MASTER IN ENERGY SELF-PRODUCTION AND ARTIFICIAL INTELLIGENCE

Do you want to drive your company towards energy independence? Do you want to understand how to best orchestrate energy production needs and capacity?

The master course in Energy Self-Production and Artificial Intelligence will give you the opportunity to accelerate your path towards greater energy and economic sustainability thanks to self-production of energy.

You will meet industry professionals who will support you step by step during the training, teaching you how to use Artificial Intelligence to optimize self-production energy systems.

Who it isaddressed
to?

The course is addressed to:

◉ Technical directors
◉ Energy Manager

and in general to the technical managers of those energy producing and consuming companies who, given the current macroeconomic context, want to accelerate their path towards greater sustainability thanks to self-production of energy.

Mode

This is a blended training course made up of in-person lessons, live streaming training, practical workshops and networking moments.

By attending the course you will also have exclusive access to the MIPU community, a place where professionals meet to network and discuss topics of interest.

At the end of the course all participants will receive a certificate of participation.

What you will learn

The training course will help you develop all the skills necessary to become energetically independent. You will have an overview of the potential of Artificial Intelligence and how this tool can help you optimize photovoltaic, cogeneration and trigeneration systems, hydroelectric or wind systems, as well as a company’s energy consumption.

Thanks to training alternating with moments of discussion, sharing of success cases, practical workshops and the constant support of teachers, you will concretely learn to use artificial intelligence models and apply what you have learned.

Achieve energy independence thanks to Artificial Intelligence

32 hours of training – practical workshop – experiences– networking

Program

32 hours of training in 3 weeks
Thursday 16:00 – 19:00 + Friday 9:00 – 18:00

MODULE 1 - AI for optimization

An in-depth overview of how AI can help us optimize energy production, including from renewable sources, and at the same time predict our energy consumption.

MODULE 2 - Orchestrating requirements and production

An insight into how to best orchestrate the production and sale of energy, how to evaluate investments and calculate the economic return.

MODULE 3 - AI Workshop

A session dedicated to practical workshops in order to understand how to use artificial intelligence models, build an orchestrator and manage it over time.

Structure

We have studied a formula that allows you to combine work activities with the training course.

Training on alternating weeks
Our training is scheduled on Thursday evenings and Fridays to give the opportunity to dedicate the right amount of time to training, without falling behind on work.

Classroom and online training
Alternating online and in-person training gives maximum flexibility, without giving up precious moments of practical exercise and networking.

WEEKEND 1 - Milan

Thursday 15:00 - 19:00 | Friday 09:00 - 18:00

WEEKEND 2 - Live Streaming

Thursday 15:00 - 19:00 | Friday 09:00 - 18:00

WEEKEND 3 - Milan

Thursday 15:00 - 19:00 | Friday 09:00 - 18:00

Project Work

Achieve energy independence thanks to Artificial Intelligence

32 hours of training – practical project works – experiences – networking

Price and financing

€2.700,00 + VAT

Possible discounts for multiple registrations.
Scholarships available for freelancers. Learn more here.

Our scholarships

Dedicated to private individuals and those who register independently without the support of their company

WOMEN IN TECH

Less than a third of the global tech workforce is made up of women. It’s time to change the course.

UPSKILLING UNDER 30

For young people who want to build a profession in the predictive company.

RESKILLING OVER 50

It is never too late to start a new route.

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