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ABOUT THE COURSE:
Why Deep Learning in MSE? Deep Learning has widely been used in various sectors; health care, finance, agriculture, education, energy, entertainment etc have been using Deep Learning to improve their performances. Tech giants have been pushing their boundaries to achieve more as Deep Learning is the driving force everywhere and similarly the demand for skilled professional has steeply been rising. The design and discovery of new materials, processing optimization and prediction of properties would require applications of Deep Learning techniques and even deployment of the same. The present course is meant for students preparing for higher studies, researchers applying AI tools, the industry professionals wanting to upskill. This is a balanced course with conceptual learning and hands-on with ability to build intuition, apply concepts to data, and interpret model output. Upon successfully completing this course, you will have a mini portfolio of Deep Learning projects, which can be showcased to the potential employers or use for research.
INTENDED AUDIENCE: Materials, Mechanical, Physics, Chemistry
PREREQUISITES: Knowledge of Artificial Intelligence and Machine Learning
Why Deep Learning in MSE? Deep Learning has widely been used in various sectors; health care, finance, agriculture, education, energy, entertainment etc have been using Deep Learning to improve their performances. Tech giants have been pushing their boundaries to achieve more as Deep Learning is the driving force everywhere and similarly the demand for skilled professional has steeply been rising. The design and discovery of new materials, processing optimization and prediction of properties would require applications of Deep Learning techniques and even deployment of the same. The present course is meant for students preparing for higher studies, researchers applying AI tools, the industry professionals wanting to upskill. This is a balanced course with conceptual learning and hands-on with ability to build intuition, apply concepts to data, and interpret model output. Upon successfully completing this course, you will have a mini portfolio of Deep Learning projects, which can be showcased to the potential employers or use for research.
INTENDED AUDIENCE: Materials, Mechanical, Physics, Chemistry
PREREQUISITES: Knowledge of Artificial Intelligence and Machine Learning
