M Tech in Data Science
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M. Tech. in in Data Science - REVA University
M. Tech. in Data Science

M. Tech. in Data Science

Course Overview

NIST Big Data Working Group defines data science as, “Data Science is the empirical synthesis of actionable knowledge from raw data through the complete data lifecycle process”.

Data science is collecting, manipulating, and analyzing of data in order to extracting value from it and also predicting the future. This task is done by a Data Scientist. Data Scientists analyze high volumes of data, question assumptions, discover patterns in the data, develop insights, construct narratives, and provide solutions that make sense.

Data science combines several disciplines, including statistics, data analysis, machine learning, and computer science. Data Science has applications in Computer vision, Text mining, NLP, Biomedical signal processing, robotics, Autonomous vehicles, Precision agriculture, business intelligence and so on. Data Science is considered as fourth paradigm of learning after empirical, theoretical, and computational.

A Data Scientist needs to be an expert in Computer science and software programming, written and verbal communication, probability and statistics and business domain. Since computer systems and storage capacity have turned out to be increasingly affordable over time, numerous solutions now utilize various computer systems which are cooperating together that are not very exorbitant to scale, rather than scaling solutions by acquiring a solitary super powerful and extremely costly computing machine.

The School of Computing and Information Technology at REVA UNIVERSITY offers M. Tech., in Data Science–a postgraduate programme to create motivated, innovative, creative and thinking graduates to fill the roles of Data Scientists who can conceptualize, design, analyze and develop computer software to process and analyse big data.

In Master of Data Science program, you learn to explore data using high-level mathematics, statistics, and computer science. In particular, you learn how to analyze data, visualize your results, and articulate your discoveries. You will leave the program with the ability to think about the real problems that need to be solved, not to simply find technical solutions.

The M Tech programme in Data Science program covers specialized areas in the field of IT industry and research. The program focuses on technologies managing huge traditional and non-traditional data including temporal, spatial and multi-dimensional data. It also focuses on cloud computing concepts that feature subjects as well as projects that typically involve construction and experimentation with software prototypes.

Programme Educational Objectives (PEOs)

The aim of the programme is to produce postgraduates with advanced knowledge and understanding of Data Engineering and Cloud Computing; higher order critical, analytical, problem solving and transferable skills; ability to think rigorously and independently to meet higher level expectations of ICT industry, academics, research establishments or take up entrepreneurial route.

The Programme Educational Objectives are to prepare the students to:

  • Be data scientists who can write programmes to process data for further analysis and use cloud computing technology
  • Pursue for higher degrees to work in colleges, universities as professors or as scientists in research establishments
  • Act as administrators in public, private and government organizations with further training
  • Be conversant with environmental, legal, cultural, social, ethical, public safety issues
  • Work as a member of a team as well as lead a team
  • Communicate effectively across team members and work under constraints
  • Set his/her own enterprise with further training
  • Adopt lifelong learning philosophy for continuous improvement

Programme Outcomes (POs)

After undergoing this programme, a student will be able to:

  • Build, approve, and test models, for example, recommendations, predictive models.
  • Wrangling, parsing, munging, transforming and cleaning data
  • Mining and analyzing the data, for example, summary statistics, Exploratory Data Analysis (EDA),Gaining data
  • Tuning and enhancing models or deliverables
  • Use technologies like distributed computing, cloud computing and other upcoming technologies
  • Lead a team to ensure that projects are completed satisfactorily, on time, and within budget
  • Conform to cultural, environmental, sustainability and ethical issues
  • Communicate across teams verbally, visually and by writing and manage the systems
  • Choose appropriate online educational programmes for further learning, participate in seminars and conferences

Course Curriculum

First Year

Semester I

Sr. No.

First Semester

1

Advanced DBMS

2

Machine learning

3

Data Science using R

4

Probability and Statistics 

5

Soft Core 1 (SC-1) : (Click here)

6

Soft Core 2 (SC-2) : (Click here)

7

ADBMS LAB

8

Data Science Using R Lab

Semester II

Sr. No

Course Title

1

Cloud Security

2

Big data & Analytics  

3

Business Intelligence

4

Soft Core 3 (SC-3) : (Click here)

5

Soft Core 4 (SC-4) : (Click here)

6

Soft Core 5 (SC-5) : (Click here)

7

Big data &  Analytics Lab

8

Cloud Lab

Second Year

Semester III
Sr. No Course Title
1 Soft Core 6 (SC-6) : (Click here)
2 Open Elective
3 Project Phase-1
4 Internship
5 Global Certification
6 MOOC
7 Sports ,Yoga, Music, Dance, Theatre
Semester IV
Sr. No Course Title
1 Project Phase -2 and Dissertation


Note:
1. Internship should be carried out in a reputed /Tier-1/R & D organization, preferably, internship should be with stipend. The internship should be approved by the REVA University authorities before completion of 3rd semester and the students should obtain the permission for the same by producing the necessary details of company, selection process, and the offer letter issued by the company. At the end of the Internship, detailed report must be submitted.

2. Students can take-up the internship only if it is approved by RU authorities.

3. Project work phase 1 comprises of literature survey, review paper writing, problem formulation, identification of tools and techniques, and methodology for the project. Project work phase – 2, in 4th semester should have an outcome: publication in a reputed National/International Journal or a patent filing to earn 2 credits.

4. Global Certification programs: Students have to register for global certification programs of their choice such as networking, JAVA, ORACLE, etc. The students can also choose skill development programs conducted by the UIIC or School, which may not be globally certified. However, weightage is more for global certification courses (10% weight age is accounted less for non-global programs).The registration must happen before beginning of the third semester.

Career Opportunities

The students completing M Tech in Data Science will have plenty of career opportunities in several institutions, organizations and multinational companies. This broader area includes:

  • Data Scientist
  • Data Architect
  • Data Administrator
  • Data Analyst
  • Business Analyst
  • Data/Analytics Manager
  • Business Intelligence Manager

Eligibility

  • B E / B Tech in ECE / CSE / ISE / TE / MCA / M Sc in Computer Science or Mathematics or Information Science or Information Technology with a minimum of 50% (45% in case of SC/ST) marks in aggregate of any recognized University / Institution or AMIE or any other qualification recognized as equivalent there to.

Course Duration: 4 Semesters (2 Years)

Important Dates

Application Round Opening Date of Application Closing Date of Application
Application Round 21st April 2019 30th April 2019

Admissions

ADMISSION OPEN

How to Apply?

Contact for Admissions
Office of Admissions,
REVA University, Rukmini Knowledge Park Kattigenahalli, Yelahanka,
Bangalore – 560 064
Karnataka, India
+91 95388 74444
admissions@reva.edu.in
Application Fee
Course Application Fee
Indian / SAARC Nationals
(Rs.)
NRI Fee
(Rs.)
Foreign Nationals
($)
M. Tech. in Data Science 1000 2000 50
Hostel Fee
Transportation Fee
Transportation Route