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

Customers served! 100 + Courses

Courses

Customers served! 100 + Mentors

Mentors

Customers served! 100 + Participants

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 in Plastic Lifecycle Analysis: Detection, Tracking, and Mitigation
🗓 Apr 27, 2026

AI

AI for LCA Automation: Real‑Time Data, NLP & Predictive Impact Modeling
🗓 Apr 27, 2026

AI

Air Quality AI: Spatiotemporal Fusion, Concept Drift & Forecasting
🗓 Apr 29, 2026

AI

AI for Waste Reduction and Resource Optimization
🗓 Apr 29, 2026

AI

Environmental & Social Impact of AI: Assessment, Metrics & Governance
🗓 Apr 29, 2026

AI

AI for Autonomous Industrial Systems and Process Optimization
🗓 Apr 30, 2026

AI

Algorithmic Plasma Physics: AI-Accelerated Nuclear Fusion Commercialization
🗓 May 4, 2026

AI

Characterization Decoder: FTIR, Raman & XRD Made Clear
🗓 May 4, 2026

AI

Sustainable Agriculture: LCA, Remote Sensing & Optimization
🗓 May 5, 2026

Course

Learn from Expert Mentors

Connect with industry leaders and academic experts who are passionate about teaching

Dr. Galiveeti Poornima

Artificial Intelligence | Assistant Professor | Presidency University, Bengaluru | 8+ years experience
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About Dr. Galiveeti Poornima

Dr. Galiveeti Poornima is a distinguished academician and researcher specializing in Machine Learning (ML) and Deep Learning. With a Ph.D. in Computer Science from Presidency University, Bengaluru, she has devoted her research to pioneering advancements in Signed Language Recognition, particularly for Indian Sign Languages. Her expertise extends to the application of ML and AI in healthcare, IoT, and cybersecurity, where she has contributed significantly to the development of intelligent systems for medical diagnostics and social media analytics.

Areas of Expertise

Ph.D.

Computer Science,

Machine Learning (ML), Deep Learning, AI for Healthcare, Python

Experience & Education

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Testimonials from Researchers & Professionals

great

Md Abdullah Al Baki
Biological Sequence Analysis using R Programming

Excellent delivery of course material. Although, we would have benefited from more time to practice with the plethora of presented resources.

Kevin Muwonge
Scientific Paper Writing: Tools and AI for Efficient and Effective Research Communication

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

Though he explained all things nicely, my suggestion is to include some more examples related to hydrogen as fuel, and the necessary action required for its safety and wide use.

Pushpender Kumar Sharma
The Green NanoSynth Workshop: Sustainable Synthesis of NiO Nanoparticles and Renewable Hydrogen Production from Bioethanol

The mentor talked about the basics of microbial consortium and then explained their applications for bioprocess in detail. The Mentor explained the various topics with a clear and detailed approach.

Anirudh Gupta
Designing and Engineering of Artificial Microbial Consortia (AMC) for Bioprocess: Application Approaches

Rich content and good delivery, with limited time to deliver all the necessary material and information.

Kevin Muwonge
Protein Structure Prediction and Validation in Structural Biology

Frequently Asked Questions


1️⃣ What is AI and what will I learn in an AI workshop/course?

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.

2️⃣ Do I need a programming or technical background to join?

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.

3️⃣ How are AI workshops structured (duration, delivery, levels)?

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.

4️⃣ What outcomes can I expect after completing an AI workshop?

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.

5️⃣ Are certificates included and are they recognized?

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.

6️⃣ How long will it take to complete an AI course/workshop?

Duration varies: short workshops may run 2–5 days; bootcamps and structured programs may extend over weeks or months with live sessions and projects.

7️⃣ Will I have access to instructors or mentors?

Quality AI workshops typically include live sessions, Q&A, and mentor support — especially for cohort-based formats. Instructor access levels can vary by program.

8️⃣ What payment options and modes are accepted?

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.

9️⃣ Is the content hands-on with projects and real datasets?

Top AI workshops and bootcamps emphasize hands-on learning, practical exercises, and real data projects rather than just lectures or theory.

🔟 What career paths are supported by completing AI training?

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.

Get In Touch

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