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Seungbum Hong
Learn about the materials that have advanced the performance of artificial intelligence, and the machine learning models that could help accelerate the design and development of novel materials.
Read more
Learn about the materials that have advanced the performance of artificial intelligence, and the machine learning models that could help accelerate the design and development of novel materials.
Read more
Learn about the materials that have advanced the performance of artificial intelligence, and the machine learning models that could help accelerate the design and development of novel materials.
This course defines artificial intelligence (AI) as a machine to which some or all of the functions of the human brain have been delegated. It highlights the need, and explains in an easy-to-understand way how machine learning from artificial intelligence can dramatically accelerate the development of new materials.
Register for this course and see more details by visiting:
OpenCourser.com/course/iwck5c/ai
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What's inside
Syllabus
Birth of AI
AI recognizes
AI Emotion
Read more
Syllabus
Birth of AI
AI recognizes
AI Emotion
Read more
AI learns Materials Processing
AI Materials Fab
AI Materials Imaging 1
AI Materials Imaging 2
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Examines how artificial intelligence can accelerate the development of new materials, which is highly relevant to industry
Taught by Seungbum Hong, who is recognized for their work in AI and materials science
Develops skills and knowledge in AI and materials science, which are core skills for materials scientists
Builds a strong foundation for beginners in AI and materials science
Covers unique perspectives and ideas in AI and materials science that may add color to other topics and subjects
Advises students to take prerequisites in materials science before taking this course
Save this course
Save AI Materials to your list so you can find it easily later:
Save
Save
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in AI Materials with these
activities:
Organize Course Materials
Show steps
Stay organized and improve retention by compiling essential materials.
Show steps
-
Create a system for organizing notes, assignments, and readings.
-
Review and summarize key concepts regularly.
Follow Online Machine Learning Tutorials
Show steps
Supplement course materials with guided tutorials to reinforce concepts.
Browse courses on
Machine Learning
Show steps
-
Identify reputable online platforms and resources for machine learning tutorials.
-
Select tutorials that align with the course syllabus and focus on core concepts.
Review 'Artificial Intelligence: A Modern Approach'
Show steps
Build a foundation of machine learning concepts through reviewing theoretical and practical applications.
Show steps
-
Read the introduction and chapter summaries to get an overview of AI's concepts and applications.
-
Focus on chapters covering machine learning algorithms, such as supervised and unsupervised learning.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Join a Study Group
Show steps
Engage with peers to discuss concepts, solve problems, and share insights.
Browse courses on
Machine Learning
Show steps
-
Connect with classmates or find online study groups dedicated to machine learning.
-
Regularly participate in study sessions, actively contributing and seeking support.
Attend a Machine Learning Workshop
Show steps
Gain practical experience and connect with experts in the field.
Browse courses on
Machine Learning
Show steps
-
Research and identify workshops related to machine learning and AI.
-
Register and attend the workshop, actively participating in discussions and hands-on exercises.
Practice Machine Learning Algorithms
Show steps
Enhance understanding of machine learning algorithms and techniques.
Browse courses on
Supervised Learning
Show steps
-
Choose a programming language and framework for practice (e.g., Python, scikit-learn).
-
Work through tutorials and exercises on supervised learning algorithms (e.g., linear regression, decision trees, support vector machines).
-
Explore unsupervised learning algorithms (e.g., clustering, dimensionality reduction).
Develop a Machine Learning Project
Show steps
Apply machine learning techniques to a real-world problem, showcasing proficiency.
Show steps
-
Define a project scope and identify a dataset.
-
Apply machine learning algorithms and techniques to solve the problem.
-
Evaluate the performance of the model and present the results.
Organize Course Materials
Show steps
Stay organized and improve retention by compiling essential materials.
Show steps
Show steps
Show steps
- Create a system for organizing notes, assignments, and readings.
- Review and summarize key concepts regularly.
Follow Online Machine Learning Tutorials
Show steps
Supplement course materials with guided tutorials to reinforce concepts.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Identify reputable online platforms and resources for machine learning tutorials.
- Select tutorials that align with the course syllabus and focus on core concepts.
Review 'Artificial Intelligence: A Modern Approach'
Show steps
Build a foundation of machine learning concepts through reviewing theoretical and practical applications.
Show steps
Show steps
Show steps
- Read the introduction and chapter summaries to get an overview of AI's concepts and applications.
- Focus on chapters covering machine learning algorithms, such as supervised and unsupervised learning.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Join a Study Group
Show steps
Engage with peers to discuss concepts, solve problems, and share insights.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Connect with classmates or find online study groups dedicated to machine learning.
- Regularly participate in study sessions, actively contributing and seeking support.
Attend a Machine Learning Workshop
Show steps
Gain practical experience and connect with experts in the field.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Research and identify workshops related to machine learning and AI.
- Register and attend the workshop, actively participating in discussions and hands-on exercises.
Practice Machine Learning Algorithms
Show steps
Enhance understanding of machine learning algorithms and techniques.
Browse courses on
Supervised Learning
Show steps
Show steps
Show steps
- Choose a programming language and framework for practice (e.g., Python, scikit-learn).
- Work through tutorials and exercises on supervised learning algorithms (e.g., linear regression, decision trees, support vector machines).
- Explore unsupervised learning algorithms (e.g., clustering, dimensionality reduction).
Develop a Machine Learning Project
Show steps
Apply machine learning techniques to a real-world problem, showcasing proficiency.
Show steps
Show steps
Show steps
- Define a project scope and identify a dataset.
- Apply machine learning algorithms and techniques to solve the problem.
- Evaluate the performance of the model and present the results.
Career center
Learners who complete AI Materials will develop knowledge and skills
that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer develops and implements machine learning models to solve real-world problems. This course may be useful for a Machine Learning Engineer who wants to learn how to apply machine learning to the design and development of new materials.
Research Scientist
Research Scientist
A Research Scientist conducts research to advance scientific knowledge. This course may be useful for a Research Scientist who wants to learn how to use artificial intelligence to accelerate the development of new materials.
Technical Writer
Technical Writer
A Technical Writer creates and edits technical documents, such as user manuals, white papers, and presentations. This course may be useful for a Technical Writer who wants to learn how to write about artificial intelligence and its applications in materials science.
Data Scientist
Data Scientist
A Data Scientist uses data to solve business problems. This course may be useful for a Data Scientist who wants to learn how to use machine learning to analyze materials data and identify trends.
Science Communicator
Science Communicator
A Science Communicator communicates scientific information to the public. This course may be useful for a Science Communicator who wants to learn how to communicate about artificial intelligence and its applications in materials science.
Management Consultant
Management Consultant
A Management Consultant helps businesses and organizations improve their performance. This course may be useful for a Management Consultant who wants to learn how to use artificial intelligence to help businesses develop new materials.
Business Development Manager
Business Development Manager
A Business Development Manager develops and implements strategies to grow a company's business. This course may be useful for a Business Development Manager who wants to learn how to use artificial intelligence to develop new materials.
Patent Attorney
Patent Attorney
A Patent Attorney helps clients obtain and protect patents for their inventions. This course may be useful for a Patent Attorney who wants to learn how to write and prosecute patents related to artificial intelligence and materials science.
Investment Analyst
Investment Analyst
An Investment Analyst researches and analyzes investments for clients. This course may be useful for an Investment Analyst who wants to learn how to identify and invest in companies that are developing new materials.
Science Teacher
Science Teacher
A Science Teacher teaches science to students. This course may be useful for a Science Teacher who wants to learn how to incorporate artificial intelligence into their teaching.
Materials Scientist
Materials Scientist
A Materials Scientist researches and develops new and improved materials for various industries, including aerospace, automotive, and electronics. This course may be useful for a Materials Scientist who wants to understand how artificial intelligence can be used to accelerate the development of new materials.
Sales Manager
Sales Manager
A Sales Manager leads and manages a team of sales professionals. This course may be useful for a Sales Manager who wants to learn how to use artificial intelligence to develop new materials.
Financial Analyst
Financial Analyst
A Financial Analyst researches and analyzes financial data for clients. This course may be useful for a Financial Analyst who wants to learn how to analyze the financial performance of companies that are developing new materials.
Product Manager
Product Manager
A Product Manager develops and manages new products. This course may be useful for a Product Manager who wants to learn how to use artificial intelligence to develop new materials.
Consultant
Consultant
A Consultant provides advice to businesses and organizations on a variety of topics. This course may be useful for a Consultant who wants to learn how to use artificial intelligence to help businesses develop new materials.
For more career information including salaries, visit:
OpenCourser.com/course/iwck5c/ai
Reading list
We've selected ten books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
AI Materials.
Provides a practical introduction to density functional theory (DFT), which powerful computational method used to study the electronic structure of materials.
Save
Provides a comprehensive overview of molecular modeling and simulation, which are powerful computational methods used to study the behavior of molecules and materials.
Provides a comprehensive overview of thermodynamics and statistical mechanics, which are powerful theoretical frameworks used to study the behavior of materials.
Save
Provides a comprehensive overview of solid state physics, which is the study of the physical properties of solids.
Provides a comprehensive overview of quantum mechanics, which is the study of the physical properties of matter at the atomic and subatomic level.
Provides a comprehensive overview of physics, which is the study of the physical world.
Save
Provides a comprehensive overview of theoretical physics, which is the study of the fundamental principles of the universe.
Provides a comprehensive overview of machine learning, which is the study of the design and development of algorithms that can learn from data.
Save
Provides a comprehensive overview of deep learning, which powerful machine learning technique that has been used to achieve state-of-the-art results in a wide range of tasks.
Provides a comprehensive overview of reinforcement learning, which powerful machine learning technique that has been used to achieve state-of-the-art results in a wide range of tasks.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/iwck5c/ai
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Level
Introductory
Via
Coursera
Institution
Korea Advanced Institute of Science and Technology(KAIST)
Instructor
Seungbum Hong
Language
English
Good to know
Examines how artificial intelligence can accelerate the development of new materials, which is highly relevant to industry
Taught by Seungbum Hong, who is recognized for their work in AI and materials science
Develops skills and knowledge in AI and materials science, which are core skills for materials scientists
Builds a strong foundation for beginners in AI and materials science
Covers unique perspectives and ideas in AI and materials science that may add color to other topics and subjects
Advises students to take prerequisites in materials science before taking this course
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