Artificial Inteligenece and Machine learning Techniques for Functional Materials

Artificial Intelligence and Machine Learning Techniques for Functional Materials
Course Outline
This course introduces how Machine Learning (ML) and Artificial Intelligence (AI) are transforming modern materials science. Learners will explore how materials datasets, such as structural data, spectral data, and microstructure images, can be processed and analyzed using AI techniques to uncover patterns that are difficult to identify through traditional methods. The course covers essential ML concepts including data preparation, feature extraction, supervised and unsupervised learning, model building, and performance evaluation, all within the context of materials research.
The course also highlights how AI accelerates materials discovery by predicting properties, identifying defects, classifying materials, and guiding the design of new materials through data-driven insights. Hands-on exercises using Python and popular ML libraries enable participants to develop end-to-end AI workflows for real materials datasets. By the end of the program, learners will gain practical skills in applying ML and AI tools to solve challenges in materials development, characterization, and optimization, preparing them for research and industry roles in the growing field of AI-driven materials science.
Course Syllabus

Please Click here…Machine Learning Course final syllabus (1)
Who can Apply?….
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B.Sc./B.Tech students
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M.Sc./M.Tech students
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Ph.D. scholars
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Faculty Members
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Industry professionals dealing with materials development or materials data
Course Highlights
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20-credit comprehensive program (6 months course) covering AI and ML for materials science
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Hybrid learning mode with both online and in-person sessions
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Hands-on training using Python and popular ML libraries
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Real-world materials datasets for practical applications
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AI-based property prediction, defect detection, and materials classification
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Expert lectures and guided assignments for skill development
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Mini-projects to build end-to-end AI/ML workflows
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Suitable for students, researchers, and industry professionals
Account details
The Director School of Polymer Science and Technology
Account no: 42119806899
IFSC Code: SBIN0070669
After payment, please share the screenshot of payment details to the email id: materialsscienceml2025@gmail.com
Course Fee details
Indian Participants
Category
Fee
Students affiliated to MG university ₹ 10000
Students not affiliated to MG university ₹ 15000
Participants from Academic institutions ₹ 20000
Industry professionals ₹ 25000
International Participants
Category
Fees
International Students : € 500
International participants from academic institutions : € 1000
International participants from industry : € 1500
Registration Fee: ₹500 for Indian participants and € 50 for International Participants.
Upon completion of the course, participants will be evaluated through four theory examinations and one mini-project. Securing a minimum of 50% marks is mandatory for the award of the certificate issued by the School of Polymer Science and Technology. To apply the course: https://forms.gle/Sp4Q3QJorbAqbqu57
Contact Details
Dr. Saju Joseph
Assistant Professor
School of Nanoscience and Nanotechnology
Mahatma Gandhi University
Mobile no:+918281915276
Ms. Deepa S Dev
Senior Research Fellow
IIUCNN
Mahatma Gandhi University
Mobile no:+919539717207

Course email id: materialsscienceml2025@gmail.com