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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.
📘 Researchers • 🎓 PhD Scholars • 🧪 Industry R&D
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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
Blue Bioeconomy & Aquaculture LCA: Tools for Climate-Smart Coastal and Marine Food Systems
🗓 Jan 21, 2026
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Advance Artificial Intelligence Certification: Mechanics, Ethics, and Impact
🗓 Jan 26, 2026
AI
AI-Driven Insect Immunology: Enhancing Pest Control Through Advanced Biotechnological Solutions
🗓 Jan 27, 2026
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R Programming: Basic to Advanced
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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
Contents were excellent
Surya Narain Lal
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
The mentor was supportive, clear in their guidance, and encouraged active participation throughout the process.
António Ricardo de Bastos Teixeira
Large Language Models (LLMs) and Generative AI
very good explanation, clear and precise
Fatima Almusleh
Prediction of Protein Structure Using AlphaFold: An Artificial Intelligence (AI) Program
Very good way of giving information and training softwares . Thank you sir
Arun S
In Silico Molecular Modeling and Docking in Drug Development
The mentor was supportive, clear in their guidance, and encouraged active participation throughout the process.
António Ricardo de Bastos Teixeira
Generative AI and GANs
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.