nyrala Posted June 17, 2025 Posted June 17, 2025 https://sanet.pics/storage-11/0625/avif/pSqBOkz7Y1ytl3g1INDAVlM7Mnd8T1lz.avif]Published 6/2025Created by IndustryX.ai Smart ManufacturingMP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 ChLevel: Beginner | Genre: eLearning | Language: English | Duration: 10 Lectures ( 10h 21m ) | Size: 4.81 GB[/center]Data Science for Materials Engineering: AI, ML & InformaticsWhat you'll learnFundamentals of materials informatics and its role in materials designStatistical and machine learning methods tailored for material scienceData mining, data preprocessing, and database management for materialsWorking with images, graphs, and symbolic data in material developmentRequirementsNo prior knowledge required.DescriptionMaterial Informatics: AI, Machine Learning & Data Science in MaterialsUnlock 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. What You'll Learn:Fundamentals of materials informatics and its role in materials designStatistical and machine learning methods tailored for material scienceData mining, data preprocessing, and database management for materialsHands-on with materials science databases and APIsWorking with images, graphs, and symbolic data in material developmentOptimization techniques including Bayesian and hyperparameter optimizationAdvanced data visualization and interpretable MLIntroduction to high-throughput experiments and structure predictionUse of Python, Jupyter Notebook, and virtual reality toolsCase studies from Additive Manufacturing and structural materialsTools & Technologies:Python, Jupyter Notebook, Materials Project APIMachine Learning AlgorithmsSynthetic data generation Who Should Enroll:Materials Science & Engineering studentsData Scientists entering material designMechanical, Metallurgical & Chemical EngineersResearchers in nanotechnology, metallurgy, or additive manufacturingAnyone interested in the future of AI-driven material developmentWho this course is forMaterials Science & Engineering studentsData Scientists entering material designMechanical, Metallurgical & Chemical EngineersResearchers in nanotechnology, metallurgy, or additive manufacturingAnyone interested in the future of AI-driven material developmentHomepagehttps://www.udemy.com/course/material-informatics/]https://www.udemy.com/course/material-informatics/Screenshothttps://sanet.pics/storage-11/0625/avif/lqjnBrMk3yzDetDBb1AMobSJJ25FfzNY.avif]Welcome to https:///blogs/bonnytuts/]My Blog - Check it Every DaysIf you have any troubles with downloading, PM mePlease Buy Premium Account from my links to get high download speed and support meHappy Learning!!Buy Premium From My Links To Get Resumable Support and Max Speed https://rapidgator.net/file/0cad1bf152b047ddab0b9f636956c215/Material_Informatics_Data_Science_in_Materials.part5.rar.htmlhttps://nitroflare.com/view/CF16DC74C025337/Material_Informatics_Data_Science_in_Materials.part5.rar
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