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The AI Learning Platform for Researchers
250+ expert-curated AI programs built on scientific rigor and real-world applicability — designed to elevate academic researchers, doctoral scholars, and industry R&D professionals.
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Harvard University
Stanford University
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University of Oxford
University of Cambridge
Caltech
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Yale University
📘 Researchers • 🎓 PhD Scholars • 🧪 Industry R&D
Courses
Mentors
Participants
Why Researchers Trust NanoSchool AI
Research-Focused Curriculum
Every module is engineered to support publication-quality analysis, reproducible workflows, and high-level academic learning.
Led by Experts
Courses created and taught by seasoned professors, data scientists, and active researchers with real-world domain experience.
Structured Learning Ecosystem
1700+ programs across 27+ tracks, 200+ domains — aligned to scientific advancement and industry relevance.
AI Training Initiatives
Upcoming AI Workshops
AI
AI-Powered Precision Agriculture: Remote Sensing, Satellite Data & Machine Learning for Crop Prediction
🗓 Sep 21, 2026
AI
Industrial Digital Twins : AI, IoT, Predictive Maintenance & Autonomous Smart Manufacturing
🗓 Sep 25, 2026
AI
Green Hydrogen 2.0: AI-Guided Electrocatalyst Discovery, Water Electrolysis & Techno-Economic Optimization
🗓 Sep 28, 2026
AI
AI-Powered Drug Discovery: Molecular Screening, ADMET and Lead Prediction
🗓 Sep 28, 2026
Course
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From Patch to Product: Turning Physical Models into Plugins
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AI Governance & Risk Management (AI GRC)
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Intelligent Molecular Diagnostics & Primer Engineering
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Generative AI in Drug Discovery: From Molecules to Medicines
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ML for Epidemiological Forecasting and Vaccine Logistics Optimization
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Epigenetic Mechanisms in Gene Regulation
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Environmental Remediation: Enzyme Technologies and Bioremediation
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Quantum Computing Applications in Biology & Drug Discovery
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Learn from Expert Mentors
Connect with industry leaders and academic experts who are passionate about teaching
Abedeera Gunarathna Patabandige Gayathri Maduwanthi
| | | 4+ years experience
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About Abedeera Gunarathna Patabandige Gayathri Maduwanthi
Gayathri Gunarathna is an experienced Lecturer in Computing and ICT Teacher from Sri Lanka with strong academic and technical expertise in computing, software engineering, programming, web development, and database systems. She currently serves as a Lecturer in Computing/IT at Londontec City Campus, where she delivers IT modules, prepares teaching materials, guides students in programming and web technologies, and supports academic progress. She has also worked as a Senior ICT Teacher and Web Developer, gaining practical experience in teaching, curriculum delivery, software development, system maintenance, and technical troubleshooting. She holds UK qualifications including an MSc in Computing from Wrexham Glyndŵr University and a BSc (Hons) in Software Engineering from Kingston University. Her research interests include Artificial Intelligence, digitalisation in education, emerging computing technologies, and digital forensics.
Areas of Expertise
Computing, Software Engineering, ICT Education, Programming, Web Development, Database Systems, Cybersecurity Basics, Digital Forensics
Role Lecturer in Computing / IT, Computing Department; specialization in Programming, Web Technologies, Databases, Software Engineering, and ICT Education
Java, C#, PHP, C++, Flutter, Python, HTML, CSS, JavaScript, MySQL, MS SQL Server, Firebase, SQLite, Android Studio, Visual Studio, NetBeans, Eclipse, Laravel, Basic Penetration Testing, Secure Coding Practices
Experience & Education
–
Diploma Student
PIBT Campus, Sri Lanka
Foundation and applied training in software engineering, programming, web development, database systems, and application development.
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Testimonials from Researchers & Professionals
Some topics could be organized in different order. That occurred at the end of training in the last day when the mentor needed to remind one by one where is the ligand where is the target. It can be helpful to label components (files) like that and label days of training respectively.
Anna Ogrodowczyk
In Silico Molecular Modeling and Docking in Drug Development
Very nice lectures
VARDIREDDY JYOTSNA
Artificial Intelligence for Cancer Drug Delivery
The mentor was clear and informative, and was also open to providing further help or clarification after the session.
Savina Mariettou
I thank you for delivering such an informative and interesting workshop. I would like to work with you to learn and acquire more knowledge from you.
USHASI DAS
thank you for the lecture and if l ever face any challenges will reach out
Tatenda Justice Gunda
Bacterial Comparative Genomics
Overall, the workshop was conducted with professionalism and easy-to-follow teaching methods, allowing us to better understand and grasp the concepts of mathematical models and infectious disease analysis, without overly intimidating the complexity of the mathematics involved.
If we could have files with more exercises, that would be great, and we could be added to a WhatsApp group where we can see what other colleagues around the world are doing and ask questions if necessary.
Joel KOSIANZA BELABO
Frequently Asked Questions
AI (Artificial Intelligence) refers to systems that perform tasks requiring human-like intelligence — such as learning, reasoning, and decision-making. In AI courses, you typically learn basics of machine learning, neural networks, deep learning, data handling, practical tools, and real-world applications.
Not necessarily. Many beginner-friendly AI courses are designed to be accessible without prior technical experience. However, for advanced workshops, knowledge in Python, statistics, or basic math can be very helpful.
AI workshops vary widely: short hands-on sessions over a few days, multi-week live cohorts, or hybrid models with live sessions and self-paced modules. They can be beginner, intermediate, or advanced in level.
You should gain practical skills such as model building, data analysis, use of AI tools, project experience, and a certificate upon completion. Some programs also support portfolio projects or career guidance.
Yes — most reputable AI workshops include a certificate of completion that can be shared professionally. The recognition depends on the provider’s credibility and your network or industry.
Duration varies: short workshops may run 2–5 days; bootcamps and structured programs may extend over weeks or months with live sessions and projects.
Quality AI workshops typically include live sessions, Q&A, and mentor support — especially for cohort-based formats. Instructor access levels can vary by program.
Most AI programs accept online payments via major gateways (cards, UPI, PayPal) and may offer early-bird or group discounts. Workshops sometimes provide installment or corporate billing options.
Top AI workshops and bootcamps emphasize hands-on learning, practical exercises, and real data projects rather than just lectures or theory.
AI training can open roles such as Data Scientist, ML Engineer, AI Researcher, Business Intelligence Specialist, and domain roles like Predictive Analytics in specific industries — depending on depth and focus.