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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
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📘 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
Hands-on Introduction to NGS Data Analysis: From Raw Sequencing Reads to Biological Interpretation
🗓 Sep 17, 2026
AI
Molecular Dynamics (MD) Simulations using LAMMPS/GROMACS: Predicting Mechanical & Thermal Properties
🗓 Sep 18, 2026
AI
Agentic AI for Industrial Digital Twins: Predictive Maintenance, Smart Sensors & Autonomous Operations
🗓 Sep 18, 2026
AI
AI-Powered Precision Agriculture: Crop Monitoring, ERA5 Climate Stress & Forecasting
🗓 Sep 21, 2026
AI
Green Hydrogen 2.0: AI-Guided Electrocatalyst Discovery, Water Electrolysis & Techno-Economic Optimization
🗓 Sep 23, 2026
Course
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Introduction to RNA-Seq Analysis
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Generative AI and Parametric Design for Sustainable Architecture
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AI-Powered Life Cycle Assessment for Sustainable Green Bioproducts
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Responsible AI for Research and Development: Scientific Writing, Literature Review, Data Analysis and Ethical AI Use
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Microplastics Analytics and Mitigation: Detection Technologies, Risk Assessment & Circular Intervention Strategies
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AI-Assisted Protein Structure Prediction, Molecular Docking and Virtual Screening
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Predictive Epidemiology: ML Frameworks for Global AMR Tracking and Surveillance
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Global Course on Digital Contracts, E-Commerce Transactions and Corporate Legal Risk Management in the AI Era
Original price was: INR ₹4,999.00.INR ₹2,499.00Current price is: INR ₹2,499.00. Add to cart
Learn from Expert Mentors
Connect with industry leaders and academic experts who are passionate about teaching
DR. CHITRA DHAWALE
Science and Technology Department | Professor | Datta Meghe Institute of Education and Research | 25+ years experience
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About DR. CHITRA DHAWALE
Dr. Chitra Dhawale is a Professor in the Science and Technology Department of Datta Meghe Institute of Education and Research (Deemed to be University). She received her Ph.D. Degree in Computer Science from S.G.B.Amravati University in 2009. She is having 25+ years of teaching and research experience in computer science. Her area of Expertise includes: Data Science, Machine Learning, Deep Learning, Python Programming, R Programming, Tableau. She/he is the author of 02 books, 08 book chapters and 78 research papers.
Areas of Expertise
Professor
Science and Technology Department, Science and Technology
Data Science; Machine Learning; Deep Learning; Python Programming; R Programming; Tableau
Experience & Education
2007 – 2009
Professor
S.G.B. Amravati University
Computer Science (Data Science & Machine Learning)
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Testimonials from Researchers & Professionals
All correct. Thank you very much for your suggestions and help during the course.
María Martínez Ranz
In Silico Molecular Modeling and Docking in Drug Development
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
Thank you for good lecture
Aleksandra Kuliga
In Silico Molecular Modeling and Docking in Drug Development
Mentor deliverd the talk very smoothely. He had a good knowledge about MD simulations. He was able to engage the audience and deliver the talk in simple yet inforamtive way.
Meghna Patial
the workshop was very good, thank you very much
Sandra Wingender
AI and Ethics: Governance and Regulation
Dr. Indra Neel was quite descriptive despite the limited time. He shared his wide experience and was kind enough to entertain all questions.
Amlan Das
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.