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🏫 Materials Informatics Dojo

Comprehensive Learning Platform for Data-Driven Materials Development

📚 18 Series | 75+ Chapters | 500+ Code Examples | Total Study Time: 25-35 hours

📚 Introductory Series (3 series)

📘

Data-Driven Materials Introduction

Fundamentals of data-driven approaches in materials science

Beginner 60-90 min 4 chapters

📘

Machine Learning Potentials (MLP) Introduction

Neural network potentials for atomistic simulations

Intermediate 90-120 min 4 chapters

📗

Bioinformatics Introduction

Protein engineering and biomaterial design with AI

Beginner-Intermediate 100-120 min 5 chapters

🤖 Machine Learning Methods (5 series)

🎯

Active Learning Introduction

Efficient exploration with active learning strategies

Intermediate 80-100 min 4 chapters

📊

Bayesian Optimization Introduction

Advanced optimization for materials discovery

Intermediate-Advanced 90-120 min 4 chapters

🧠

Graph Neural Networks (GNN) Introduction

Graph-based deep learning for molecular and crystal structures

Advanced 120-150 min 5 chapters

🔬

GNN Features Comparison Introduction

Comparative analysis of graph neural network architectures

Advanced 80-100 min 4 chapters

🎮

Reinforcement Learning Introduction

RL for materials design and process optimization

Advanced 90-120 min 4 chapters

🔄

Transformer Introduction

Attention mechanisms for materials science applications

Advanced 80-100 min 4 chapters

🔧 Materials Features & Descriptors (2 series)

⚛️

Composition Features Introduction

Chemical composition-based descriptors for materials properties

Intermediate 90-120 min 5 chapters

🧪

Chemoinformatics Introduction

Molecular descriptors and QSAR/QSPR modeling

Intermediate 80-100 min 4 chapters

💻 Computational Methods (2 series)

⚡

Computational Materials Basics Introduction

DFT, molecular dynamics, and quantum chemistry fundamentals

Intermediate 100-120 min 5 chapters

🚀

High-Throughput Computing Introduction

Large-scale materials screening and workflow automation

Advanced 100-120 min 5 chapters

🤖

NIMO: Automated Materials Exploration with AI

Closed-loop optimization combining AI and robotic experiments

Beginner 90-120 min 5 chapters

📊 Data & Experimental (2 series)

🗄️

Materials Databases Introduction

Accessing and utilizing materials data repositories

Beginner 70-90 min 4 chapters

🔬

Experimental Data Analysis Introduction

Machine learning for experimental characterization data

Intermediate 80-100 min 4 chapters

🎯 Application Domains (3 series)

🔋

Battery MI Application

Machine learning for battery materials discovery

Intermediate 80-100 min 4 chapters

⚗️

Catalyst MI Application

AI-driven catalyst design and optimization

Intermediate 80-100 min 4 chapters

💊

Drug Discovery MI Application

Machine learning in pharmaceutical materials development

Intermediate 80-100 min 4 chapters

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