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L'Italiano nel mondo
Introduction to HTML5
Umano Digitale
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Wolfram U offers free open interactive courses, learning events and other educational resources for professional and technical development.
Learn digital image processing in Wolfram Language: adjust brightness and contrast, transform histograms, segment images, reduce noise, detect keypoints, and analyze object shapes.
Use Wolfram Language notebooks for chemistry: access curated data and PubChem, build Molecule objects from SMILES, import SDF, XYZ and Cube files, and match atomic patterns.
Build interactive chemistry lessons in Wolfram Notebooks: pull curated data with the Entity framework, render 2D and 3D molecular models, and publish assessments online.
Combine coding and art: create visual art, computational poetry, audio and text- and graphics-based video games with Wolfram Language built-in functions in notebooks.
Review elementary algebra and apply it to linear systems, matrices and optimization, then work through the mathematics of finance, probability, Bayes' theorem, Markov chains and game theory.
Perform supervised and unsupervised learning in Wolfram Language: apply machine learning superfunctions to regression, classification, clustering and anomaly detection in just a few lines of code.
Build neural nets in Wolfram Language: apply pre-trained models from the Neural Net Repository, use transfer learning, assemble layers, and train, test and inspect your own networks.
Use Wolfram Notebooks for teaching: code with the Wolfram AI Assistant, work with and transfer data, and build interactive content for science, math and algorithmic thinking.
Learn to install and call functions from Wolfram Language Paclet Repository paclets, then build your own with paclet.wl metadata, documentation and GitHub CI/CD deployment.
Build Wolfram Language paclets: write PacletInfo.wl metadata, use PacletTools, author documentation with Documentation Tools, and find or submit paclets in the Paclet Repository.
Solve AIME, PROMYS and SUMaC contest problems with Wolfram Language: visualize word problems, apply number theory, combinatorics, discrete calculus and algebra, and test solutions.
Build, train and validate neural nets in the Wolfram Language: linear and nonlinear regression, image classification, layer visualization, and the Neural Net Repository.
Write Wolfram Language code outside notebooks: install the official Sublime Text package and VS Code extension, and use Language Server Protocol for syntax and semantic highlighting.
Import, visualize and compute on DNA sequences, medical tests and anatomical models in Wolfram Language, then build machine learning models that detect tumors and classify cells.
Perform machine learning tasks in Wolfram Language: build a feature extractor to cluster images, compare classification models, retrain neural networks, and access LLM technology.
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