BE Artificial Intelligence and Machine Learning
via Sahyadri College of Engineering and Management, Mangalore
BE Artificial Intelligence and Machine Learning
via RVCE Bangalore
Location
Ownership
College Type
Establishment Year
Campus Size
Total Courses Offered
Careers360 Rating
(Engineering and Architecture)
NIRF Rank
(Engineering and Architecture)
-
Approvals
Accreditations
Insight 1/3
Ranking & Accreditations
RVCE Bangalore dipped by 3 spots.
Insight 2/3
Ranking & Accreditations
RVCE Bangalore shows the highest decrease of 3% among all compared colleges.
Insight 3/3
Ranking & Accreditations
RVCE Bangalore has shown a downward trend over the years.
Source: NIRF
Data presented for the year 2024
Total Students Placed
(In Engineering and Architecture)
Graduating Students
(In Engineering and Architecture)
Placement Percentage
(In Engineering and Architecture)
Median Salary LPA
(In Engineering and Architecture)
Student Going Higher Studies
Graduating Students
(overall)
Total Students Placed
(overall)
Placement Percentage
(overall)
Median Salary Lpa
(overall)
Student Going Higher Studies
(overall)
Insight 1/2
Placement Statistics
The average salary of Sahyadri College of Engineering and Management, Mangalore stands highest at 4.75 LPA followed by RVCE Bangalore at 10.50 LPA .
Insight 2/2
Placement Statistics
RVCE Bangalore recruited highest number of students with 992 placements followed by Sahyadri College of Engineering and Management, Mangalore at 314 placements.
Source: NIRF
Course Credential
Degree
Branch
Duration
Mode
Approved Intake
Fees
-
Course Approval
Admission Details
In the admission procedure, allotment of seats and fees structure for all the seats, our College strictly adheres the order of the Government of Karnataka amended from time to time and prevalent at the date of admission. As per the order of the Government of Karnataka, the allotment and distribution of the seats are as follows:
Out of the total seats 45% of the seats are filled by the common entrance test conducted by karnataka examination authority (KEA), 30% of seats are filled through common entrance test conducted by private mangements association (COMED-K) and 25% by management, all by merit.
Eligibility Criteria
Pass in 2nd PUC/12th/Equivalent Exam with English as one of the Languages and a minimum of 45% Marks in aggregate in Physics and Mathematics along with Chemistry/Bio-Technology/Biology/Electronics/Computer Science. (40% for SC, ST, Specified category Candidates).
B.E. LEET - Diploma students should have 50% aggregate marks in all three years.
The basic qualification for eligibility for admission t o B.E. program s is two year Pre-University or 12th Standard or equivalent examination (hereinafter referred to as the Qualifying Examination or Q.E ). The candidate should have taken Physics and Mathematics as compulsory course s along with Chemistry / Biotechnology / Computer Science / Biology / Electronics as optional course s and English as one of the languages of study in the Q .E. Further, the candidate should have passed the Q .E with an aggregate minimum of 45% marks in the optional course s in the Q.E (40% of marks in Q.E in case of SC, ST & OBC Category candidates) for eligibility . The marks obtained by the candidate in Biotechnology / Computer Science / Biology / Electronics in the Q.E., will be considered in place of Chemistry, only for the purpose of determination of eligibility and not for the purpose of determination of rank, in respect of Engineering programme.
Data presented for the year 2025
Total Fees
Total Scholarships Provided
Highest Scholarship Providing Authority
Insight
Fees
Sahyadri College of Engineering and Management, Mangalore released a total of 590 scholarships granted by government bodies. RVCE Bangalore released a total of 1027 scholarships granted by government bodies.
Data presented for the year 2024
Total Students
Total Faculty
Total Male Students
Total Female Students
Total Students Outside State
Insight 1/2
Class Profile
Sahyadri College of Engineering and Management, Mangalore has a lower faculty ratio with 1 faculty over 17 students as compared with the average faculty ratio of private colleges which is 4 students per faculty. RVCE Bangalore has a lower faculty ratio with 1 faculty over 23 students as compared with the average faculty ratio of private colleges which is 4 students per faculty.
Insight 2/2
Class Profile
Sahyadri College of Engineering and Management, Mangalore has lower gender diversity with 36% female students as compared with the gender diversity of private colleges which is 36%. RVCE Bangalore has lower gender diversity with 26% female students as compared with the gender diversity of private colleges which is 36%.
Facilities
Facilities Count
Alumni Associations
Auditorium
Boys Hostel
Cafeteria
Classrooms
Girls Hostel
Gym
I.T Infrastructure
Laboratories
Library
Medical/Hospital
Sports
Transport Facility
Wifi
Banks/ATMs
Boys Hostel
Cafeteria
Girls Hostel
Gym
I.T Infrastructure
Laboratories
Library
Medical/Hospital
Sports
Transport Facility
Wifi
College Infrastructure
Campus Life
Academics
Placements
Value for Money
Total Reviews
Individual Reviews
“ Excellent College for Academic and Personal Growth !!! ”
posted on 2 years ago by Mallika D K G“ Very good college ”
posted on 2 months ago by C MANAMOHAN GOWDA“ I would love to rate my college 5 stars ”
posted on 2 months ago by SHREYAS V GALAG“ Greatest option RV college for doing engineering from here ”
posted on 8 months ago by Shafique HasaniInsight 1/2
College Reviews & Perception
RVCE Bangalore has received the lowest rating for value for money whereas Sahyadri College of Engineering and Management, Mangalore has comparatively better ratings across all aspects.
Insight 2/2
College Reviews & Perception
RVCE Bangalore has received the maximum positive reviews indicating strong placement support and active campus life.
Which college/course would you like to go ahead with?
Sahyadri College of Engineering and Management, Mangalore
BE Artificial Intelligence and Machine Learning
RVCE Bangalore : RV College of Engineering, Bangalore
BE Artificial Intelligence and Machine Learning
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