[](https://github.com/microsoft/AI-For-Beginners/blob/main/LICENSE) [](https://GitHub.com/microsoft/AI-For-Beginners/graphs/contributors/) [](https://GitHub.com/microsoft/AI-For-Beginners/issues/) [](https://GitHub.com/microsoft/AI-For-Beginners/pulls/) [](http://makeapullrequest.com) [](https://GitHub.com/microsoft/AI-For-Beginners/watchers/) [](https://GitHub.com/microsoft/AI-For-Beginners/network/) [](https://GitHub.com/microsoft/AI-For-Beginners/stargazers/) [](https://mybinder.org/v2/gh/microsoft/ai-for-beginners/HEAD) [](https://gitter.im/Microsoft/ai-for-beginners?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge) [](https://discord.gg/nTYy5BXMWG) # Intelligenza Artificiale per Principianti - Un Curriculum || |:---:| | AI For Beginners - _Sketchnote di [@girlie_mac](https://twitter.com/girlie_mac)_ | Esplora il mondo dell'**Intelligenza Artificiale** (IA) con il nostro curriculum di 12 settimane e 24 lezioni! Include lezioni pratiche, quiz e laboratori. Il curriculum è adatto ai principianti e copre strumenti come TensorFlow e PyTorch, oltre all'etica nell'IA ### 🌐 Supporto multilingue #### Supportato tramite GitHub Action (Automatizzato e Sempre Aggiornato) [Arabo](../ar/README.md) | [Bengalese](../bn/README.md) | [Bulgaro](../bg/README.md) | [Birmano (Myanmar)](../my/README.md) | [Cinese (semplificato)](../zh/README.md) | [Cinese (tradizionale, Hong Kong)](../hk/README.md) | [Cinese (tradizionale, Macau)](../mo/README.md) | [Cinese (tradizionale, Taiwan)](../tw/README.md) | [Croato](../hr/README.md) | [Ceco](../cs/README.md) | [Danese](../da/README.md) | [Olandese](../nl/README.md) | [Estone](../et/README.md) | [Finlandese](../fi/README.md) | [Francese](../fr/README.md) | [Tedesco](../de/README.md) | [Greco](../el/README.md) | [Ebraico](../he/README.md) | [Hindi](../hi/README.md) | [Ungherese](../hu/README.md) | [Indonesiano](../id/README.md) | [Italiano](./README.md) | [Giapponese](../ja/README.md) | [Kannada](../kn/README.md) | [Coreano](../ko/README.md) | [Lituano](../lt/README.md) | [Malese](../ms/README.md) | [Malayalam](../ml/README.md) | [Marathi](../mr/README.md) | [Nepalese](../ne/README.md) | [Pidgin nigeriano](../pcm/README.md) | [Norvegese](../no/README.md) | [Persiano (Farsi)](../fa/README.md) | [Polacco](../pl/README.md) | [Portoghese (Brasile)](../br/README.md) | [Portoghese (Portogallo)](../pt/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Romeno](../ro/README.md) | [Russo](../ru/README.md) | [Serbo (Cirillico)](../sr/README.md) | [Slovacco](../sk/README.md) | [Sloveno](../sl/README.md) | [Spagnolo](../es/README.md) | [Swahili](../sw/README.md) | [Svedese](../sv/README.md) | [Tagalog (Filippino)](../tl/README.md) | [Tamil](../ta/README.md) | [Telugu](../te/README.md) | [Thailandese](../th/README.md) | [Turco](../tr/README.md) | [Ucraino](../uk/README.md) | [Urdu](../ur/README.md) | [Vietnamita](../vi/README.md) **Se desideri avere ulteriori traduzioni le lingue supportate sono elencate [qui](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)** ## Unisciti alla comunità [](https://discord.gg/nTYy5BXMWG) ## Cosa imparerai **[Mappa mentale del corso](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)** In questo curriculum imparerai: * Diversi approcci all'Intelligenza Artificiale, incluso il "buon vecchio" approccio simbolico con **Rappresentazione della conoscenza** e ragionamento ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)). * **Reti Neurali** e **Deep Learning**, che sono al cuore dell'IA moderna. Illustreremo i concetti dietro questi importanti argomenti usando codice in due dei framework più popolari - [TensorFlow](http://Tensorflow.org) e [PyTorch](http://pytorch.org). * **Architetture neurali** per lavorare con immagini e testo. Copriremo modelli recenti ma potremmo essere un po' carenti rispetto allo stato dell'arte. * Approcci meno diffusi dell'IA, come **Algoritmi genetici** e **Sistemi multi-agente**. Cosa non tratteremo in questo curriculum: > [Trova tutte le risorse aggiuntive per questo corso nella nostra raccolta Microsoft Learn](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) * Casi aziendali sull'utilizzo dell'**IA nel business**. Considera di seguire il percorso di apprendimento [Introduction to AI for business users](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) su Microsoft Learn, o [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), sviluppato in collaborazione con [INSEAD](https://www.insead.edu/). * **Machine Learning classico**, che è ben descritto nel nostro [Machine Learning for Beginners Curriculum](http://github.com/Microsoft/ML-for-Beginners). * Applicazioni pratiche di IA costruite utilizzando **[Cognitive Services](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**. Per questo, ti consigliamo di iniziare con i moduli di Microsoft Learn per [visione](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [elaborazione del linguaggio naturale](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[AI Generativa con Azure OpenAI Service](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** e altri. * Specifici **framework cloud** per ML, come [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum), o [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Considera l'utilizzo dei percorsi di apprendimento [Build and operate machine learning solutions with Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) e [Build and Operate Machine Learning Solutions with Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum). * **IA conversazionale** e **chat bot**. Esiste un percorso di apprendimento separato [Create conversational AI solutions](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum), e puoi anche fare riferimento a [questo post del blog](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) per maggiori dettagli. * **Matematica approfondita** dietro il deep learning. Per questo, raccomandiamo [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) di Ian Goodfellow, Yoshua Bengio e Aaron Courville, che è anche disponibile online su [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/). Per un'introduzione graduale agli argomenti _IA nel cloud_ puoi considerare di seguire il percorso di apprendimento [Get started with artificial intelligence on Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum). # Contenuto | | Link della lezione | PyTorch/Keras/TensorFlow | Laboratorio | | :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ | | 0 | [Configurazione del corso](./lessons/0-course-setup/setup.md) | [Configura il tuo ambiente di sviluppo](./lessons/0-course-setup/how-to-run.md) | | | I | [**Introduzione all'IA**](./lessons/1-Intro/README.md) | | | | 01 | [Introduzione e storia dell'IA](./lessons/1-Intro/README.md) | - | - | | II | **IA simbolica** | | 02 | [Rappresentazione della conoscenza e Sistemi esperti](./lessons/2-Symbolic/README.md) | [Sistemi esperti](./lessons/2-Symbolic/Animals.ipynb) / [Ontologia](./lessons/2-Symbolic/FamilyOntology.ipynb) /[Grafo concettuale](./lessons/2-Symbolic/MSConceptGraph.ipynb) | | | III | [**Introduzione alle reti neurali**](./lessons/3-NeuralNetworks/README.md) ||| | 03 | [Perceptron](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [Notebook](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [Laboratorio](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) | | 04 | [Perceptrone multistrato e creazione del nostro framework](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [Notebook](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [Laboratorio](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) | | 05 | [Introduzione ai framework (PyTorch/TensorFlow) e sovradattamento](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Laboratorio](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) | | IV | [**Visione Artificiale**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [Esplora la Visione Artificiale su Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) | | 06 | [Introduzione alla Computer Vision. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [Notebook](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [Laboratorio](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) | | 07 | [Reti Neurali Convoluzionali](./lessons/4-ComputerVision/07-ConvNets/README.md) & [Architetture CNN](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [Laboratorio](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) | | 08 | [Reti pre-addestrate e apprendimento per trasferimento](./lessons/4-ComputerVision/08-TransferLearning/README.md) and [Trucchi di addestramento](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Laboratorio](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) | | 09 | [Autoencoder e VAE](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | | | 10 | [Reti Generative Avversarie & Trasferimento di Stile Artistico](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | | | 11 | [Rilevamento oggetti](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [Laboratorio](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) | | 12 | [Segmentazione Semantica. U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | | | V | [**Elaborazione del Linguaggio Naturale**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Esplora l'elaborazione del linguaggio naturale su Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)| | 13 | [Rappresentazione del testo. BoW/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | | | 14 | [Embedding semantici delle parole. Word2Vec e GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | | | 15 | [Modellazione del linguaggio. Addestrare i propri embedding](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Laboratorio](./lessons/5-NLP/15-LanguageModeling/lab/README.md) | | 16 | [Reti Neurali Ricorrenti](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb) | | | 17 | [Reti Ricorrenti Generative](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.ipynb) | [Laboratorio](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) | | 18 | [Transformers. BERT.](./lessons/5-NLP/18-Transformers/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | | | 19 | [Riconoscimento delle entità nominate](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb) | [Laboratorio](./lessons/5-NLP/19-NER/lab/README.md) | | 20 | [Grandi modelli linguistici, programmazione dei prompt e compiti few-shot](./lessons/5-NLP/20-LangModels/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | | | VI | **Altre tecniche di IA** || | | 21 | [Algoritmi genetici](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [Notebook](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | | | 22 | [Apprendimento per rinforzo profondo](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [Laboratorio](./lessons/6-Other/22-DeepRL/lab/README.md) | | 23 | [Sistemi multi-agente](./lessons/6-Other/23-MultiagentSystems/README.md) | | | | VII | **Etica dell'IA** | | | | 24 | [Etica dell'IA e IA responsabile](./lessons/7-Ethics/README.md) | [Microsoft Learn: Principi per un'IA responsabile](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | | | IX | **Extra** | | | | 25 | [Reti multimodali, CLIP e VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [Notebook](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | | ## Ogni lezione contiene * Materiale di lettura preliminare * Notebook Jupyter eseguibili, spesso specifici per il framework (**PyTorch** o **TensorFlow**). Il notebook eseguibile contiene anche molto materiale teorico, quindi per comprendere l'argomento è necessario consultare almeno una versione del notebook (o PyTorch o TensorFlow). * **Laboratori** disponibili per alcuni argomenti, che offrono l'opportunità di provare ad applicare il materiale appreso a un problema specifico. * Alcune sezioni contengono link a [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) moduli che coprono argomenti correlati. ## Per iniziare ### 🎯 Nuovo nell'IA? Inizia qui! Se sei completamente nuovo all'IA e vuoi esempi rapidi e pratici, dai un'occhiata ai nostri [**Esempi per principianti**](./examples/README.md)! Questi includono: - 🌟 **Hello AI World** - Il tuo primo programma di IA (riconoscimento di pattern) - 🧠 **Simple Neural Network** - Costruisci una rete neurale da zero - 🖼️ **Image Classifier** - Classifica immagini con commenti dettagliati - 💬 **Sentiment del testo** - Analizza testo positivo/negativo These examples are designed to help you understand AI concepts before diving into the full curriculum. ### 📚 Configurazione del curriculum completo - Abbiamo creato una [setup lesson](./lessons/0-course-setup/setup.md) per aiutarti con l'impostazione del tuo ambiente di sviluppo. - For Educators, we have created a [curricula setup lesson](./lessons/0-course-setup/for-teachers.md) for you too! - How to [Run the code in a VSCode or a Codepace](./lessons/0-course-setup/how-to-run.md) Follow these steps: Fork the Repository: Click on the "Fork" button at the top-right corner of this page. Clone the Repository: `git clone https://github.com/microsoft/AI-For-Beginners.git` Don't forget to star (🌟) this repo to find it easier later. ## Incontra altri studenti Join our [official AI Discord server](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum) to meet and network with other learners taking this course and get support. If you have product feedback or questions whilst building visit our [Azure AI Foundry Developer Forum](https://aka.ms/foundry/forum) ## Quiz > **Una nota sui quiz**: Tutti i quiz sono contenuti nella cartella Quiz-app in etc\quiz-app, o [Online qui](https://ff-quizzes.netlify.app/) They are linked from within the lessons the quiz app can be run locally or deployed to Azure; follow the instruction in the `quiz-app` folder. They are gradually being localized. ## Aiuto richiesto Do you have suggestions or found spelling or code errors? Raise an issue or create a pull request. ## Ringraziamenti speciali * **✍️ Autore principale:** [Dmitry Soshnikov](http://soshnikov.com), PhD * **🔥 Editore:** [Jen Looper](https://twitter.com/jenlooper), PhD * **🎨 Illustratore degli sketchnote:** [Tomomi Imura](https://twitter.com/girlie_mac) * **✅ Creatore dei quiz:** [Lateefah Bello](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/) * **🙏 Collaboratori principali:** [Evgenii Pishchik](https://github.com/Pe4enIks) ## Altri curricula Our team produces other curricula! Check out: ### LangChain [](https://aka.ms/langchain4j-for-beginners) [](https://aka.ms/langchainjs-for-beginners?WT.mc_id=m365-94501-dwahlin) --- ### Azure / Edge / MCP / Agents [](https://github.com/microsoft/AZD-for-beginners?WT.mc_id=academic-105485-koreyst) [](https://github.com/microsoft/edgeai-for-beginners?WT.mc_id=academic-105485-koreyst) [](https://github.com/microsoft/mcp-for-beginners?WT.mc_id=academic-105485-koreyst) [](https://github.com/microsoft/ai-agents-for-beginners?WT.mc_id=academic-105485-koreyst) --- ### Serie Generative AI [](https://github.com/microsoft/generative-ai-for-beginners?WT.mc_id=academic-105485-koreyst) [-9333EA?style=for-the-badge&labelColor=E5E7EB&color=9333EA)](https://github.com/microsoft/Generative-AI-for-beginners-dotnet?WT.mc_id=academic-105485-koreyst) [-C084FC?style=for-the-badge&labelColor=E5E7EB&color=C084FC)](https://github.com/microsoft/generative-ai-for-beginners-java?WT.mc_id=academic-105485-koreyst) [-E879F9?style=for-the-badge&labelColor=E5E7EB&color=E879F9)](https://github.com/microsoft/generative-ai-with-javascript?WT.mc_id=academic-105485-koreyst) --- ### Apprendimento di base [](https://aka.ms/ml-beginners?WT.mc_id=academic-105485-koreyst) [](https://aka.ms/datascience-beginners?WT.mc_id=academic-105485-koreyst) [](https://aka.ms/ai-beginners?WT.mc_id=academic-105485-koreyst) [](https://github.com/microsoft/Security-101?WT.mc_id=academic-96948-sayoung) [](https://aka.ms/webdev-beginners?WT.mc_id=academic-105485-koreyst) [](https://aka.ms/iot-beginners?WT.mc_id=academic-105485-koreyst) [](https://github.com/microsoft/xr-development-for-beginners?WT.mc_id=academic-105485-koreyst) --- ### Serie Copilot [](https://aka.ms/GitHubCopilotAI?WT.mc_id=academic-105485-koreyst) [](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers?WT.mc_id=academic-105485-koreyst) [](https://github.com/microsoft/CopilotAdventures?WT.mc_id=academic-105485-koreyst) ## Ottenere aiuto Se rimani bloccato o hai domande sulla creazione di app per l'IA. Unisciti ad altri studenti e sviluppatori esperti nelle discussioni su MCP. È una community di supporto dove le domande sono benvenute e le conoscenze vengono condivise liberamente. [](https://discord.gg/nTYy5BXMWG) If you have product feedback or errors while building visit: [](https://aka.ms/foundry/forum) --- **Dichiarazione di non responsabilità**: Questo documento è stato tradotto utilizzando il servizio di traduzione automatica [Co-op Translator](https://github.com/Azure/co-op-translator). Pur impegnandoci per l'accuratezza, si prega di notare che le traduzioni automatiche potrebbero contenere errori o imprecisioni. Il documento originale nella sua lingua nativa deve essere considerato la fonte autorevole. Per informazioni critiche, si raccomanda una traduzione professionale effettuata da un traduttore umano. Non siamo responsabili per eventuali incomprensioni o interpretazioni errate derivanti dall'uso di questa traduzione.