Data Science is a dynamic interdisciplinary field unifying Statistics, Computer science, Mathematics, Data visualization and integration to solve problems covering a wide range of applications using knowledge extracted from noisy, structured and unstructured data, typically large. From capturing data to communicating results, data scientists play an important role in making high-level decisions in a variety of applications, including strategic business solutions for small, medium and large-scale companies.
As can be envisaged, high-level multiple skills create great demand for data scientists.
However, rigorous data science training is provided by perhaps only a handful of institutions, and St. Xavier's College (Autonomous), Kolkata, stands out in this respect. From the very inception of the two-year M.Sc. in Data Science course in 2022, the faculty members of the Department of Statistics and the Department of Computer Science, are committed towards providing a wholesome data science training to highly motivated students, admitted through rigorous examination and subsequent interview. This is one of the very few courses in India to offer rigorous training in nuances of Statistics and Probability, Machine Learning, Mathematics, Computer Science, sophisticated programming, software training for data science and Big Data Analytics.
This course not only includes data mining, programming skills and analysing sets of data but goes beyond to look at the entire data science life cycle. This course is designed to develop an in depth understanding of the key concepts and technologies in data science, machine learning, visualization techniques, predictive modelling, and statistics. The students are expected to gain holistic knowledge about various computational platforms available for big data analytics.
Integrating the fields of Statistics, Computer Science and Optimization Techniques, this course intends to create adept and well-versed data scientists by exposing the students to real-world problems in the classroom and through experiential learning.