Materials Data Sciences and Informatics (Coursera)

Materials Data Sciences and Informatics (Coursera)

This course aims to provide a succinct overview of the emerging discipline of Materials Informatics at the intersection of materials science, computational science, and information science. Attention is drawn to specific opportunities afforded by this new field in accelerating materials development and deployment efforts.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

A particular emphasis is placed on materials exhibiting hierarchical internal structures spanning multiple length/structure scales and the impediments involved in establishing invertible process-structure-property (PSP) linkages for these materials. More specifically, it is argued that modern data sciences (including advanced statistics, dimensionality reduction, and formulation of metamodels) and innovative cyberinfrastructure tools (including integration platforms, databases, and customized tools for enhancement of collaborations among cross-disciplinary team members) are likely to play a critical and pivotal role in addressing the above challenges.

Syllabus

WEEK 1
Welcome
What you should know before you start the course
Accelerating Materials Development and Deployment
• Learn and appreciate historical paradigms of advanced materials development while emphasizing the critical need for new approaches that employ data sciences and informatics as the glue to connect computational simulation and experiments to speed up the processes of materials discovery and development.
• Learn about the emergence of key national and international 21st century initiatives in accelerated materials discovery and development and how they are expected to bring about a disruptive transformation of new product capabilities and time to market.

WEEK 2
Materials Knowledge and Materials Data Science
• Understand property, structure and process spaces
• Learn about Process-Structure-Property Linkages • Learn what does Materials Knowledge mean • Learn about a role of Data Science in Materials Knowledge System • Overview approaches and main components of Data Science • Learn about a new discipline - Materials Data Sciences

WEEK 3
Materials Knowledge Improvement Cycles
• Learn material structure and its digital representation
• Learn how to calculate 2-point statistics • Learn how Principal Component Analysis can be used to reduce dimensionality • Understand Homogenization and Localization concepts

WEEK 4
Case Study in Homogenization: Plastic Properties of Two-Phase Composites
This module demonstrates a homogenization problem based on an example of two-phase composites

WEEK 5
Materials Innovation Cyberinfrastructure and Integrated Workflows
• Learn about materials innovation system and cyberinfrastructure
• Review Materials Databases, e-collaboration platforms and code repositories • Learn why integrated workflows are needed • Define Metadata, Structured and Unstructured data • Learn about available services for e-collaborations

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Data Science in Health Technology Assessment (Coursera) Coursera
Genentech

Data Science in Health Technology Assessment (Coursera)

This course explores key concepts and methods in Health Economics and Health Technology Assessment (HTA) and is intended for learners who have a foundation in data science, clinical science, regulatory and are new to this field and would like to understand basic principles used by payers for their reimbursement decisions.

Aug 17th 2026
3 Weeks
Introduction to Genomic Technologies (Coursera) Coursera
Johns Hopkins University

Introduction to Genomic Technologies (Coursera)

This course introduces you to the basic biology of modern genomics and the experimental tools that we use to measure it. We'll introduce the Central Dogma of Molecular Biology and cover how next-generation sequencing can be used to measure DNA, RNA, and epigenetic patterns. You'll also get an introduction to the key concepts in computing and data science that you'll need to understand how data from next-generation sequencing experiments are generated and analyzed.

Aug 17th 2026
4 Weeks
Iniciándome en la Química (Coursera) Coursera
Universidad Autónoma Metropolitana

Iniciándome en la Química (Coursera)

En este curso aprenderás los conocimientos básicos de química general que te permitirán tener una mejor comprensión del estudio de la química, así como de la naturaleza. A lo largo del curso aprenderás la clasificación de la materia y sus propiedades, las teorías atómicas, la clasificación periódica, los tipos de enlaces y nomenclatura inorgánica.

Aug 17th 2026
4 Weeks
Machine Learning Introduction for Everyone (Coursera) Coursera
IBM

Machine Learning Introduction for Everyone (Coursera)

This three-module course introduces machine learning and data science for everyone with a foundational understanding of machine learning models. You’ll learn about the history of machine learning, applications of machine learning, the machine learning model lifecycle, and tools for machine learning. You’ll also learn about supervised versus unsupervised learning, classification, regression, evaluating machine learning models, and more.

Aug 17th 2026
3 Weeks
Population Health: Fundamentals of Population Health Management (Coursera) Coursera
Leiden University

Population Health: Fundamentals of Population Health Management (Coursera)

What are the principles of Population Health Management as a pro-active management approach to improve health and to tackle health disparities? In this course we will discuss the basic principles of Population Health Management that will help you as (future) health care professional or policymaker to analyse current healthcare challenges and to design possible solutions using the Population Health Management Approach.

Aug 17th 2026
4 Weeks
Interpersonal Communication for Engineering Leaders (Coursera) Coursera
Rice University

Interpersonal Communication for Engineering Leaders (Coursera)

This course covers communication skills that engineering leaders use every day to motivate, inspire, and support the people in their organizations. Speaking and writing are basic leadership communication skills. (We covered these topics in the Specialization course 1 and 3.) However, leaders also need to be skillful interpersonal communicators.

Aug 17th 2026
4 Weeks
Machine Learning Rapid Prototyping with IBM Watson Studio (Coursera) Coursera
IBM

Machine Learning Rapid Prototyping with IBM Watson Studio (Coursera)

An emerging trend in AI is the availability of technologies in which automation is used to select a best-fit model, perform feature engineering and improve model performance via hyperparameter optimization. This automation will provide rapid-prototyping of models and allow the Data Scientist to focus their efforts on applying domain knowledge to fine-tune models. This course will take the learner through the creation of an end-to-end automated pipeline built by Watson Studio’s AutoAI experiment tool, explaining the underlying technology at work as developed by IBM Research.

Aug 17th 2026
4 Weeks