[![GitHub license](https://img.shields.io/github/license/microsoft/ML-For-Beginners.svg)](https://github.com/microsoft/ML-For-Beginners/blob/master/LICENSE) [![GitHub contributors](https://img.shields.io/github/contributors/microsoft/ML-For-Beginners.svg)](https://GitHub.com/microsoft/ML-For-Beginners/graphs/contributors/) [![GitHub issues](https://img.shields.io/github/issues/microsoft/ML-For-Beginners.svg)](https://GitHub.com/microsoft/ML-For-Beginners/issues/) [![GitHub pull-requests](https://img.shields.io/github/issues-pr/microsoft/ML-For-Beginners.svg)](https://GitHub.com/microsoft/ML-For-Beginners/pulls/) [![PRs Welcome](https://img.shields.io/badge/PRs-welcome-brightgreen.svg?style=flat-square)](http://makeapullrequest.com) [![GitHub watchers](https://img.shields.io/github/watchers/microsoft/ML-For-Beginners.svg?style=social&label=Watch)](https://GitHub.com/microsoft/ML-For-Beginners/watchers/) [![GitHub forks](https://img.shields.io/github/forks/microsoft/ML-For-Beginners.svg?style=social&label=Fork)](https://GitHub.com/microsoft/ML-For-Beginners/network/) [![GitHub stars](https://img.shields.io/github/stars/microsoft/ML-For-Beginners.svg?style=social&label=Star)](https://GitHub.com/microsoft/ML-For-Beginners/stargazers/) ### 🌐 Usaidizi wa Lugha Nyingi #### Unaungwa Mkono Kupitia Hatua za GitHub (Moja kwa Moja & Daima Imesasishwa) [Arabic](../ar/README.md) | [Bengali](../bn/README.md) | [Bulgarian](../bg/README.md) | [Burmese (Myanmar)](../my/README.md) | [Chinese (Simplified)](../zh-CN/README.md) | [Chinese (Traditional, Hong Kong)](../zh-HK/README.md) | [Chinese (Traditional, Macau)](../zh-MO/README.md) | [Chinese (Traditional, Taiwan)](../zh-TW/README.md) | [Croatian](../hr/README.md) | [Czech](../cs/README.md) | [Danish](../da/README.md) | [Dutch](../nl/README.md) | [Estonian](../et/README.md) | [Finnish](../fi/README.md) | [French](../fr/README.md) | [German](../de/README.md) | [Greek](../el/README.md) | [Hebrew](../he/README.md) | [Hindi](../hi/README.md) | [Hungarian](../hu/README.md) | [Indonesian](../id/README.md) | [Italian](../it/README.md) | [Japanese](../ja/README.md) | [Kannada](../kn/README.md) | [Korean](../ko/README.md) | [Lithuanian](../lt/README.md) | [Malay](../ms/README.md) | [Malayalam](../ml/README.md) | [Marathi](../mr/README.md) | [Nepali](../ne/README.md) | [Nigerian Pidgin](../pcm/README.md) | [Norwegian](../no/README.md) | [Persian (Farsi)](../fa/README.md) | [Polish](../pl/README.md) | [Portuguese (Brazil)](../pt-BR/README.md) | [Portuguese (Portugal)](../pt-PT/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Romanian](../ro/README.md) | [Russian](../ru/README.md) | [Serbian (Cyrillic)](../sr/README.md) | [Slovak](../sk/README.md) | [Slovenian](../sl/README.md) | [Spanish](../es/README.md) | [Swahili](./README.md) | [Swedish](../sv/README.md) | [Tagalog (Filipino)](../tl/README.md) | [Tamil](../ta/README.md) | [Telugu](../te/README.md) | [Thai](../th/README.md) | [Turkish](../tr/README.md) | [Ukrainian](../uk/README.md) | [Urdu](../ur/README.md) | [Vietnamese](../vi/README.md) > **Unapendelea Kukopa Mahali Pako?** > Hifadhidata hii ina tafsiri za lugha 50+ ambazo huongeza sana ukubwa wa kupakua. Ili kukopa bila tafsiri, tumia sparse checkout: > ```bash > git clone --filter=blob:none --sparse https://github.com/microsoft/ML-For-Beginners.git > cd ML-For-Beginners > git sparse-checkout set --no-cone '/*' '!translations' '!translated_images' > ``` > Hii itakupatia kila kitu unachohitaji kukamilisha kozi hii kwa kupakua haraka zaidi. #### Jiunge na Jamii Yetu [![Microsoft Foundry Discord](https://dcbadge.limes.pink/api/server/nTYy5BXMWG)](https://discord.gg/nTYy5BXMWG) Tuna mfululizo wa kujifunza kwenye Discord ukihusisha AI, jifunze zaidi na ujiunge nasi kwenye [Mfululizo wa Kujifunza na AI](https://aka.ms/learnwithai/discord) kuanzia 18 - 30 Septemba, 2025. Utapokea vidokezo na mbinu za kutumia GitHub Copilot kwa Sayansi ya Data. ![Learn with AI series](../../translated_images/sw/3.9b58fd8d6c373c20.webp) # Kujifunza Mashine kwa Kompyuta kwa Waanzilishi - Mtaala > 🌍 Tembea duniani kote tunapochunguza Kujifunza Mashine kupitia tamaduni za dunia 🌍 Wafuasi wa Cloud Advocates wa Microsoft wana furaha kutoa mtaala wa wiki 12, somo 26 kuhusu **Kujifunza Mashine**. Katika mtaala huu, utajifunza kuhusu kile kinachoitwa mara nyingine **kujifunza mashine klassiki**, ukitumia hasa maktaba ya Scikit-learn na kuepuka deep learning, ambayo inashughulikiwa katika [mtaala wetu wa AI kwa Waanzilishi](https://aka.ms/ai4beginners). Pia weka masomo haya sambamba na mtaala wetu wa ['Sayansi ya Data kwa Waanzilishi'](https://aka.ms/ds4beginners). Tembea nasi duniani kote tunapotumia mbinu hizi klassiki kwenye data kutoka sehemu nyingi za dunia. Kila somo lina majaribio ya kabla na baada ya somo, maelekezo yaliyoandikwa kukamilisha somo, suluhisho, kazi ya nyumbani, na mengine zaidi. Mbinu yetu ya kujifunza kwa mradi inakuruhusu kujifunza huku ukiwa unajenga, njia thabiti ya kupata ujuzi mpya. **✍️ Shukrani za dhati kwa waandishi wetu** Jen Looper, Stephen Howell, Francesca Lazzeri, Tomomi Imura, Cassie Breviu, Dmitry Soshnikov, Chris Noring, Anirban Mukherjee, Ornella Altunyan, Ruth Yakubu na Amy Boyd **🎨 Pia shukrani kwa wachoraji wetu** Tomomi Imura, Dasani Madipalli, na Jen Looper **🙏 Shukrani maalum 🙏 kwa waandishi, wakaguzi, na wachangiaji wa maudhui wa Microsoft Student Ambassador**, hasa Rishit Dagli, Muhammad Sakib Khan Inan, Rohan Raj, Alexandru Petrescu, Abhishek Jaiswal, Nawrin Tabassum, Ioan Samuila, na Snigdha Agarwal **🤩 Asante zaidi kwa Microsoft Student Ambassadors Eric Wanjau, Jasleen Sondhi, na Vidushi Gupta kwa masomo yetu ya R!** # Kuanzia Fuata hatua hizi: 1. **Fanya Fork ya Hifadhidata**: Bonyeza kitufe cha "Fork" upande wa juu kulia wa ukurasa huu. 2. **Kopa Hifadhidata**: `git clone https://github.com/microsoft/ML-For-Beginners.git` > [pata rasilimali zote za ziada za kozi hii katika mkusanyiko wetu wa Microsoft Learn](https://learn.microsoft.com/en-us/collections/qrqzamz1nn2wx3?WT.mc_id=academic-77952-bethanycheum) > 🔧 **Unahitaji msaada?** Angalia [Mwongozo wa Kutatua Matatizo](TROUBLESHOOTING.md) kwa suluhisho za matatizo yanayojirudia kwenye usakinishaji, usanidi, na kuendesha masomo. **[Wanafunzi](https://aka.ms/student-page)**, kutumia mtaala huu, fanya fork ya repozitori yote kwenye akaunti yako ya GitHub na kamilisha mazoezi peke yako au na kikundi: - Anza na jaribio kabla ya somo. - Soma somo na kamilisha shughuli, simama na fikiria kila kipimo cha maarifa. - Jaribu kutengeneza miradi kwa kuelewa masomo badala ya kuendesha msimbo wa suluhisho; hata hivyo msimbo huo upo katika folda za `/solution` katika kila somo linalojikita kwenye mradi. - Fanya jaribio baada ya somo. - Kamilisha changamoto. - Kamilisha kazi ya nyumbani. - Baada ya kukamilisha kundi la masomo, tembelea [Bodi ya Majadiliano](https://github.com/microsoft/ML-For-Beginners/discussions) na "jifunze kwa sauti" kwa kujaza PAT rubric inayofaa. 'PAT' ni Chombo cha Tathmini ya Maendeleo ambacho ni rubric unayojaza ili kuendeleza kujifunza kwako. Unaweza pia kutoa maoni juu ya PAT nyingine ili tujifunze pamoja. > Kwa masomo zaidi, tunapendekeza kufuata moduli na njia za kujifunza hizi za [Microsoft Learn](https://docs.microsoft.com/en-us/users/jenlooper-2911/collections/k7o7tg1gp306q4?WT.mc_id=academic-77952-leestott). **Walimu**, tumetoa [mapendekezo kadhaa](for-teachers.md) kuhusu jinsi ya kutumia mtaala huu. --- ## Video za Maelekezo Baadhi ya masomo yanapatikana kama video fupi. Unaweza kupata yote haya ndani ya masomo, au kwenye [orodha ya video za ML kwa Waanzilishi kwenye channel ya Microsoft Developer YouTube](https://aka.ms/ml-beginners-videos) kwa kubonyeza picha hapa chini. [![ML for beginners banner](../../translated_images/sw/ml-for-beginners-video-banner.63f694a100034bc6.webp)](https://aka.ms/ml-beginners-videos) --- ## Kutana na Timu [![Promo video](../../images/ml.gif)](https://youtu.be/Tj1XWrDSYJU) **Gif na** [Mohit Jaisal](https://linkedin.com/in/mohitjaisal) > 🎥 Bonyeza picha hapo juu kwa video kuhusu mradi na watu waliouunda! --- ## Mbinu ya Kufundisha Tumechagua mbinu mbili za kufundisha wakati wa kujenga mtaala huu: kuhakikisha ni **mradi unaotekelezwa kwa mikono** na kwamba unajumuisha **mara kwa mara quizzes**. Zaidi ya hayo, mtaala huu una **kauli mbiu** ya pamoja kwa kumuunganisha. Kwa kuhakikisha maudhui yanaendana na miradi, mchakato unakuwa wa kuvutia zaidi kwa wanafunzi na kunahakikisha wazo la dhahania linakumbukwa. Zaidi ya hayo, jaribio la chini ya mzigo kabla ya darasa linaweka nia ya mwanafunzi kuelekea kujifunza mada, wakati jaribio la pili baada ya darasa linahakikisha kumbukumbu zaidi. Mtaala huu umeundwa kuwa rahisi kubadilika na kufurahisha na unaweza kufuatwa kwa jumla au sehemu. Miradi inaanza mdogo na kuwa ngumu zaidi mwishoni mwa mzunguko wa wiki 12. Mtaala huu pia unajumuisha maelezo ya matumizi halisi ya ML, ambayo yanaweza kutumika kama alama ya ziada au msingi wa majadiliano. > Tafuta [Kanuni Zetu za Maadili](CODE_OF_CONDUCT.md), [Mchango](CONTRIBUTING.md), [Tafsiri](TRANSLATIONS.md), na [Kutatua Matatizo](TROUBLESHOOTING.md). Tunakaribisha maoni yako ya kujenga! ## Kila somo linajumuisha - chati ya sketchnote kwa hiari - video za ziada kwa hiari - video ya maelekezo (masomo mengine pekee) - [jaribio la joto kabla ya somo](https://ff-quizzes.netlify.app/en/ml/) - somo lililoandikwa - kwa masomo yanayojikita kwenye mradi, mwongozo wa hatua kwa hatua wa jinsi ya kujenga mradi - vipimo vya maarifa - changamoto - somo la ziada - kazi ya nyumbani - [jaribio baada ya somo](https://ff-quizzes.netlify.app/en/ml/) > **Tafadhali kuhusu lugha**: Masomo haya huandikwa hasa kwa Python, lakini mengi yanaweza kupatikana pia kwa R. Ili kumaliza somo la R, nenda kwenye folda ya `/solution` na tatua masomo ya R. Yana kiambatisho cha .rmd kinachoashiria faili ya **R Markdown** ambayo inaweza kueleweka kama jalada la `vipande vya msimbo` (ya R au lugha nyingine) na `kichwa cha YAML` (kinachoongoza jinsi ya kuitengeneza matokeo kama PDF) katika `nyaraka za Markdown`. Kwa hiyo, ni mfumo bora wa uandishi kwa sayansi ya data kwa sababu hukuruhusu kuunganisha msimbo wako, matokeo yake, na mawazo yako kwa kuyaratibu kwa Markdown. Zaidi ya hayo, nyaraka za R Markdown zinaweza kutengenezwa kuwa aina mbalimbali za matokeo kama PDF, HTML, au Word. > **Kumbuka kuhusu mitihani ya maarifa**: Mitihani yote iko ndani ya [Folda ya Programu ya Mitihani](../../quiz-app), kwa jumla ya mitihani 52 yenye maswali matatu kila moja. Imeunganishwa ndani ya masomo lakini programu ya mitihani inaweza kuendeshwa kwa ndani; fuata maelekezo katika folda ya `quiz-app` ili kuiendesha au kuiweka moja kwa moja Azure. | Nambari ya Somo | Mada | Kikundi cha Somo | Malengo ya Kujifunza | Somo Linalounganishwa | Mwandishi | | :-------------: | :--------------------------------------------------------------: | :--------------------------------------------------------: | ----------------------------------------------------------------------------------------------------------------------------- | :------------------------------------------------------------------------------------------------------------------------------------------: | :--------------------------------------------------: | | 01 | Utangulizi wa ujifunzaji wa mashine | [Utangulizi](1-Introduction/README.md) | Jifunze dhana msingi nyuma ya ujifunzaji wa mashine | [Somo](1-Introduction/1-intro-to-ML/README.md) | Muhammad | | 02 | Historia ya ujifunzaji wa mashine | [Utangulizi](1-Introduction/README.md) | Jifunze historia inayosimamia uwanja huu | [Somo](1-Introduction/2-history-of-ML/README.md) | Jen na Amy | | 03 | Usawa na ujifunzaji wa mashine | [Utangulizi](1-Introduction/README.md) | Ni masuala gani muhimu ya kifalsafa kuhusu usawa ambayo wanafunzi wanapaswa kuyazingatia wakati wa kujenga na kutumia mifano ya ML? | [Somo](1-Introduction/3-fairness/README.md) | Tomomi | | 04 | Mbinu za ujifunzaji wa mashine | [Utangulizi](1-Introduction/README.md) | Ni mbinu gani wanazotumia watafiti wa ML kujenga mifano ya ML? | [Somo](1-Introduction/4-techniques-of-ML/README.md) | Chris na Jen | | 05 | Utangulizi wa urekebishaji | [Urekebishaji](2-Regression/README.md) | Anza na Python na Scikit-learn kwa mifano ya urekebishaji | [Python](2-Regression/1-Tools/README.md) • [R](../../2-Regression/1-Tools/solution/R/lesson_1.html) | Jen • Eric Wanjau | | 06 | Bei za malenge ya Amerika Kaskazini 🎃 | [Urekebishaji](2-Regression/README.md) | Onyesha na safisha data kwa ajili ya ML | [Python](2-Regression/2-Data/README.md) • [R](../../2-Regression/2-Data/solution/R/lesson_2.html) | Jen • Eric Wanjau | | 07 | Bei za malenge ya Amerika Kaskazini 🎃 | [Urekebishaji](2-Regression/README.md) | Jenga mifano ya urekebishaji wa mstari na polynomial | [Python](2-Regression/3-Linear/README.md) • [R](../../2-Regression/3-Linear/solution/R/lesson_3.html) | Jen na Dmitry • Eric Wanjau | | 08 | Bei za malenge ya Amerika Kaskazini 🎃 | [Urekebishaji](2-Regression/README.md) | Jenga mfano wa urekebishaji wa logistic | [Python](2-Regression/4-Logistic/README.md) • [R](../../2-Regression/4-Logistic/solution/R/lesson_4.html) | Jen • Eric Wanjau | | 09 | Programu ya Mtandao 🔌 | [Programu ya Mtandao](3-Web-App/README.md) | Jenga programu ya mtandao kutumia mfano uliyofundishwa | [Python](3-Web-App/1-Web-App/README.md) | Jen | | 10 | Utangulizi wa upangaji wa makundi | [Upangaji wa Makundi](4-Classification/README.md) | Safisha, andaa, na onyesha data yako; utangulizi wa upangaji wa makundi | [Python](4-Classification/1-Introduction/README.md) • [R](../../4-Classification/1-Introduction/solution/R/lesson_10.html) | Jen na Cassie • Eric Wanjau | | 11 | Ladha tamu za Asia na India 🍜 | [Upangaji wa Makundi](4-Classification/README.md) | Utangulizi wa wapangaji wa makundi | [Python](4-Classification/2-Classifiers-1/README.md) • [R](../../4-Classification/2-Classifiers-1/solution/R/lesson_11.html) | Jen na Cassie • Eric Wanjau | | 12 | Ladha tamu za Asia na India 🍜 | [Upangaji wa Makundi](4-Classification/README.md) | Wapangaji wa makundi zaidi | [Python](4-Classification/3-Classifiers-2/README.md) • [R](../../4-Classification/3-Classifiers-2/solution/R/lesson_12.html) | Jen na Cassie • Eric Wanjau | | 13 | Ladha tamu za Asia na India 🍜 | [Upangaji wa Makundi](4-Classification/README.md) | Jenga programu ya mtandao ya kupendekeza kwa kutumia mfano wako | [Python](4-Classification/4-Applied/README.md) | Jen | | 14 | Utangulizi wa ugawaji kundi | [Ugawaji Kundi](5-Clustering/README.md) | Safisha, andaa, na onyesha data yako; utangulizi wa ugawaji kundi | [Python](5-Clustering/1-Visualize/README.md) • [R](../../5-Clustering/1-Visualize/solution/R/lesson_14.html) | Jen • Eric Wanjau | | 15 | Kuchunguza Ladha za Muziki za Nigeria 🎧 | [Ugawaji Kundi](5-Clustering/README.md) | Chunguza mbinu ya ugawaji kundi wa K-Means | [Python](5-Clustering/2-K-Means/README.md) • [R](../../5-Clustering/2-K-Means/solution/R/lesson_15.html) | Jen • Eric Wanjau | | 16 | Utangulizi wa usindikaji wa lugha asilia ☕️ | [Usindikaji wa Lugha Asilia](6-NLP/README.md) | Jifunze misingi ya NLP kwa kujenga bot rahisi | [Python](6-NLP/1-Introduction-to-NLP/README.md) | Stephen | | 17 | Kazi za kawaida za NLP ☕️ | [Usindikaji wa Lugha Asilia](6-NLP/README.md) | Zidisha ujuzi wako wa NLP kwa kuelewa kazi za kawaida zinazohitajika wakati wa kushughulika na miundo ya lugha | [Python](6-NLP/2-Tasks/README.md) | Stephen | | 18 | Tafsiri na uchambuzi wa hisia ♥️ | [Usindikaji wa Lugha Asilia](6-NLP/README.md) | Tafsiri na uchambuzi wa hisia na Jane Austen | [Python](6-NLP/3-Translation-Sentiment/README.md) | Stephen | | 19 | Hoteli za kimapenzi za Ulaya ♥️ | [Usindikaji wa Lugha Asilia](6-NLP/README.md) | Uchambuzi wa hisia kwa mapitio ya hoteli 1 | [Python](6-NLP/4-Hotel-Reviews-1/README.md) | Stephen | | 20 | Hoteli za kimapenzi za Ulaya ♥️ | [Usindikaji wa Lugha Asilia](6-NLP/README.md) | Uchambuzi wa hisia kwa mapitio ya hoteli 2 | [Python](6-NLP/5-Hotel-Reviews-2/README.md) | Stephen | | 21 | Utangulizi wa utabiri wa mfululizo wa wakati | [Mfululizo wa Wakati](7-TimeSeries/README.md) | Utangulizi wa utabiri wa mfululizo wa wakati | [Python](7-TimeSeries/1-Introduction/README.md) | Francesca | | 22 | ⚡️ Matumizi ya Nguvu Duniani ⚡️ - utabiri wa mfululizo wa wakati na ARIMA | [Mfululizo wa Wakati](7-TimeSeries/README.md) | Utabiri wa mfululizo wa wakati kwa kutumia ARIMA | [Python](7-TimeSeries/2-ARIMA/README.md) | Francesca | | 23 | ⚡️ Matumizi ya Nguvu Duniani ⚡️ - utabiri wa mfululizo wa wakati na SVR | [Mfululizo wa Wakati](7-TimeSeries/README.md) | Utabiri wa mfululizo wa wakati kwa kutumia Support Vector Regressor | [Python](7-TimeSeries/3-SVR/README.md) | Anirban | | 24 | Utangulizi wa ujifunzaji wa kuimarisha | [Ujifunzaji wa Kuimarisha](8-Reinforcement/README.md) | Utangulizi wa ujifunzaji wa kuimarisha kwa kutumia Q-Learning | [Python](8-Reinforcement/1-QLearning/README.md) | Dmitry | | 25 | Msaada kwa Peter kuepuka mbwa mwitu! 🐺 | [Ujifunzaji wa Kuimarisha](8-Reinforcement/README.md) | Gym ya ujifunzaji wa kuimarisha | [Python](8-Reinforcement/2-Gym/README.md) | Dmitry | | Postscript | Hali halisi za ML na matumizi yake | [ML porini](9-Real-World/README.md) | Matumizi yenye kuvutia na kufunua ya ML ya kihistoria | [Somo](9-Real-World/1-Applications/README.md) | Timu | | Postscript | Urekebishaji wa Mfano katika ML kwa kutumia dashibodi ya RAI | [ML porini](9-Real-World/README.md) | Urekebishaji wa Mfano katika Ujifunzaji wa Mashine kwa kutumia vipengele vya dashibodi ya Responsible AI | [Somo](9-Real-World/2-Debugging-ML-Models/README.md) | Ruth Yakubu | > [pata rasilimali zote za ziada kwa kozi hii katika mkusanyiko wetu wa Microsoft Learn](https://learn.microsoft.com/en-us/collections/qrqzamz1nn2wx3?WT.mc_id=academic-77952-bethanycheum) ## Upatikanaji wa nje ya mtandao Unaweza kuendesha hati hii nje ya mtandao kwa kutumia [Docsify](https://docsify.js.org/#/). Toa nakala ya repo hii, [weka Docsify](https://docsify.js.org/#/quickstart) kwenye mashine yako ya ndani, kisha katika folda ya mzizi ya repo hii, andika `docsify serve`. Tovuti itakuwa inatolewa kwenye bandari 3000 kabisa akaunti yako ya localhost: `localhost:3000`. ## PDF Pata pdf ya mtaala yenye viungo [hapa](https://microsoft.github.io/ML-For-Beginners/pdf/readme.pdf). ## 🎒 Kozi Nyingine Timu yetu hutengeneza kozi nyingine! Angalia: ### LangChain [![LangChain4j for Beginners](https://img.shields.io/badge/LangChain4j%20for%20Beginners-22C55E?style=for-the-badge&&labelColor=E5E7EB&color=0553D6)](https://aka.ms/langchain4j-for-beginners) [![LangChain.js for Beginners](https://img.shields.io/badge/LangChain.js%20for%20Beginners-22C55E?style=for-the-badge&labelColor=E5E7EB&color=0553D6)](https://aka.ms/langchainjs-for-beginners?WT.mc_id=m365-94501-dwahlin) [![LangChain for Beginners](https://img.shields.io/badge/LangChain%20for%20Beginners-22C55E?style=for-the-badge&labelColor=E5E7EB&color=0553D6)](https://github.com/microsoft/langchain-for-beginners?WT.mc_id=m365-94501-dwahlin) --- ### Azure / Edge / MCP / Agents [![AZD for Beginners](https://img.shields.io/badge/AZD%20for%20Beginners-0078D4?style=for-the-badge&labelColor=E5E7EB&color=0078D4)](https://github.com/microsoft/AZD-for-beginners?WT.mc_id=academic-105485-koreyst) [![Edge AI for Beginners](https://img.shields.io/badge/Edge%20AI%20for%20Beginners-00B8E4?style=for-the-badge&labelColor=E5E7EB&color=00B8E4)](https://github.com/microsoft/edgeai-for-beginners?WT.mc_id=academic-105485-koreyst) [![MCP for Beginners](https://img.shields.io/badge/MCP%20for%20Beginners-009688?style=for-the-badge&labelColor=E5E7EB&color=009688)](https://github.com/microsoft/mcp-for-beginners?WT.mc_id=academic-105485-koreyst) [![AI Agents for Beginners](https://img.shields.io/badge/AI%20Agents%20for%20Beginners-00C49A?style=for-the-badge&labelColor=E5E7EB&color=00C49A)](https://github.com/microsoft/ai-agents-for-beginners?WT.mc_id=academic-105485-koreyst) --- ### Mfululizo wa AI ya Kizazi [![Generative AI kwa Waanzilishi](https://img.shields.io/badge/Generative%20AI%20for%20Beginners-8B5CF6?style=for-the-badge&labelColor=E5E7EB&color=8B5CF6)](https://github.com/microsoft/generative-ai-for-beginners?WT.mc_id=academic-105485-koreyst) [![Generative AI (.NET)](https://img.shields.io/badge/Generative%20AI%20(.NET)-9333EA?style=for-the-badge&labelColor=E5E7EB&color=9333EA)](https://github.com/microsoft/Generative-AI-for-beginners-dotnet?WT.mc_id=academic-105485-koreyst) [![Generative AI (Java)](https://img.shields.io/badge/Generative%20AI%20(Java)-C084FC?style=for-the-badge&labelColor=E5E7EB&color=C084FC)](https://github.com/microsoft/generative-ai-for-beginners-java?WT.mc_id=academic-105485-koreyst) [![Generative AI (JavaScript)](https://img.shields.io/badge/Generative%20AI%20(JavaScript)-E879F9?style=for-the-badge&labelColor=E5E7EB&color=E879F9)](https://github.com/microsoft/generative-ai-with-javascript?WT.mc_id=academic-105485-koreyst) --- ### Kujifunza Msingi [![ML kwa Waanzilishi](https://img.shields.io/badge/ML%20for%20Beginners-22C55E?style=for-the-badge&labelColor=E5E7EB&color=22C55E)](https://aka.ms/ml-beginners?WT.mc_id=academic-105485-koreyst) [![Sayansi ya Data kwa Waanzilishi](https://img.shields.io/badge/Data%20Science%20for%20Beginners-84CC16?style=for-the-badge&labelColor=E5E7EB&color=84CC16)](https://aka.ms/datascience-beginners?WT.mc_id=academic-105485-koreyst) [![AI kwa Waanzilishi](https://img.shields.io/badge/AI%20for%20Beginners-A3E635?style=for-the-badge&labelColor=E5E7EB&color=A3E635)](https://aka.ms/ai-beginners?WT.mc_id=academic-105485-koreyst) [![Usalama wa Mtandao kwa Waanzilishi](https://img.shields.io/badge/Cybersecurity%20for%20Beginners-F97316?style=for-the-badge&labelColor=E5E7EB&color=F97316)](https://github.com/microsoft/Security-101?WT.mc_id=academic-96948-sayoung) [![Maendeleo ya Wavuti kwa Waanzilishi](https://img.shields.io/badge/Web%20Dev%20for%20Beginners-EC4899?style=for-the-badge&labelColor=E5E7EB&color=EC4899)](https://aka.ms/webdev-beginners?WT.mc_id=academic-105485-koreyst) [![IoT kwa Waanzilishi](https://img.shields.io/badge/IoT%20for%20Beginners-14B8A6?style=for-the-badge&labelColor=E5E7EB&color=14B8A6)](https://aka.ms/iot-beginners?WT.mc_id=academic-105485-koreyst) [![Maendeleo ya XR kwa Waanzilishi](https://img.shields.io/badge/XR%20Development%20for%20Beginners-38BDF8?style=for-the-badge&labelColor=E5E7EB&color=38BDF8)](https://github.com/microsoft/xr-development-for-beginners?WT.mc_id=academic-105485-koreyst) --- ### Mfululizo wa Copilot [![Copilot kwa Uandishi wa Pamoja wa AI](https://img.shields.io/badge/Copilot%20for%20AI%20Paired%20Programming-FACC15?style=for-the-badge&labelColor=E5E7EB&color=FACC15)](https://aka.ms/GitHubCopilotAI?WT.mc_id=academic-105485-koreyst) [![Copilot kwa C#/.NET](https://img.shields.io/badge/Copilot%20for%20C%23/.NET-FBBF24?style=for-the-badge&labelColor=E5E7EB&color=FBBF24)](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers?WT.mc_id=academic-105485-koreyst) [![Adventure ya Copilot](https://img.shields.io/badge/Copilot%20Adventure-FDE68A?style=for-the-badge&labelColor=E5E7EB&color=FDE68A)](https://github.com/microsoft/CopilotAdventures?WT.mc_id=academic-105485-koreyst) ## Kupata Msaada Ikiwa unakwama au una maswali yoyote kuhusu kujenga programu za AI. Jiunge na wanafunzi wenzako na waendelezaji wenye uzoefu katika mijadala kuhusu MCP. Ni jamii yenye msaada ambapo maswali yanakaribishwa na maarifa hushirikiana kwa uhuru. [![Microsoft Foundry Discord](https://dcbadge.limes.pink/api/server/nTYy5BXMWG)](https://discord.gg/nTYy5BXMWG) Ikiwa una maoni kuhusu bidhaa au makosa wakati wa kujenga tembelea: [![Microsoft Foundry Developer Forum](https://img.shields.io/badge/GitHub-Microsoft_Foundry_Developer_Forum-blue?style=for-the-badge&logo=github&color=000000&logoColor=fff)](https://aka.ms/foundry/forum) --- **Tangazo la Kutojihusisha**: Nyaraka hii imetatuliwa kwa kutumia huduma ya kutafsiri kwa AI [Co-op Translator](https://github.com/Azure/co-op-translator). Ingawa tunajitahidi kupata usahihi, tafadhali fahamu kwamba tafsiri za kiotomatiki zinaweza kuwa na makosa au upungufu wa usahihi. Nyaraka asilia katika lugha yake ya asili inapaswa kuchukuliwa kama chanzo cha mamlaka. Kwa taarifa muhimu, tafsiri ya kitaalamu ya binadamu inapendekezwa. Hatubeba dhamana kwa maana potofu au tafsiri zisizo sahihi zinazotokana na matumizi ya tafsiri hii.