Predict Battery Health, Lifetime, and Performance Using Data-Driven Models
Explore cutting-edge techniques in battery performance optimization and degradation analysis through machine learning, and gain hands-on experience in predicting battery lifetime and enhancing reliability in energy storage systems
The aim of this workshop is to equip participants with the knowledge and practical skills to leverage machine learning techniques for analyzing battery lifetime, predicting performance degradation, and optimizing the reliability of energy storage systems.
🛠️ Hands-on:
Import and visualize battery cycle data, clean raw dataset, and plot degradation trends in Google Colab
🛠️ Hands-on:
Build a simple ML model to predict battery capacity fade and lifetime using Google Colab
🛠️ Hands-on:
Interpret model results, compare prediction performance, and generate research-ready battery analysis outputs in Google Colab
April 16, 2026
IST
April 16, 2026 – April 18, 2026
IST 05: 30 PM
₹2,499
$50
The live sessions of this workshop are over, so the live fees no longer apply. The recordings are being uploaded. They appear in your dashboard as soon as they are ready, and we will e-mail you then.
Yes. Paid participants get the session recordings and study material in their NanoSchool dashboard (My registrations → Recorded Lectures / Study Material).
Watch the recording in your dashboard and send your questions to the mentor through the support desk.
Yes, an e-certificate of participation after the workshop, with a QR code anyone can verify and an "Add to LinkedIn" button.
Choose the category that matches your current role: Student, Ph.D. Scholar / Researcher, Academician / Faculty or Industry Professional.
By card, UPI or PayPal on the payment page; international bank transfer is also available there.
See our Returns, Refunds & Cancellation policy: Returns, Refunds & Cancellation policy
Registration open
Live, mentor-led and certified. Dates and times in IST.
