Material Science Courses
Material science courses can help you learn about the properties of materials, material selection, nanotechnology, and the principles of thermodynamics. You can build skills in analyzing material behavior, conducting experiments, and applying statistical methods to interpret data. Many courses introduce tools such as scanning electron microscopes, X-ray diffraction, and software for modeling material properties, that support practical applications in industries like aerospace, electronics, and biomedical engineering.
Popular Material Science Courses and Certifications
Status: Free TrialJohns Hopkins University
Skills you'll gain: Network Analysis, Statistical Modeling, Bayesian Network, R (Software), R Programming, Social Network Analysis, Simulations, Graph Theory, Statistical Analysis, Probability & Statistics, Markov Model, Probability Distribution, Data Visualization, Machine Learning, Statistical Hypothesis Testing
Status: NewStatus: Free TrialSkills you'll gain: Logo Design, Branding, Brand Strategy, Intellectual Property, Graphic Design, Strategic Thinking, Legal Risk, Typography, Design, Creativity, Case Studies
Status: NewSkills you'll gain: Docker (Software), CI/CD, Model Deployment, Cloud Deployment, Cloud Development, Application Performance Management, Google App Engine
Status: NewStatus: Free TrialSkills you'll gain: API Design, Restful API, Application Programming Interface (API), Application Deployment, Spring Boot, Spring Framework, Back-End Web Development, Data Modeling, Database Design, Software Architecture, Object-Relational Mapping, System Configuration, Data Persistence, Business Logic
Status: Free TrialSkills you'll gain: Generative AI, AI Enablement, Responsible AI, AI Product Strategy, OpenAI, Return On Investment, Data Ethics, Artificial Intelligence, ChatGPT, Business Process Automation, Operational Efficiency, Innovation, AI Workflows, Content Creation, Product Design, Customer Support
Skills you'll gain: Prompt Engineering, LLM Application, AI Workflows, AI Orchestration, No-Code Development, OpenAI API, Tool Calling, Generative AI Agents, Vector Databases, Application Programming Interface (API)
Status: PreviewSkills you'll gain: React.js, UI Components, JavaScript Frameworks, Web Development Tools, Maintainability, Javascript, Programming Principles
Status: NewStatus: Free TrialDassault Systèmes
Skills you'll gain: Computer Aided Three-Dimensional Interactive Application (CATIA), 3D Modeling, Design Software
Status: NewStatus: Free TrialSkills you'll gain: PyTorch (Machine Learning Library), Transfer Learning, Natural Language Processing, Large Language Modeling, Generative Model Architectures, Embeddings
Status: PreviewDeepLearning.AI
Skills you'll gain: Deep Learning, Tensorflow, Model Evaluation, Applied Machine Learning, Artificial Neural Networks, Machine Learning Methods, Performance Tuning, Machine Learning, Data Validation, Debugging, Algorithms
Skills you'll gain: Google App Engine, Google Cloud Platform, Cloud Deployment, Application Deployment, Cloud Applications, Go (Programming Language), Serverless Computing, Development Testing, Data Store
Skills you'll gain: ChatGPT, OpenAI API, Model Deployment, LLM Application, Tool Calling, Large Language Modeling, Prompt Engineering, Application Programming Interface (API), No-Code Development, Python Programming, Software Installation, Open Source Technology, Development Environment, Data Science
In summary, here are 10 of our most popular material science courses
- Computational and Graphical Models in Probability: Johns Hopkins University
- Logo Design For Versatility: How Big Brands Have Adapted: Skillshare
- Data Science Model Deployments and Cloud Computing on GCP: Packt
- RESTful API Project - Employee Management System Tool: EDUCBA
- Maximizing the Generative AI Value: Coursera
- Master LangChain with No-Code tools - Flowise and LangFlow: Packt
- Build Reusable React Components: Scrimba
- Practice CATIA Part Design: Dassault Systèmes
- Introduction to Transformer Models for NLP: Unit 1: Pearson
- Améliorez les réseaux neuronaux profonds: DeepLearning.AI
