MTech in Data Science

MTech in Data Science at MIT, Manipal is a two-year postgraduate degree program taught by MIT and industry experts. The program is designed to train graduates to pursue a career in the area of data science. Data Science is a unique multidisciplinary confluence of Computer Science, Computational Mathematics, Statistics, and Management. Data technologies for data collection, data storage, retrieval, and computation will be taught during the course.  The core data science subjects focus on data analysis, visualization, predictive modelling, and analytics for data-driven decision-making.  Knowledge representation, machine learning, artificial intelligence, deep learning will be taught with relevant case studies.  

Program Educational Objectives (PEOs)

MTech. in Data Science graduate will be able to:

PEO-1:   Understand the challenges in data representation and computation in the domain of Data Science, Computational Mathematics, Statistics, and Management

PEO-2:   Acquire technical skills to perform data analysis and visualization for decision making in various domains.

PEO-3:   Apply statistical and computational methods to prepare data and perform predictive analytics.

PEO-4:   Contribute to multidisciplinary research and development by using innovative and creative methods.

PEO-5:   Pursue higher studies and obtain positions as data scientists or data analysts

Program Outcomes (POs)

The Program Outcomes of MTech in Data Science enable students to:

PO-1:       Apply analytics and statistical principles for data analysis and visualization.

PO-2:       Understand the importance of image data and learning methods to process the data

PO-3:       Design creative and innovative perspective of the data in the domain of market analysis and forecast analytics

PO-4:       Develop the ability to build and assess data-based models

PO-5:       Develop high-level applications for data management using advanced technologies and programming languages, such as artificial intelligence, machine learning, and deep learning

PO-6:       Demonstrate the ability to understand and analyze data associated with various applications, such as finances, business, and healthcare

PO-7:       Contribute to reputable journals and conferences by publishing interdisciplinary   research articles through team work

PO-8:       Contribute to research and innovation in order to be an entrepreneur

Career Prospects

Data analysts and scientists are in high demand since the last few years and the demand is unlikely to slow down any time soon. The Institution’s placement cell, industry collaborators, and alumni network will facilitate placement and internships as data scientists, data analysts, and data engineers. The course targets placements and internships in top data science companies, research organizations, and in domains such as finance, business, economics, and healthcare.

The course will equip students to target the following profiles:

·         Data Analyst

·         Business Analyst

·         Data Engineer

·         Machine Learning Engineer

·         Data Scientist

Click here to download the Course Structure