Programme OverviewDuration: 2 Years| Programme Code: 020320
M.Tech Data Science programme aims to develop computational and statistical skills for data-driven multi-disciplinary problems. Data science integrates statistics and data mining techniques to develop methods to collect, process and extract meaningful information from large and diverse data sets. The M. Tech in Data science curriculum will prepare student in areas such as Machine Learning, Deep Learning, Data Mining, Predictive Analytics, large-scale data analytics and Big Data. The usefulness of this course is in every industry, government organization, and Internet start-ups to financial institutions to handle big data projects at every level.
Programme Educational Objectives
- To apply statistical data analysis and other decision science techniques to effectively solve real-world problems.
- Develop appropriate algorithms using machine learning techniques to solve problems.
- Effectively communicate the results of the analysis using appropriate data visualization techniques
Programme OutcomesUpon completion of the Data Science programme, students will be able to:
- acquire in-depth knowledge of concepts of statistics and machine learning to discriminate, evaluate, analyze and synthesize existing and new knowledge and to integrate the same for enhancement of knowledge with a global perspective.
- able to apply the knowledge of computing tools and techniques in the field of Big Data for solving real world problems encountered in the Software Industries.
- understand the impact of computing and engineering solutions in a global, economic, environmental and societal context.
- understand the professional and ethical responsibilities in engineering practice.
- demonstrate knowledge of contemporary issues in the area statisticsa and machine learning.
- demonstrate the knowledge and understanding of engineering and management principles in the area of Computer Science and Engineering to manage projects in multidisciplinary environment.
Distinctive academic curriculum, qualified and competent faculty members, inter-disciplinary project based learning, state-of-the-art laboratories, exceptional computing facilities, industry interaction and internships, semester abroad opportunities.
Some of the major areas that will be covered
Statical programming, Applied machine learning, probablistic graphical models, scaling to big data, Deep learning, Bayesian data analysis, Social and web analytics, parallel and distributed systems, managing cloud, Security in Cloud.
This programme is designed with equal emphasis on both theoretical and practical aspects of building an intelligent system. Opportunities exist in the area of Machine Learning, Natural language understanding.
An undergraduate degree in an appropriate discipline from UGC approved University. In addition, applicants will also have to successfully complete Goenka Aptitude Test for Admission (GATA) and appear for personal interview