Download Material Informatics: Data Science in Materials 2025
Material Informatics: Data Science in Materials video course download, Data Science for Materials Engineering: AI, ML & Informatics. Unlock the future of materials science with this comprehensive course on Material Informatics — where AI, Machine Learning, and Data Science meet materials engineering.
Whether you’re a student, researcher, or professional, this course will help you explore the powerful intersection of materials design and informatics. In this hands-on course, you’ll learn how to work with real-world material datasets, apply modern ML techniques like decision trees, clustering, and ANN, and even use tools like ChatGPT and the Materials Project API to accelerate materials discovery and design.
- Fundamentals of materials informatics and its role in materials design
- Statistical and machine learning methods tailored for material science
- Data mining, data preprocessing, and database management for materials
- Hands-on with materials science databases and APIs
- Working with images, graphs, and symbolic data in material development
- Optimization techniques including Bayesian and hyperparameter optimization
- Advanced data visualization and interpretable ML
- Introduction to high-throughput experiments and structure prediction
- Use of Python, Jupyter Notebook, and virtual reality tools
- Case studies from Additive Manufacturing and structural materials
Course content
- Fundamentals of materials informatics and its role in materials design
- Statistical and machine learning methods tailored for material science
- Data mining, data preprocessing, and database management for materials
- Hands-on with materials science databases and APIs
- Working with images, graphs, and symbolic data in material development
- Optimization techniques including Bayesian and hyperparameter optimization
- Advanced data visualization and interpretable ML
- Introduction to high-throughput experiments and structure prediction
- Use of Python, Jupiter Notebook, and virtual reality tools
- Case studies from Additive Manufacturing and structural materials
- Tools & Technologies:
- Python, Jupyter Notebook, Materials Project API
- Machine Learning Algorithms
- Synthetic data generation
- Who Should Enroll:
- Materials Science & Engineering students
- Data Scientists entering material design
- Mechanical, Metallurgical & Chemical Engineers
- Researchers in nanotechnology, metallurgy, or additive manufacturing
- Anyone interested in the future of AI-driven material development
Who this course is for:
- Materials Science & Engineering students
- Data Scientists entering material design
- Mechanical, Metallurgical & Chemical Engineers
- Researchers in nanotechnology, metallurgy, or additive manufacturing
- Anyone interested in the future of AI-driven material development
Course details
- Video quality: MP4 | Video: h264, 1280 × 720
- Audio quality: Audio: AAC, 44.1 KHz, 2 Ch
- Last updated 06/2025
- Video duration: 10h 21m
- Number of lessons: 10 sections, 10 lectures
- Language: Language: English
- Compressed file size: 4.81 GB
