ME793 - Multiscale Materials Informatics, Discovery and Design

ME793 - Multiscale Materials Informatics, Discovery and Design

Instructor

Prof Alankar Alankar

Semester

Spring ‘20

Course Difficulty

Very chill

Time Commitment Required

Moderate

Grading Policy and Statistics

Relative Grading. AA-5, AB-2, BB-2

Attendance Policy

None

Pre-requisites

None

Evaluation Scheme

Relative grading 60% Assignments and a 40% Final project

Topics Covered in the Course

The course is focused on providing essential tools to perform data analysis for on material science through statistics, machine learning, and deep learning in python from scratch to finish.

Teaching Style

Lectures are a combination of hands on approach and in depth theoretical studies. The instructor weekly gives either assignment or tutorial to ensure that each topic is thorough. A project with the aim of solving a hard task in the domain of material science through machine learning is also done in the latter half of the course.

Tutorials/Assignments/Projects

Tutorials and assignments are the key to understanding and scoring a good grade in this course.

Motivation for taking this course

It’s a great course for people interested in material science who want to step into domain of machine learning.

How strongly would I recommend this course?

Highly

ME 793 Review By: Kanishka Sunick