Dear aspirants ,

MSDS is a professional course but if you are beginner in Data science then this course is not suitable for you because before join this course you should know about the basic things of programming ,data science ,python ,machine learning ,AI then this course will be good for you otherwise you feel difficulties during the course .But we are discusses briefly about this course ..

The AIM MSDS curriculum reflects the latest trends and best practices in the field  from data mining and exploration to machine learning, deep learning, big data analytics, and cloud computing.One of the strengths of the MSDS program is that it addresses a critical pain point of enterprises—the lack of technically-skilled individuals who possess the required level of communication, leadership, and management skills to help businesses and organizations make informed decisions. The program is designed to bridge this gap that plagues many organizations worldwide. At AIM, data scientists work closely with domain experts familiar with business and management issues. Students will, therefore, learn how to formulate the right questions and identify the correct datasets and ensemble of data-driven approaches to address highly diverse business and societal problems. More crucially, they will be taught how to properly communicate results and data-driven insights to maximize their impact on business and industry.  All MSDS students have access to a world-class computing facility housed at AIM, where they learn how to handle, manipulate, and analyze truly big datasets. The facility is part of the Institute’s Analytics, Computing, and Complex Systems (ACCeSs) lab run by world-class researcher scientists and engineers. ACCeSs at AIM is equipped with a 1.2-petaflops AI GPU powered Acer supercomputer. The advanced analytics lab is envisioned to bridge public-private R&D collaboration to develop real-world solutions that address business and societal issues. It is designed to become a center of excellence in data analytics, artificial intelligence, machine learning, and computational modelling.

Hope it will helpful

Thanks