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+PINA Tutorials
+==============
+
+In this folder we collect useful tutorials in order to understand the principles and the potential of **PINA**.
+
+Getting started with PINA
+-------------------------
+.. toctree::
+   :maxdepth: 3
+   :titlesonly:
+
+   Introduction to PINA for Physics Informed Neural Networks training <tutorials/tutorial1/tutorial.rst>
+   Introduction to PINA Equation class <tutorials/tutorial12/tutorial.rst>
+   PINA and PyTorch Lightning, training tips and visualizations <tutorials/tutorial11/tutorial.rst>
+   Building custom geometries with PINA Location class <tutorials/tutorial6/tutorial.rst>
+
+
+Physics Informed Neural Networks
+--------------------------------
+.. toctree::
+   :maxdepth: 3
+   :titlesonly:
+
+   Two dimensional Poisson problem using Extra Features Learning<tutorials/tutorial2/tutorial.rst>
+   Two dimensional Wave problem with hard constraint<tutorials/tutorial3/tutorial.rst>
+   Resolution of a 2D Poisson inverse problem<tutorials/tutorial7/tutorial.rst>
+   Periodic Boundary Conditions for Helmotz Equation<tutorials/tutorial9/tutorial.rst>
+   Multiscale PDE learning with Fourier Feature Network<tutorials/tutorial13/tutorial.rst>
+
+Neural Operator Learning
+------------------------
+.. toctree::
+   :maxdepth: 3
+   :titlesonly:
+
+   Two dimensional Darcy flow using the Fourier Neural Operator<tutorials/tutorial5/tutorial.rst>
+   Time dependent Kuramoto Sivashinsky equation using the Averaging Neural Operator<tutorials/tutorial10/tutorial.rst>
+
+Supervised Learning
+-------------------
+.. toctree::
+   :maxdepth: 3
+   :titlesonly:
+
+   Unstructured convolutional autoencoder via continuous convolution<tutorials/tutorial4/tutorial.rst>
+   POD-RBF and POD-NN for reduced order modeling<tutorials/tutorial8/tutorial.rst>