M.Sc. (Data Science)

Program Overview | Program Objective | Program Structure | Admission Process

Program Overview

Data science is a “concept to unify statistics, data analysis, machine learning and their related methods” in order to “understand and analyze actual phenomena” with data. In other words, the detailed study of the flow of information from structured and unstructured data available with an organization is called data science. It primarily involves obtaining the meaningful insights from the data which is processed through analytical study. The current era is becoming a digital space where each organization deals with large amount of structured and unstructured data on a daily basis. Evolving technologies are leading to cost saving solutions for storage and analysis of such large data. In the current era, for the career progression, one needs to understand the language of data through analytical skill. Hence, it is absolutely necessary nowadays, to develop manpower with a skill to perform data analysis to get meaningful information from the data of different domains such as banking and finance, insurance, agriculture, healthcare, retail, education, social media, manufacturing, transportation, entertainment and so on. As reported recently, with nearly 100,000 vacancies, India is the second biggest data analytics jobs hub after the US and demand for data science skill sets is increasing at a very fast pace.

The field of data science has witnessed an immense growth in recent years particularly due to the rise of internet and social media. The exploration of data science by the business world initially started with analysis of business data and hence emphasis was given for financial data analytics. With the increase of multimedia data such as image, video, audio and text, each domain as mentioned above, many a times needs to perform analysis of such multimedia big data. Hence the study of data science includes analysis of multimedia data along with other types of data such as business data and unstructured social media data. In our daily life, now we are capturing data from sources such as i) sensors used in various places like agricultural fields, shopping malls, ii) posts on social media, iii) digital images and videos captured in cell phones and iv) purchase transactions made through e-commerce.  Analysis of such big data which could be multimodal in nature is a huge challenge. Modern technologies in the areas of artificial intelligence (AI) and machine learning (ML) are now extensively used to get insights of such big data.

With the availability of modern technologies of data storage, cleaning and computing, the study of data science expanded beyond the boundaries of mathematics and statistics. In modern days the study of data science is constituted with the knowledge of mathematics, statistics and computer science. Data science brings together a lot of skills of these disciplines with adequate domain knowledge to help any organization find ways to i) take major business decisions, ii) reduce costs, iii) get in to new markets, iv) launch a new product or service, v) find the sentiment of the customers, vi) recruiting the best talent and so on.

With all these in mind, our new master’s program in Data Science starting July 2020, will not only include traditional data analysis skills but also incorporates other crucial skills to perform multimedia and big data analysis. The courses will focus on acquiring fundamental knowledge of mathematics, statistics and computer science. The curriculum will also include domain specific knowledge by incorporating courses in multimedia, business and finance. Techniques such as data processing, database management, machine learning along with tools such as Python, R and SAS are also included to enhance the technical and analytical skills. SAS based training to be imparted during the program encompasses building basic skills in analytical programming, advanced skills in data integration, machine learning, deep learning, artificial intelligence and big data visualization. SAS has variety of tools and applications that are part of the curriculum which enables students with industry ready skills. The SAS based courses are offered in mini project, outcome-oriented workshop mode to make the students hands-on with the challenges of data science. MSc. in Data Science program has been designed to provide students with a strong foundation in data management and analysis, and the necessary skills to succeed in data-analytics related job.

Degree Name: MSc. in Data Science

Duration: 2 Years (Four Semesters)

Characterization of the Program: Intersection of Mathematics, Statistics, Programming, Big-Data and Machine Learning

Uniqueness of the Program: Hands on and case study based program

The program primarily aims to cater to the following audience:

    1. Traditional Science/ Economics/ Engineering Graduates with good mathematical aptitude, basic programming skills and inclination towards data science.
    2. Professionals in the workplace who wish to improve their skills for the emerging jobs in data-science related fields

Program Objective

The primary objective of the M.Sc. in Data Science program is to develop skilled professional workforce that is prepared to address the increasing needs in the rapidly expanding area of big data analytics. The program aims to provide skills in quantitative data analysis, data mining, data modeling and prediction, data storage and management, big data processing, data visualization, multimedia big data, programming and communication skills. SAS based courses/ training and a large number of practical case studies have been integrated in the program to boost the learner confidence and market acceptability. The program also enables the students to obtain SAS global certification in many fields and the skills can be ratified and showcased through SAS international certification badges.

Program Structure

AUTUMN SEMESTER (SEMESTER 1) 

Course Name

Credits (L-T-P-C)

Mathematical Foundation for Data Science

4 Credits (3-1-0-4)

Data Structures and Algorithms (Lab:Python)

4 Credits (3-0-2-4)

Statistical Methods (Lab:R)

4 Credits (3-0-2-4)

Programming Lab

  • Introduction to Python and R
  • PROGRAMMING FOR DATA SCIENCE IN SAS -ESSENTIALS & MANIPULATION TECHNIQUES
 

2 Credits (0-0-4-2)

Introduction to Database Management

4 Credits (3-0-2-4)

WINTER BREAK 

MACRO & SQL PROGRAMMING FOR DATA SCIENCE IN SAS

 INTRODUCTION TO SAS AND HADOOP

SAS Certification Exam – I

(SAS Certified Specialist: Base Programming Using SAS 9.4)

 

48 hours (2 weeks)

 

 WINTER SEMESTER (SEMESTER 2) 

Machine Learning

4 Credits (3-0-2-4)

Numerical Methods for Data Science

4 Credits (3-0-2-4)

Big-Data Processing

3 Credits (2-0-2-3)

SAS based Mini Project -1

  • DATA INTEGRATION FOR MANAGERS

2 Credits (0-0-4-2)

Optimization

3 Credits (2-0-2-3)

Technical Elective1

4 Credits (3-0-2-4)

SUMMER BREAK 

BIG DATA VISUALIZATION – ESSENTIALS AND ADVANCED

STATISTICAL INFERENCE AND MODELING USING SAS

APPLIED MACHINE LEARNING USING SAS

SAS Certification Exam – II

( SAS Certified Data Integration Developer for SAS 9)

SAS Certification Exam – III

( SAS Certified Specialist: Machine Learning Using SAS VIYA 3.4)

72 Hours (2-3 weeks)

AUTUMN SEMESTER (SEMESTER 3) 

Course Name

Credits (L-T-P-C)

Deep Learning

4 Credits (3-0-2-4)

Interactive Data Visualization

4 Credits (3-0-2-4)

Open Elective1

3 Credits (3-0-0-3)

Technical Elective2

3/ 4 Credits

SAS Based Mini Project 2

  • NEURAL NETWORK ESSENTIALS
  • DEEP LEARNING USING SAS
  • VISUAL TEXT ANALYTICS USING SAS

Domain Specific Mini Project

2 Credits (0-0-4-2)

 

 

2 Credits (0-0-4-2)

 WINTER BREAK 

VISUAL FORECASTING USING SAS

OPTIMIZATION CONCEPTS FOR DATA SCIENCE AND ARTIFICAL INTELLIGENCE

SAS Certification Exam – IV

(SAS Certified Specialist: Natural Language Processing and Computer Vision Using SAS VIYA 3.4)

SAS Certification Exam – V

(SAS Certified Specialist: Forecasting and Optimization Using SAS VIYA 3.4)

 

32 hours (1 week)

 

WINTER SEMESTER (Semester 4):

On-Campus Projects / Industry Internships

List of Technical Electives 

• Image Processing • Information Retrieval
• Speech Processing • Social Media Analytics
• Computer Vision • Cloud Security
• Natural Language Processing • Cloud Computing
• Financial/ Business Data Analysis • Data Warehousing and Data Mining

After successfully completing the SAS global exams (III-V) mentioned above, a student will be awarded the following certification:

SAS Certified Professional : AI & Machine Learning

More details regarding the SAS certifications can be found here: 

https://www.sas.com/en_in/certification.html 

Admission Process

Details on the application process, admission criteria, fee structure and financial assistance can be found here