M.Tech programs in data Science | RV University

M.Tech. Data Science

M.Tech. Data Science for working professionals

Programme Overview

Data Science is a field that gives valuable insights from unstructured data points, using various scientific methods and algorithms. It is interdisciplinary and combines the fields of mathematics, statistics, artificial intelligence, computer science and different domains and helps in creation of forecasts, and data-driven decisions. In our programme, students learn from expert faculty and industry professionals, in collaboration with upGrad Campus, and solve real-world problems in their domains, via capstone projects, case studies or thesis work. They also receive extensive career support and placement assistance to start and accelerate their career.

Modular Masters Certifications

During the course of the degree programme, the following Modular Masters certifications will be awarded by upGrad Campus

  • Programming for Data Science
  • Data Analysis
  • Machine Learning
  • Deep Learning
  • Specializations, if any

Should a student pause the degree programme, accumulated course credits will be accounted for in the Academic Bank of Credits that they can use later towards their M.Tech. Data Science degree, as per the New Education Policy (NEP) and the following certifications will be awarded

  • Certificate in Data Analysis
    • After successful completion of the first year
  • Advanced Post Graduate Diploma in Data Analysis and Machine Learning
    • After successful completion of the first two years

Specialisation

M.Tech. Data Science offers electives for specialisation in

  • Artificial Intelligence

  • Networks, IoT and Cyber Security

  • Business Analytics

  • Computational Aerospace, Computational Mechanical

  • Computational Science

Programme Structure and Course Details

For details on the program structure, curriculum and course syllabus, download the program brochure available here Download

Why at RV University?

  • Focus on equipping domain experts with the most relevant and sought-after computing and data analytics skills

  • Joint-degree with upGrad Campus, with 100% placement assistance

  • Support for developing an appealing portfolio and assistance through a Placement Preparation Module comprising Resume Building, LinkedIn Profile Builder, Mock interviews, Career Guidance and access to Exclusive Job Portal by upGrad.

  • Learn through live-projects, capstone projects that simulate actual projects in top companies across industry and case studies.

  • Live Sessions with dedicated industry experts working in various companies and personalized guidance by upGrad Campus mentors.

  • Recruitment partnership with over 1000 top companies

  • Advisory Board with eminent academicians, industry leaders and entrepreneurs to drive the vision of the programme

  • Locational advantage of Bengaluru which is regarded as the Silicon Valley of India and it is considered as one of the ‘Next Decade’s Fastest — Growing Cities’ by Forbes Magazine

Eligibility & Selection Criteria

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Eligibility

The institute seeks diversity of background and interests, from a wide range of corporations, public institutions and other professional fields. A candidate seeking admission into M.Tech. Data Science programme must have:

– 4-year bachelor’s degree/ MCA/ M.Sc./ B.Sc. (Research) in Core Engineering or allied subjects duly recognized by UGC/ AIU, with minimum aggregate marks of 50% for General, 47% for NC-OBC, and 45% for SC/ST/DAP or

– AIME or equivalent degree approved by statutory bodies

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Selection Criteria

Based on final merit list which would consider

– Performance of the candidate in the personal interview.

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Important Dates of RVU Selection Process

March 31st, 2021

How to apply/Admission process:

1.

RVU Selection Process

Depends on the course applied

2.

Selection letter issued

Subjected to fulfilment of eligibility and admission criteria

3.

Programme Registration

On receipt of registration fee as specified in the selection letter

4.

Provisional Admission Letter

Issued upon completion of the selection procedure

M.Tech. Data Science Admission process and fee details

Admission process and fee payment need to be completed on campus.

DOCUMENTS TO BE SUBMITTED AT THE TIME OF ADMISSION.

  • Originals of 10th and 12th Marks Cards
  • Original Degree Certificate(s)
  • Sponsorship letter from the employer, if sponsored by the employer
  • If a seat is claimed under category, then they must submit relevant category /Income/ Rural/ Kannada Medium/ Hyderabad Karnataka/ Sports/ NCC/ Defense / J&K resident certificate, others.
  • Photocopy of student Aadhar card
  • Photocopy of PAN card
  • 3 sets of photocopy copies of the documents related to SL NO 1, 2, 3, 4, 5, 6, 7.
  • Submit 5 Recent color Passport-sized photographs & 2 Stamp-sized photographs.
  • Other document(s) as applicable

Details of Fee Structure for the programme are as follows:

  • Rs. 1,32,000 per year

Contact Admissions regarding early bird offers, corporate enrollment waivers, financial aid and merit scholarships.

Career Options

Data scientist jobs have been the most demanding jobs of the 21st century due to the explosion in the data available globally. The International Data Corporation (IDC) predicts that by 2030, global data will grow to 175 zettabytes, which means we will continue to be in dire need of quality Data Science professionals in the next 10 years.

  • Data Analyst
  • Data Scientist
  • Data Architect
  • Data Engineer
  • Data Science Consultant
  • Database Administrator
  • Machine Learning Engineer
  • AI Engineer

How To Reach RV University

  • Metro connectivity: Pattanagere station on the purple line. Exit towards the RV College of Engineering side
  • Any BMTC buses travelling towards Kengeri/ Bidadi: Alight at RVU
  • Distance to our campus from Bangalore Railway Station/ KempeGowda Bus Stand/ K R Market is nearly 13 KMs.
  • Located at about 3 KMs from Bangalore University Gate/ Raja Rajeshwari Nagar Arch.
  • Distance to our campus from Kengeri Railway Station is nearly 4 kms.

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