Materials Informatics for Data-Driven Design

Learn how to apply data science, machine learning, and computational workflows to accelerate materials discovery and analyze complex material structures.

4.5 (351) ⏱ 1 oras 49 min 📚 4 aralin 🎧 Audio version

Tungkol sa kursong ito

Traditional materials discovery is often slow and relies heavily on trial-and-error experimentation. Materials informatics changes this by leveraging data science, machine learning, and computational tools to design, analyze, and discover materials at unprecedented speeds. This course guides you through the foundational concepts of materials informatics, showing you how to convert physical material structures into digital data that algorithms can analyze. You will understand how to build predictive models, utilize public materials databases, and apply modern data-driven workflows to accelerate development across different structural scales. What you'll learn: - Understand the core principles of materials informatics and how data science intersects with physical materials chemistry. - Represent material structures digitally using crystal and molecular descriptors, fingerprints, and feature engineering. - Apply machine learning algorithms to predict mechanical, thermal, and electronic properties from materials data. - Navigate and extract valuable information from open-access materials databases and repositories. - Explore active learning and Bayesian optimization strategies for efficient materials discovery. - Analyze hierarchical material structures spanning multiple length scales using computational modeling techniques. You will start with the fundamental definitions of materials data and representation before moving into practical computational workflows. Through clear written explanations, structured code snippets, and practical exercises, you will learn to build predictive models and query materials databases. This course is designed for students, researchers, and engineers in materials science, chemistry, or data science who are new to informatics. No prior experience with machine learning is required, though a basic understanding of materials science concepts is helpful. Begin your journey into the future of materials discovery today.

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  • Maikli at focused
    1 oras 49 min ng practical content

Mga review (8)

Elias Korhonen FI Verified learner
★ 4 · 2026-05-12T17:26:05+00:00

Fantastic course! The material was presented in a very digestible way, and the real-world applications made it super valuable. Highly recommend this one.

حسن الشابي TN Verified learner
★ 5 · 2025-12-26T02:57:05+00:00

This course exceeded my expectations. The real-world applications discussed are incredibly useful. Great job!

لطيفة عبدالله AE Verified learner
★ 1 · 2025-10-19T01:32:05+00:00

Found it a bit dry, tbh. The examples weren't always the most relevant, making it hard to stay engaged through some of the modules.

Karl Andersson SE Verified learner
★ 4 · 2025-08-03T00:17:05+00:00

What a ride! The material was presented in a super accessible way. I'm already thinking about applying what I learned. Awesome stuff.

Camila Dias BR Verified learner
★ 4 · 2025-06-03T07:53:05+00:00

Fantastic resource. I learned so much, and the examples used were super helpful in understanding the concepts. Highly recommend.

Valentina López PA Verified learner
★ 4 · 2025-05-25T10:52:05+00:00

Brilliant course design. The way concepts build on each other is seamless. Very practical and well-explained.

وفاء السيد EG
★ 5 · 2025-05-04T21:48:05+00:00

Couldn't have asked for a better learning experience. The structure flowed perfectly, and the examples were incredibly relevant. Highly recommend!

عمر بن سالم المري BH Verified learner
★ 3 · 2025-01-03T11:08:05+00:00

Fantastic learning experience. The pace was perfect, and the examples really solidified the concepts. Big thumbs up!

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