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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
MIT
University of Oxford
University of Cambridge
Caltech
Princeton University
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 25, 2026
AI
AI-Powered Structural Biology: AlphaFold-Based Protein Prediction, Validation & Biological Discovery
🗓 Sep 28, 2026
AI
Green Hydrogen 2.0: AI-Driven Electrocatalyst Discovery, Materials Informatics & Techno-Economic Optimization for Hydrogen Production
🗓 Sep 28, 2026
AI
AI-Powered Drug Discovery: Molecular Screening, ADMET Prediction, QSAR Modeling & Lead Optimization
🗓 Sep 28, 2026
AI
Industrial Digital Twins : AI, IoT, Predictive Maintenance & Autonomous Smart Manufacturing
🗓 Sep 30, 2026
AI
AI-Driven Materials Discovery: Machine Learning Potentials, Molecular Dynamics & High-Throughput Screening
🗓 Oct 2, 2026
Course
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Advanced AI and Machine Learning for Professionals
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Scientific & Technical Writing Course
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Tableau for Business Intelligence
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Nanoelectronics and Its Industrial Applications Program
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Quantum Dots: Their Biological and Sensor Applications
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Creating Sustainable and Healthy Buildings: A Course on Natural Ventilation and Building Optimization
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R Programming: Basic to Advanced Course
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Nanoparticles based Electrochemical Sensors Course
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Learn from Expert Mentors
Connect with industry leaders and academic experts who are passionate about teaching
Prof. Mohit Tiwari
| Assistant Professor | Bharati Vidyapeeth’s College of Engineering,Delhi,Delhi, 110063 Delhi, Delhi | 20+ years experience
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About Prof. Mohit Tiwari
Dr. Mohit Tiwari is an Assistant Professor at Bharati Vidyapeeth’s College of Engineering, Delhi, with over 20 years of experience in teaching, research, software engineering, networking, system administration, and IT infrastructure management. He holds a B.Tech in Computer Science and an MBA in Operations and Research.
His expertise includes Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Cloud Computing, IoT, Cybersecurity, Bioinformatics, Medical AI, Research Methodology, and Academic Writing.
Dr. Tiwari has published 50+ research papers in reputed international journals and conferences in the areas of AI, ML, IoT, cybersecurity, healthcare AI, nanotechnology, and smart systems. He also holds 10+ patents/copyrights related to AI, IoT, automation, smart systems, and cybersecurity. Additionally, he has authored/edited 10+ books and contributed multiple book chapters in computing, cloud computing, computational intelligence, nanocomputing, and emerging technologies.
Areas of Expertise
Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Cloud Computing, IoT, Cybersecurity, Computer Networks, IT Infrastructure Management, Research Methodology, Academic Writing, and Emerging Technologies
Assistant Professor, Computer Science / Artificial Intelligence, Machine Learning, Data Science, Cloud Computing, Cybersecurity, IoT, and IT Systems
Python, Machine Learning, Deep Learning, Neural Networks, Data Mining, Cloud Computing, IoT, Networking, Database Administration, System Administration, Web Security, Technical Support, Research Writing, Academic Mentoring
Experience & Education
2007 – 2010
Postgraduate Student
UPRTOU, Allahabad
Academic Highlights: Specialized in Operations Management, Research Methodology, Decision-Making, Business Analytics, Process Optimization, and Management Systems. Developed strong analytical, managerial, and problem-solving skills applicable to academic administration, research planning, and technology management. Awards & Achievements: Completed postgraduate specialization in Operations and Research, strengthening expertise in management research, operational planning, analytical decision-making, and institutional process improvement.
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Testimonials from Researchers & Professionals
Very nice interaction, but need to clear all the doubts in all the sessions and each session should be equally valuable for all as the 2nd day session was most informative while 1st day and 3rd day were more or less like casual.
Shuvam Sar
Good
AATHIRA DAMIA W V
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
informative lecture
Sheenam Sharma
In Silico Molecular Modeling and Docking in Drug Development
Very good way of giving information and training softwares . Thank you sir
Arun S
In Silico Molecular Modeling and Docking in Drug Development
Excellent Presentation and Guidance in AI assisted design of composite materials by the mentor.
RAJKUMAR GUNTI [email protected]
AI-Assisted Composite Materials Design
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.