MASTER OF
SCIENCE
B
IG DATA ANALYTICS

Mission

M.Sc Big Data Analytics has been developed to create Post graduates who can become data scientists capable of working with the massive amounts of data now common to many businesses. It is aimed at people who want to move into this rapidly expanding and exciting area. The modules on this course help the learner to develop the core skills and expertise needed by the data scientist. The course can be split into three main areas, statistics, computing and management.

Program Educational Objectives

The intent of the M.Sc (Big Data Analytics) program is to produce Data Scientists who are able to achieve the following objectives:

  • Identify appropriate methods for data analysis in various domains
  • Apply relevant quantitative and qualitative analysis techniques.
  • Demonstrate primary data collection techniques
  • Access and process secondary data sources
  • Able to formulate and design data analytic solutions.
  • Interpret, communicate and apply findings
  • Evaluate data science regarding ethics, social responsibility and bias
  • Able to manage large-scale, complex data and obtain the interpretation.
  • Able to recognize and evaluate the opportunities, needs, and limitations of data.
  • Able to interpret data analytics and communicate the implications to stakeholders.
  • Attain data scientist and data engineer positions in a fast-growing field
  • Accelerate progress into related Research and Development in Data Science and Big Data

Student Outcomes

Students graduating from our Big Data Analytics Programme will be able to choose many different roles; you will develop specialist, advanced skills in data science methods and their applications. You will gain practical experience and a thorough theoretical understanding of the field, making you attractive to a wide range of employers or preparing you for further academic study. The learning outcomes of the degree are to foster:

  • To Analyze and interpret data using an ethically responsible approach.
  • Use appropriate models of analysis, assess the quality of input, derive insight from results, and investigate potential issues.
  • Design, implement, populate and query relational databases for operational data
  • Design, implement, populate and query data warehouses for informational data
  • Harness very large data sets to make business decisions
  • Apply computing theory, languages and algorithms, as well as mathematical and statistical models, and the principles of optimization to appropriately formulate and use data analyses.
  • Evaluate the use of data from acquisition through cleansing, warehousing, analytics, and visualization to the ultimate business decision
  • Discern when to implement relational versus document oriented database structures
  • Execute real-time analytical methods on streaming datasets to react quickly to customer needs
  • Interpret data findings effectively to any audience, orally, visually and in written formats.

M.Sc Big Data Analytics.. (Course for Data Scientist …)

The M.Sc. (Big Data Analytics) program is designed to provide students with a comprehensive foundation for applying statistical methods to solve real-world problems. One goal of this Big Data Analytics program is to prepare students for careers in Data Analytics with a broad knowledge of the application of statistical tools, techniques, and methods, as well as the ability to conduct in-depth analysis, synthesis, and evaluation. Another goal is to prepare students for careers with analytical database knowledge, the ability to apply analytical database tools, techniques, and methods, and the ability to design, develop, implement, program, and maintain data marts and data warehouses.

Data science & Big Data Analytics is the study of the computational principles, methods, and systems for extracting and structuring knowledge from data; and the application and use of those principles. Large data sets are now generated by almost every activity in science, society, and commerce – ranging from molecular biology to social media, from sustainable energy to health care. As a MSc Big Data Analytics student you will explore how to efficiently find patterns in these vast streams of data. Many research areas have tackled parts of this problem. Machine learning focuses on finding patterns and making predictions from data; ideas from algorithms and databases are required to build systems that scale to big data streams; and separate research areas have grown around different types of unstructured data such as text, images, sensor data, video, and speech.

M.Sc Big Data Analytics at St Aloysius College (Autonomous), Mangalore – Highlights

  • School of Information Technology is going to offer 2-Year M.Sc Big Data Analytics course from 2018 under the Autonomous Scheme.
  • M.Sc Big Data Analytics has an integrated curriculum that consists of a highly diverse set of Data Science, Statistics, IT courses, Big Data Technology Courses and interdisciplinary Big Data research projects, continuous interaction with industry and personality development courses.
  • The programme equips students with the skill and relevant competence to handle all practical problems faced by industry.
  • The aim of the M.Sc (Big Data Analytics) program is to produce leaders for the IT and Big Data industry and profession.
  • Continuous advances in technology have resulted in an explosion in the range and nature of computer applications, Data Science, Big Data Technology and applications of Big Data in various domains which today includes societal, scientific, industrial and financial applications.
  • The core subjects like Data Science, Big Data Analytics, Data Warehousing and Data Mining, Multivariate Data Analytics, Cloud and Big Data etc so that the students have a sound footing in the technical fundamentals.
  • It also prepares them for advanced study in areas of their interest. Courses like Business Intelligence and Data Mining, Big Data Analytics with Map Reduce and Hadoop, Soft Skills module to tap full potential of the students by improving time and self-management, communication skills, team spirit, confidence even and career building attitude.
  • The newly proposed syllabi is as per the guidelines of Mangalore University- Hard Core, Soft Core, Open Electives.. In the newly proposed scheme the Choice Based Credit System has been introduced to give better choices to the students in technology domains with a deep dive such as – Data Science, Business Analytics and Big Data Technologies.

Who Can Apply for M.Sc Big Data Analytics | Eligibility criteria

A candidate who has passed any recognized under graduate examination or equivalent examination with Mathematics or Statistics or Computer Science or Computer Applications or Computer Programming or Business Mathematics or Business Statistics as one of the optional subjects and obtained an aggregate minimum of 45% marks taken together in all the subjects in all the years of the Degree Examination is eligible for admission to the course. 40% of marks in Q. E. in case of SC, ST and Category-I of candidates.

Provided that in respect of candidate who has studied and passed one of the subjects specified above in Pre-University Course with 50% percent of marks in that subject shall also be considered for admission. 45% of marks in case of SC, ST and Category-I of candidate

Recognition & Core Values

Learning at AIMIT extends beyond the classroom. Throughout the program, classroom learning is complemented by hands-on experiences. You have a project work, industrial visits, technical rounds, seminars, competitions and a host of other activities that are designed to enhance your understanding of computer applications.,

  • M.Sc Big Data Analytics programme at AIMIT, St Aloysius College (Autonomous) is Recognized by the Mangalore University , UGC New Delhi
  • The School of Information Technology has introduced the Data Science and Big Data related courses back from 2010 at MCA and M.Sc Software Technology programmes
  • Well Qualified and Experienced faculty in Data Science and Big Data Technology, trained through the Industry-Academia Collaboration of the Dept and by the R&D
  • The programme starts with one month Refresher Course ”Foundations of Information Technology” designed by Infosys under the Campus Connect Initiative.
  • Several Industry Elective papers are being included in the syllabus from Infosys, IBM, EMC.
  • The School of Information Technology has been awarded with a Project to set up a Big Data Analytics Lab in Health Informatics by the Vision Group in Science & Technology (VGST) , Government of Karnataka .
  • The students have to undergo Business Consultancy projects at various Industries, which will help them to study the Data Patterns and arrive at Business Decisions.
  • The School of IT is keen in working very closely with several Research & Development Institutions for advanced research work in Big Data.
  • Encouraging the students to organize and deliver workshops, present and publish papers, work closely with the faculty at the Special Interest Group in Technology.
  • The School of IT is aiming at producing the effective Data Scientist and Big Data Analyst through this course, thus bridging the requirements gap at the Industries in Big Data.
  • We would like to look forward lot of Design Thinking and Entrepreneurship through this course..

School of Information Technology of AIMIT provides

  • International Standards in Course Structure in collaboration with Universities, Institutions and Companies from India and Abroad
  • World Class ambience for Information Technology & Bioinformatics Studies.
  • Wi-Fi Enabled Campus – Available 24×7 in the classrooms, campus and especially in the Hostels.
  • Well Equipped Labs with Servers and Nodes with Advanced Software installed.
  • Access to Latest e-Journals and e-Books through IEEE, ACM, Safari Books, 24×7 Books etc.
  • Spacious Library & Reading Rooms with Latest Editions of Books on all IT Subjects, Soft Skills, Leadership, Competitive Exams, Interview Preparation, CAT, MAT, GRE, GATE etc; Industry programme manuals
  • Advanced Syllabi under the Autonomous Stream; updated as per the Industry needs.
  • IT Industry Collaborated Elective Papers with Infosys, EMC, Microsoft, IBM, Vmware, Cisco & Oracle.
  • Excellent Placement Records with Leading Companies – IT / ITES / IT Product co.s / Banking / Supply Chain Mgmt / Media Processing / Content Management / Animation / Games Design co.s etc.
  • Internships in IT Companies – For Services, Product Development, Research Labs
  • Business Consultancy Project works to promote Design Thinking.
  • Infosys Campus Connect programme with Electives such as : Business Intelligence, Big Data Analytics, Internet of Things, FP 5.0 (Python Programming), Soft Skills
  • DELL-EMC Electives : Information Storage Management, Cloud Computing, Data Science And Big Data Analytics
  • IBM Software Center of Excellence for Add on Certification in Cloud Computing and Big Data Analytics
  • Collaboration with NASSCOM for NAC-TECH Examination which enables Employment in 1300 companies
  • Certification through MOOCS in various Technologies as a part of Self Study
  • Special Interest Groups of Faculty and Students to Enhance Research & Consultancy.
  • Free & Open Source Software (FOSS) – collaboration with CDAC-W3C
  • Computer Society of India, IEEE, IEEE Computer Scoiety – AIMIT Branch
  • Placement Training – Model Interviews, Analytics Labs, Analytics Schools.
  • Soft Skill Training in association with Infosys Leadership Development Institute
  • Leadership opportunity & Training in organizing various activities and Events in the Campus as well as Participation in Intercollegiate Fests.
  • International / National Level Seminars & Paper presentations / Publications to enable Research Oriented thinking
  • Webinars on Latest Technologies by IT Industries & Labs – Expert Interaction with the students.
  • Center for Creativity & Innovation & Incubation – to Promote Entrepreneurship.
  • National Level IT Fests (epITome) , IT Exhibition (Infovision), International Conference (SACAIM), Symposium (Anveeksha), Talent Hunt (Lakshya), Sports Day (Utkarasha), Defining Dialogues (Alumni Interaction)
  • Rural Immersion Programme to reach out the backward areas of Karnataka and getting experience under Student Social Responsibility Programme
  • Industry visits to different Locations and Interact with the Industry professionals

Admission Process

  • Admission to M.Sc Big Data Analytics programme for Karnataka / Non Karnataka candidates is made based on BIG DATA ANALYTICS COMPETENCY TEST (BDACT) conducted by St Aloysius College (Autonomous), Mangalore as per the norms of the Autonomous institute regulations .
  • The minimum percentage in eligibility examination for admission in M.Sc Big Data Analytics programme is 50% in case GM and 45% in case of SC / ST.
  • Ranking of the admission will be given based on 50% of the scores of Undergraduate Examination and remaining 50% of the Scores from BIG DATA ANALYTICS COMPETENCY TEST (BDACT)
  • In the event of a particular department receiving lesser number of applications than the number of seats available, the entrance test, where applicable, may not be conducted. (As per Mangalore University regulations)

Course Curriculum

Master of Science – Software Technology
Advanced Course for Software Professionals

Campus Connect – Foundations of IT

I Semester

FIT 1

Introduction to Computer Hardware

P 531.1

Advanced Data Structures and Analysis of Algorithms

FIT 2

System Software Concepts

P 532.1

Database Management Systems Engineering

FIT 3

Fundamentals of Programming

P 533.1

Object Oriented Programming with Advanced Java

FIT 4

Object Oriented Programming using C++

P 534.1

Web Programming with LAMP Technology

FIT 5

Introduction to Relational DBMS

P 535.1

Object Oriented Software Engineering with UML

FIT 6

Introduction to User Interface Design Concepts

P 536.1

Data Structures – AOA & Web Programming Lab

FIT 7

Project Work – Campus Connect Portal

P 537.1

DBMSE and Advanced Java Lab

FIT 8

Soft Skills

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Soft Skills

 

II Semester

III Semester

P 531.2

Enterprise Computing with Java EE Frameworks

P 531.3

Enterprise Cloud Computing

P 532.2

Mobile Computing and Application Development

P 532.3

SOA & Web Technologies and .NET Framework

Business Analytics Stream

Business Analytics Stream

P 533.2

Business Intelligence and Data Mining

P 533.3

Data Science and Social Media Analytics

P 534.2

Computational Intelligence & Machine Learning

P 534.3

Big Data Analytics with Map Reduce & Hadoop

Social Computing Stream

Social Computing Stream

P 533.2

Social Media Programming & Content Design

P 533.3

Ontology & Semantic Web

P 534.2

Internet of Things & Analytics

P 534.3

Augmented Reality Technologies

Open Elective Offered

Open Elective Offered

P 535.2

Enterprise Information System

P 535.3

Information Security & Assurance

P 536.2

Java EE and Mobile Computing Lab

P 536.3

Cloud Computing and .NET Lab

P 537.2

Business Analytics / Social Computing Lab

P 537.3

Business Analytics / Social Computing Lab

—-

Technical Writing & Paper Presentation

—-

Technical Writing & Paper Presentation

 

IV Semester

P 531.4

Project Work / Industry Internship / Research work at R& D Labs