Introduction to Machine Learning in Geosciences, Certificate | Online (optional) | University of Pisa | Pisa, Italy
5 days
Duration
2400 EUR/year
Free
Unknown
Tuition fee
Unknown
Apply date
Unknown
Start date

About

Within the Introduction to Machine Learning in Geosciences Certificate from University of Pisa a large number of applications that only a few years ago would have been considered impossible to be performed without any sort of human interaction are now autonomously executed by increasingly more powerful machines and sophisticated algorithms.

Visit the Visit programme website for more information

Overview

The Introduction to Machine Learning in Geosciences Certificate from University of Pisa is fed by an enormous quantity of available data, machine learning algorithms can learn, without being explicitly programmed, to solve complex tasks such as speech, face, and object recognition or to play and even defeat the best human players at the ancient game of Go.

Machine-learning is becoming an essential skill in many data-intensive scientific fields, including Earth Sciences related disciplines. The Machine Learning in Geosciences program is offered at University of Pisa.

Certificate Aim:

This summer school aim to provide an overview of the main machine learning methods and their application to geophysical, geological and environmental data, keeping a more practical flavour.

After the course the student will be able to use basic machine learning techniques applied to geosciences. The student will learn to identify which ML method is more suitable than others for the analysis of a particular datasets and to evaluate the performance of the used models. After the course the student will also have an overview of the main Machine Learning libraries (in particular SciKit-Learn, Tensorflow and Keras)

Programme Structure

Courses include:

  • Regression (Linear and Non-linear regression techniques)
  • Classification (Logistic Regression, K-Nearest Neighbors and Support Vector Machines)
  • Clustering (k-means, Hierarchical Clustering, DB-Scan)
  • Data Reduction (PCA and ICA)
  • Convolutional Neural Networks for image recognition

Key information

Duration

  • Full-time
    • 5 days

Start dates & application deadlines

Language

English

Credits

3 ECTS

Delivered

On Campus, Online

Academic requirements

We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.

English requirements

We are not aware of any English requirements for this programme.

Student insurance

Make sure to cover your health, travel, and stay while studying abroad. Even global coverages can miss important items, so make sure your student insurance ticks all the following:

  • Additional medical costs (i.e. dental)
  • Repatriation, if something happens to you or your family
  • Liability
  • Home contents and baggage
  • Accidents
  • Legal aid

We partnered with Aon to provide you with the best affordable student insurance, for a carefree experience away from home.

Get your student insurance now

Starting from €0.53/day, free cancellation any time.

Remember, countries and universities may have specific insurance requirements. To learn more about how student insurance work at University of Pisa Summer School and/or in Italy, please visit Student Insurance Portal.

Other requirements

General requirements

  • Basic knowledge of calculus, linear algebra and statistics (suggested).
  • Basic knowledge of Python Programming.

  • To obtain additional information about the program, we kindly suggest that you visit the programme website, where you can find further details and relevant resources.

Tuition Fee

To always see correct tuition fees
  • International

    2400 EUR/year
    Tuition Fee
    Based on the tuition of 2400 EUR per year during 5 days.
  • EU/EEA

    Free
    Tuition Fee
    Based on the tuition of 0 EUR per year during 5 days.

Living costs for Pisa

750 - 1100 EUR /month
Living costs

The living costs include the total expenses per month, covering accommodation, public transportation, utilities (electricity, internet), books and groceries.

Funding

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