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
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
Course
Showing 385–392 of 425 results
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PyTorch – Use in AI Course
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Scikit-learn – Use in AI Course
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Keras – Use in AI Course
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Pandas – Use in AI Course
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NumPy – Use in AI Course
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AI Applications in Pharmacy: Leveraging Technology for Innovative Healthcare Solutions Course
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Innovations in AI for Diagnostic & Medical Devices Course
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Optimizing Healthcare & Clinical Analytics with AI Course
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Learn from Expert Mentors
Connect with industry leaders and academic experts who are passionate about teaching
Dr. Dimple Thakar
About Dr. Dimple Thakar
Dr. Dimple Thakar is an esteemed Assistant Professor in Computer Science at Marwadi University, with a prolific 20-year academic career intertwined with over three years of industry experience in IT and software development. With a Ph.D. in Computer Science specializing in steganography, she is a recognized expert in her field.
Dr. Thakar has a deep commitment to education and research, reflected in her roles as Research Coordinator and NAAC criteria coordinator at the Faculty of Computer Application, where she also serves as the Program Coordinator for the BCA course. Her extensive teaching repertoire includes advanced subjects such as Data Structures, C#.NET, Design Analysis and Algorithms, and Object-Oriented Analysis and Design.
In her previous roles, she served as an Associate Professor at the Sunshine Group of Institutions, where she was also the Academic Head of the MCA department and coordinated various programs and cultural activities. Her early career includes significant stints as a lecturer at Geetanjali College and Matushri Virbai Mahila College, enriching her teaching experience.
Dr. Thakar is also notable for her contributions to the IT industry, having developed critical software solutions for sectors including banking and manufacturing, demonstrating her proficiency in a variety of programming languages and technologies.
Her scholarly contributions are substantial, with numerous papers published in international journals and conferences. She is an active member of the editorial board of the Journal of Applied Science and Engineering Research and serves as a reviewer and committee member on several international conferences.
A passionate mentor and educator, Dr. Thakar is dedicated to fostering research and academic excellence among her students, making her a vital asset to both her university and the broader academic and professional communities.
Areas of Expertise
Associate Professor
Computer Science, software development
Associate Professor
Sunshine Group of Institutions, Education
Experience & Education
Client Reviews
Testimonials from Researchers & Professionals
Excellent delivery of course material. Although, we would have benefited from more time to practice with the plethora of presented resources.
Good work
Thank you very much
Very pleasant, calm, willing to help and explain further if something wasn’t clear, hopefully will have opportunity for some cooperation in future.
Thank dea Mentor for your time and dedication to transmit a piece of your expertise.
Good but less innovative
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.
