance in the job market, the opportunity to work with data or your interest in the field. Faculty: Faculty members should ideally have strong academic backgrounds and industry experience in data science. A lower faculty-to-student ratio often allows for more personalized attention. Teaching Methods: Effective teaching methods might involve a combination of lectures, practical exercises, and hands-on projects. Faculty should be approachable, engaging, and responsive to students' needs. Timeliness of Exams: Timely term exams and result publication are crucial for smooth.
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INDRITA GANGULY
INDRITA GANGULY
2.6Helpful
Reviewed on Mar 5, 2020

Remarks:

The college should work hard on the placement part and invite placements from other companies too. The salary packages should be increased especially for this course. the infrastructure should be worked on effectively. Food availabilities should be increased.
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