Battery Modeling with Machine Learning

COHORT-BASED COURSE

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Battery Modeling with Machine Learning
NEW
NEXT COHORT

Wed, 9th October, 2024

COURSE DURATION

4 Weeks (4.5 hrs/week)

COURSE LEVEL

Intermediate

€449.00 one-time payment

For self-paced learning options, contact us

NEXT COHORT
Oct 9-Nov 2, 2024
Wed & Sat (4.5 hrs/week)
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HOSTED BY
Dr. Alex Cipolla

Dr. Alex Cipolla

Battery expert with 7+ years experience | Co-founder of Anxer and Project Director at Volta Foundation | Double-degree PhD from CEA-Liten (France) and InnoEnergy.

Pre-requisites

You should be familiar with:

Battery technology and Python

About the Course

Master battery modeling with machine learning for developing sustainable energy solutions. In this course, you will master advanced computational techniques to optimize battery performance, predict lifespan, and drive innovation in energy storage technologies. You won't just learn about machine learning—you'll actively implement it to build and utilize models for improving battery design and operation.

Flexible learning options

  • Attend live (virtual) lectures
  • Access recorded lectures in your private dashboard

Practical application

  • Apply your skills through hands-on projects
  • Engage in real-world case studies

Personalized learning experiences

  • Tailored support and guidance
  • 24x7 support by our dedicated support team

Specialized community access

  • To our Members-only Slack community
  • To our invite-only deep tech global Slack community

Syllabus Overview

  • Fundamental Battery Concepts and Features
  • History of Battery Modeling
  • Types of Battery Models: Electrochemical Models
  • Types of Battery Models: Equivalent Circuit Models
  • Types of Battery Models: Data-Driven Models
  • Comparison and Use Cases of Battery Models
Meet your Instructors
Dr. Alex Cipolla
Dr. Alex Cipolla
Instructor
Battery expert with 7+ years experience | Co-founder of Anxer and Project Director at Volta Foundation | Double-degree PhD from CEA-Liten (France) and InnoEnergy.
Dr. Cipolla has over seven years of experience in the battery sector, specializing in battery modeling and innovative chemistries. He is the co-founder of Anxer and a Project Director at Volta Foundation. Alex holds a dual PhD from CEA-Liten and InnoEnergy in battery technology and entrepreneurship, as well as an MSc in Energy Engineering from Politecnico di Milano.

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Battery Modeling with Machine Learning
For customised payments options, contact us

09 Oct, 2024

Battery Modeling with Machine Learning
One-Time Payment
€449.00

All taxes included

  • One year complete access
  • Shareable certificate on completion
  • Career guidance from instructors
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Frequently Asked Questions

Yes, this course is conducted entirely online in cohorts. You can participate from anywhere with an internet connection. The course features live online sessions, recorded lectures, hands-on assignments, and collaborative projects with your cohort.


You will join the live sessions with the instructor twice per week for four consecutive weeks, on Wednesdays at 6 PM CEST and Saturdays at 5 PM CEST. The Wednesday lecture will primarily cover theoretical aspects and will last for 2 hours. The Saturday session will be 2.5 hours long and will focus on hands-on practical topics.


The course structure and schedule have been carefully designed to accommodate busy schedules and minimize work-related distractions. If you are unable to attend a live session for any reason, you will have access to the recording through your Neovarsity account.


The course includes approximately 30 hours of live instruction and exercises with the instructor. There is also some optional homework. The course is specifically designed for individuals with busy professional and academic schedules, allowing flexibility to skip optional components while still gaining valuable insights.


Yes, you can expect more topics to be covered during the live sessions. The instructor will adjust the content based on the progress and feedback of the participants.


Yes! We encourage you to explore reimbursement options through your company or university. Should you need any assistance or documentation from us to facilitate this process, we're more than happy to help.


For more information or to ask specific questions about the course, please contact Catherine at [email protected] or start an online chat for immediate assistance.