M. Tech. in Data Science

Academics

This program is designed to enable learners to master critical skills such as mathematical modeling, machine learning and artificial intelligence. On the whole, the Master’s Program is committed to produce engineers with excellent creative capabilities and caliber to solve real life problems pertaining to industry requirements and advance their career as a Data Scientist or Data Engineer, in tune with the objectives envisioned by Amrita Vishwa Vidyapeetham.

Program Highlights

1. The curriculum covers areas that prepare you for most lucrative careers in the space of Data Science, Data Engineering and Advanced Analytics. The programme provides extensive knowledge on most popular data science techniques such as mathematical modeling, machine learning, artificial intelligence, product development and scripting languages.
2. Benefit from Case Studies, Simulations, Virtual Labs & Remote Labs that allow learners to apply concepts to simulated and real-world situations. Tools & Technologies covered include Apache Spark, Apache Storm for Big Data Systems/ Real time Processing, Tableau for data visualization, Tensor flow for Deep Learning and various packages within Python for data processing, machine learning and data visualization.
3. The programme offers core courses such as Data Structures and Algorithms, Foundation of Data Science, Big Data Mining, Computational Intelligence, Data Preparation and Analysis, Statistical Learning, Machine Learning, Deep Learning and Time Series Analysis and Forecasting. Industry experts in each stream will be invited to give sessions on practical implications of classroom learned concepts in business use cases.
4. Integrated Industry approach for problem solving in the curriculum and the delivery of the course content.
5. The Dissertation enables students to apply concepts and techniques learnt during the programme.

Program Outcomes

Students who have completed the M.Tech in Data Science Program will be able to:

• Develop in depth understanding of the key technologies in data science and business analytics such as structured/unstructured data mining, machine learning, visualization techniques, predictive modeling, and statistics.
• Practice problem analysis and decision-making.
• Interpret data, extract meaningful information, and assess findings.
• Effectively communicate data science-related information effectively in various formats to appropriate audiences.
• Apply quantitative modeling and data analysis techniques to transform findings from data resources into actionable business strategies.
• Gain practical, hands-on experience with statistics programming languages and big data tools through coursework and applied research experiences.
• Develop an ability to contribute by research and innovation to solve engineering problems.

Program Curriculum

Participants need to take certain number of Courses, Minor Project and Dissertation. The coursework requirement for the program would consist of a set of core courses and electives. Core courses are compulsory for all participants, while electives can be chosen based on individual learning preferences.

How to Pursue Research Path after Completing this Program ?

Research is an integral part of the Data Science and numerous research opportunities and career progression are available for which the program will serve the foundation. They can engage in research across a wide range of data science areas, combining theoretical work with an application focus on areas like health care domain, social media mining, cyber and business analytics. 

Advantages in Terms of Placements

Data Science Career Opportunities

A Data Scientist, according to Harvard Business Review, “is a high-ranking professional with the training and curiosity to make discoveries in the world of Big Data”. Therefore it comes as no surprise that Data Scientists are coveted professionals in the Big Data Analytics and IT industry. Demand for data scientists is booming .Fueled by big data and AI, demand for data science skills is growing exponentially. Coding skills in R/Python/Java clubbed with knowledge of statistics and applied mathematics, working knowledge of Hadoop , Spark,SQL, NoSQL, machine learning and neural networks, text processing, text analytics, proficiency in deep learning frameworks such as TensorFlow, Keras, Pytorch will fetch big career opportunities in Data Science.