From a289e7de552db90fda48fab5f3717c46f4513c8e Mon Sep 17 00:00:00 2001 From: JooHyun Date: Sat, 23 Dec 2023 13:50:53 +0900 Subject: [PATCH 1/6] start translate --- translations/README.ko.md | 203 ++++++++++++++++++++++++++++++++++++++ 1 file changed, 203 insertions(+) create mode 100644 translations/README.ko.md diff --git a/translations/README.ko.md b/translations/README.ko.md new file mode 100644 index 00000000..783011ab --- /dev/null +++ b/translations/README.ko.md @@ -0,0 +1,203 @@ +[![GitHub license](https://img.shields.io/github/license/microsoft/AI-For-Beginners.svg)](https://github.com/microsoft/AI-For-Beginners/blob/main/LICENSE) +[![GitHub contributors](https://img.shields.io/github/contributors/microsoft/AI-For-Beginners.svg)](https://GitHub.com/microsoft/AI-For-Beginners/graphs/contributors/) +[![GitHub issues](https://img.shields.io/github/issues/microsoft/AI-For-Beginners.svg)](https://GitHub.com/microsoft/AI-For-Beginners/issues/) +[![GitHub pull-requests](https://img.shields.io/github/issues-pr/microsoft/AI-For-Beginners.svg)](https://GitHub.com/microsoft/AI-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/AI-For-Beginners.svg?style=social&label=Watch)](https://GitHub.com/microsoft/AI-For-Beginners/watchers/) +[![GitHub forks](https://img.shields.io/github/forks/microsoft/AI-For-Beginners.svg?style=social&label=Fork)](https://GitHub.com/microsoft/AI-For-Beginners/network/) +[![GitHub stars](https://img.shields.io/github/stars/microsoft/AI-For-Beginners.svg?style=social&label=Star)](https://GitHub.com/microsoft/AI-For-Beginners/stargazers/) +[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/microsoft/ai-for-beginners/HEAD) +[![Gitter](https://badges.gitter.im/Microsoft/ai-for-beginners.svg)](https://gitter.im/Microsoft/ai-for-beginners?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge) + + +# 초보자를 위한 인공지능 - 교육과정 + +|![ Sketchnote by [(@girlie_mac)](https://twitter.com/girlie_mac) ](./lessons/sketchnotes/ai-overview.png)| +|:---:| +| AI For Beginners - _Sketchnote by [@girlie_mac](https://twitter.com/girlie_mac)_ | + + +마이크로 소프트와 함께 12주, 24개의 강의를 통해 **인공지능**의 세계를 탐험하세요! 심볼릭(Symbolic) AI, 인공신경망, 컴퓨터비전, 자연어처리 등을 탐구하세요. 실습형 강의와 퀴즈, 자유로운 실험을 통해 학습하세요. 본 과정은 텐서플로우, 파이토치, AI윤리를 기반으로 초보자에게 적합하게 고안되었습니다. 인공지능으로의 여행을 시작하세요! + + +이 과정에서 배울 것은 아래와 같습니다: + + +* **지식 표현**과 추론처럼 "좋지만 오래된" 기호주의적 접근 등의 다양한 인공지능을 해석하는 관점. +* 근대 AI의 핵심인 **인공신경망**과 **심층신경망**. 가장 유명한 프레임워크인 [텐서플로우](http://Tensorflow.org)와 [파이토치](http://pytorch.org)를 사용하여 두 주제에 대한 개념을 코드로 이해할 것입니다. +* 사진과 글자에 사용되는 **신경망 구조**. 오래되지 않은 모델을 배울것이지만 완전 최신이라고 하기엔 부족할 수도 있습니다. +* **유전 알고리즘**과 **다중 에이전트 시스템**같은 덜 유명한 AI기법. + +What we will not cover in this curriculum: + +* Business cases of using **AI in Business**. Consider taking [Introduction to AI for business users](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-cacaste) learning path on Microsoft Learn, or [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-cacaste), developed in cooperation with [INSEAD](https://www.insead.edu/). +* **Classic Machine Learning**, which is well described in our [Machine Learning for Beginners Curriculum](http://github.com/Microsoft/ML-for-Beginners). +* Practical AI applications built using **[Cognitive Services](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-cacaste)**. For this, we recommend that you start with modules Microsoft Learn for [vision](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-cacaste), [natural language processing](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-cacaste), **[Generative AI with Azure OpenAI Service](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** and others. +* Specific ML **Cloud Frameworks**, such as [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-cacaste), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum), or [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-cacaste). Consider using [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-cacaste) and [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-cacaste) learning paths. +* **Conversational AI** and **Chat Bots**. There is a separate [Create conversational AI solutions](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-cacaste) learning path, and you can also refer to [this blog post](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) for more detail. +* **Deep Mathematics** behind deep learning. For this, we would recommend [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) by Ian Goodfellow, Yoshua Bengio and Aaron Courville, which is also available online at [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/). + +For a gentle introduction to *AI in the Cloud* topics you may consider taking the [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-cacaste) Learning Path. + + +## Announcement - New Curriculum on Generative AI was just released! + +We just released a 12 lesson curriculum on generative AI. Come learn things like: + +- prompting and prompt engineering +- text and image app generation +- search apps + +As usual, there's a lesson, assignments to complete, knowledge checks and challenges. + +Check it out: + +> https://aka.ms/genai-beginners + +--- +# Content + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NoLessonIntroPyTorchKeras/TensorFlowLab
IIntroduction to AI
1Introduction and History of AIText
IISymbolic AI
2 Knowledge Representation and Expert SystemsTextExpert System, Ontology, Concept Graph
IIIIntroduction to Neural Networks
3PerceptronText + NotebookLab
4 Multi-Layered Perceptron and Creating our own FrameworkTextNotebookLab
5Intro to Frameworks (PyTorch/TensorFlow) and OverfittingTextPyTorchKeras/TensorFlowLab
IVComputer VisionMicrosoft Azure AI Fundamentals: Explore Computer Vision
Microsoft Learn Module on Computer VisionPyTorchTensorFlow
6Intro to Computer Vision. OpenCVTextNotebookLab
7Convolutional Neural Networks
CNN Architectures		Text
Text		PyTorchTensorFlowLab
8Pre-trained Networks and Transfer Learning
Training Tricks		Text
Text		PyTorchTensorFlow
Dropout sample
Adversarial Cat		Lab
9Autoencoders and VAEsTextPyTorchTensorFlow
10Generative Adversarial Networks
Artistic Style Transfer		TextPyTorchTensorFlow GAN
Style Transfer
11Object DetectionTextPyTorchTensorFlowLab
12Semantic Segmentation. U-NetTextPyTorchTensorFlow
VNatural Language ProcessingMicrosoft Azure AI Fundamentals: Explore Natural Language Processing
Microsoft Learn Module on Natural language processingPyTorchTensorFlow
13Text Representation. Bow/TF-IDFTextPyTorchTensorFlow
14Semantic word embeddings. Word2Vec and GloVeTextPyTorchTensorFlow
15Language Modeling. Training your own embeddingsTextPyTorchTensorFlowLab
16Recurrent Neural NetworksTextPyTorchTensorFlow
17Generative Recurrent NetworksTextPyTorchTensorFlowLab
18Transformers. BERT.TextPyTorchTensorFlow
19Named Entity RecognitionTextTensorFlowLab
20Large Language Models, Prompt Programming and Few-Shot TasksTextPyTorch
VIOther AI Techniques
21Genetic AlgorithmsTextNotebook
22Deep Reinforcement LearningTextPyTorchTensorFlowLab
23Multi-Agent SystemsText
VIIAI Ethics
24AI Ethics and Responsible AITextMS Learn: Responsible AI Principles
Extras
X1Multi-Modal Networks, CLIP and VQGANTextNotebook
+ +**[Mindmap of the Course](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)** + +Each lesson contains some pre-reading material (linked as **Text** above), and some executable Jupyter Notebooks, which are often specific to the framework (**PyTorch** or **TensorFlow**). The executable notebook also contains a lot of theoretical material, so to understand the topic you need to go through at least one version of the notebooks (either PyTorch or TensorFlow). There are also **Labs** available for some topics, which give you an opportunity to try applying the material you have learned to a specific problem. + +Some sections also contain links to **MS Learn** modules that cover related topics. Microsoft Learn provides a convenient GPU-enabled learning environment, although in terms of content you can expect this curriculum to go a bit deeper. + +# Are you a student? + +Get started with the following resources: + +- [Student Hub page](https://docs.microsoft.com/learn/student-hub?WT.mc_id=academic-77998-cacaste) In this page, you will find beginner resources, Student packs and even ways to get a free cert voucher. This is one page you want to bookmark and check from time to time as we switch out content at least monthly. +- [Microsoft Student Learn ambassadors](https://studentambassadors.microsoft.com?WT.mc_id=academic-77998-cacaste) Join a global community of student ambassadors, this could be your way into Microsoft. + +# Getting Started + +**Students**, there are a couple of ways to use the curriculum. First of all, you can just read the text and look through the code directly on GitHub. If you want to run the code in any of the notebook - [read our instructions](./etc/how-to-run.md), and find more advice on how to do it [in this blog post](https://soshnikov.com/education/how-to-execute-notebooks-from-github/). + +> **Note**: [Instructions on how to run the code in this curriculum](./etc/how-to-run.md) + +However, if you would like to take the course as a self-study project, we suggest that you fork the entire repo to your own GitHub account and complete the exercises on your own or with a group: + +- Start with a pre-lecture quiz. +- Read the intro text for the lecture. +- If the lecture has additional notebooks, go through them, reading and executing the code. If both TensorFlow and PyTorch notebooks are provided, you can focus on one of them - choose your favorite framework. +- Notebooks often contain some of the challenges that require you to tweak the code a little bit to experiment. +- Take the post-lecture quiz. +- If there is a lab attached to the module - complete the assignment. +- Visit the [Discussion board](https://github.com/microsoft/AI-For-Beginners/discussions) to "learn out loud". + + +> For further study, we recommend following these [Microsoft Learn](https://docs.microsoft.com/en-us/users/dmitrysoshnikov-9132/collections/31zgizg2p418yo/?WT.mc_id=academic-77998-cacaste) modules and learning paths. + +**Teachers**, we have [included some suggestions](/etc/for-teachers.md) on how to use this curriculum. + +--- + +## Credits + +**✍️ Primary Author:** [Dmitry Soshnikov](http://soshnikov.com), PhD
+**🔥 Editor:** [Jen Looper](https://twitter.com/jenlooper), PhD
+**🎨 Sketchnote illustrator:** [Tomomi Imura](https://twitter.com/girlie_mac)
+**✅ Quiz Creator:** [Lateefah Bello](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/)
+**🙏 Core Contributors:** [Evgenii Pishchik](https://github.com/Pe4enIks) + +## Meet the Team + +[![Promo video](/lessons/sketchnotes/ai-for-beginners.png)](https://youtu.be/m2KrAk0cC1c "Promo video") + +> 🎥 Click the image above for a video about the project and the folks who created it! + +--- + +## Pedagogy + +We have chosen two pedagogical tenets while building this curriculum: ensuring that it is hands-on **project-based** and that it includes **frequent quizzes**. + +By ensuring that the content aligns with projects, the process is made more engaging for students and retention of concepts will be augmented. In addition, a low-stakes quiz before a class sets the intention of the student towards learning a topic, while a second quiz after class ensures further retention. This curriculum was designed to be flexible and fun and can be taken in whole or in part. The projects start small and become increasingly complex by the end of the 12 week cycle. + +> Find our [Code of Conduct](etc/CODE_OF_CONDUCT.md), [Contributing](etc/CONTRIBUTING.md), and [Translation](etc/TRANSLATIONS.md) guidelines. Find our [Support Documentation here](etc/SUPPORT.md) and [security information here](etc/SECURITY.md). We welcome your constructive feedback! + +> **A note about quizzes**: All quizzes are contained [in this app](https://red-field-0a6ddfd03.1.azurestaticapps.net/), for 50 total quizzes of three questions each. They are linked from within the lessons but the quiz app can be run locally; follow the instruction in the `etc/quiz-app` folder. + +## Offline access + +You can run this documentation offline by using [Docsify](https://docsify.js.org/#/). Fork this repo, [install Docsify](https://docsify.js.org/#/quickstart) on your local machine, and then in the `etc/docsify` folder of this repo, type `docsify serve`. The website will be served on port 3000 on your localhost: `localhost:3000`. A pdf of the curriculum is available [at this link](/etc/pdf/readme.pdf). + +## Help Wanted! + +Would you like to contribute a translation? Please read our [translation guidelines](etc/TRANSLATIONS.md). + +## Other Curricula + +Our team produces other curricula! Check out: + +- [AI for Beginners](https://aka.ms/ai-beginners) +- [Data Science for Beginners](https://aka.ms/datascience-beginners) +- [Generative AI for Beginners](https://aka.ms/genai-beginners) +- [Web Dev for Beginners](https://aka.ms/webdev-beginners) +- [IoT for Beginners](https://aka.ms/iot-beginners) +- [Machine Learning for Beginners](https://aka.ms/ml-beginners) +- [XR Development for Beginners](https://aka.ms/xr-dev-for-beginners) +- [Mastering GitHub Copilot for AI Paired Programming](https://aka.ms/GitHubCopilotAI) From 7a90fe77a0843fc33c2da627544ce369289538e4 Mon Sep 17 00:00:00 2001 From: JooHyun Date: Wed, 27 Dec 2023 13:33:04 +0900 Subject: [PATCH 2/6] 12-27 tlanslate --- translations/README.ko.md | 17 ++++++++++++++--- 1 file changed, 14 insertions(+), 3 deletions(-) diff --git a/translations/README.ko.md b/translations/README.ko.md index 783011ab..3e9dac85 100644 --- a/translations/README.ko.md +++ b/translations/README.ko.md @@ -32,16 +32,27 @@ * 사진과 글자에 사용되는 **신경망 구조**. 오래되지 않은 모델을 배울것이지만 완전 최신이라고 하기엔 부족할 수도 있습니다. * **유전 알고리즘**과 **다중 에이전트 시스템**같은 덜 유명한 AI기법. -What we will not cover in this curriculum: + +아래와 같은 주제는 본 과정에서 다루지 않습니다: -* Business cases of using **AI in Business**. Consider taking [Introduction to AI for business users](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-cacaste) learning path on Microsoft Learn, or [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-cacaste), developed in cooperation with [INSEAD](https://www.insead.edu/). + + + +* 기업에서의 **AI 활용사례**. MS Learn의 [기업 사용자를 위한 AI 소개](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-cacaste)나, 세계 최고의 경영대학 중 하나인 [INSEAD](https://www.insead.edu/)와 협력하여 만든 [Microsoft AI를 통한 비즈니스 혁신](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-cacaste) 학습경로를 참고하세요. +* **기계학습**, 이를 위한 교육과정은 따로 준비되어있습니다 [초보자를 위한 기계학습](http://github.com/Microsoft/ML-for-Beginners). +* **애저 AI 서비스**를 사용한 AI 구축. [컴퓨터 비전](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-cacaste), [자연어 처리](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-cacaste), **[애저 오픈AI를 사용한 생성형 AI](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** 등과 같은 MS Learn을 통해 학습하세요. +* [애저 기계학습](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-cacaste), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum), or [애저 Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-cacaste)과 같은 특정 **클라우드 프레임워크**. [애저 기계 학습 작업 영역 살펴보기](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-cacaste) and [Azure Databricks를 사용한 기계 학습](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-cacaste) +* **대화형 AI**와 **챗봇**. MS Learn의 [대화형 AI 만들기](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-cacaste)를 학습하세요. 자세히 알고 싶다면 [블로그 글](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/)을 참고하세요 +* **AI 수학**. [심층학습](https://product.kyobobook.co.kr/detail/S000001916915)책을 추천합니다. + +*클라우드에서의 AI*에 가볍게 알고 싶다면 MS learn의 [Microsoft 애저 AI 기본 사항: AI 개요](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-cacaste) 학습경로를 들어보세요. ## Announcement - New Curriculum on Generative AI was just released! From a0a88a660d1d9f1313cb14a1567c533e0be74e2b Mon Sep 17 00:00:00 2001 From: JooHyun Date: Wed, 27 Dec 2023 14:10:32 +0900 Subject: [PATCH 3/6] update image link --- translations/README.ko.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/translations/README.ko.md b/translations/README.ko.md index 3e9dac85..ee524932 100644 --- a/translations/README.ko.md +++ b/translations/README.ko.md @@ -13,7 +13,7 @@ # 초보자를 위한 인공지능 - 교육과정 -|![ Sketchnote by [(@girlie_mac)](https://twitter.com/girlie_mac) ](./lessons/sketchnotes/ai-overview.png)| +|![ Sketchnote by [(@girlie_mac)](https://twitter.com/girlie_mac) ](/lessons/sketchnotes/ai-overview.png)| |:---:| | AI For Beginners - _Sketchnote by [@girlie_mac](https://twitter.com/girlie_mac)_ | From c4bdaf08369f03ded2f39f1b2080da513342dd11 Mon Sep 17 00:00:00 2001 From: JooHyun Date: Wed, 27 Dec 2023 14:11:27 +0900 Subject: [PATCH 4/6] Revert "12-27 tlanslate" This reverts commit 7a90fe77a0843fc33c2da627544ce369289538e4. --- translations/README.ko.md | 17 +++-------------- 1 file changed, 3 insertions(+), 14 deletions(-) diff --git a/translations/README.ko.md b/translations/README.ko.md index ee524932..e7f16ee7 100644 --- a/translations/README.ko.md +++ b/translations/README.ko.md @@ -32,27 +32,16 @@ * 사진과 글자에 사용되는 **신경망 구조**. 오래되지 않은 모델을 배울것이지만 완전 최신이라고 하기엔 부족할 수도 있습니다. * **유전 알고리즘**과 **다중 에이전트 시스템**같은 덜 유명한 AI기법. - -아래와 같은 주제는 본 과정에서 다루지 않습니다: +What we will not cover in this curriculum: - - - -* 기업에서의 **AI 활용사례**. MS Learn의 [기업 사용자를 위한 AI 소개](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-cacaste)나, 세계 최고의 경영대학 중 하나인 [INSEAD](https://www.insead.edu/)와 협력하여 만든 [Microsoft AI를 통한 비즈니스 혁신](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-cacaste) 학습경로를 참고하세요. -* **기계학습**, 이를 위한 교육과정은 따로 준비되어있습니다 [초보자를 위한 기계학습](http://github.com/Microsoft/ML-for-Beginners). -* **애저 AI 서비스**를 사용한 AI 구축. [컴퓨터 비전](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-cacaste), [자연어 처리](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-cacaste), **[애저 오픈AI를 사용한 생성형 AI](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** 등과 같은 MS Learn을 통해 학습하세요. -* [애저 기계학습](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-cacaste), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum), or [애저 Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-cacaste)과 같은 특정 **클라우드 프레임워크**. [애저 기계 학습 작업 영역 살펴보기](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-cacaste) and [Azure Databricks를 사용한 기계 학습](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-cacaste) -* **대화형 AI**와 **챗봇**. MS Learn의 [대화형 AI 만들기](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-cacaste)를 학습하세요. 자세히 알고 싶다면 [블로그 글](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/)을 참고하세요 -* **AI 수학**. [심층학습](https://product.kyobobook.co.kr/detail/S000001916915)책을 추천합니다. - -*클라우드에서의 AI*에 가볍게 알고 싶다면 MS learn의 [Microsoft 애저 AI 기본 사항: AI 개요](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-cacaste) 학습경로를 들어보세요. +For a gentle introduction to *AI in the Cloud* topics you may consider taking the [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-cacaste) Learning Path. ## Announcement - New Curriculum on Generative AI was just released! From 73fbc6a0343516f9a6d52c1634bab9ed04f5fad9 Mon Sep 17 00:00:00 2001 From: JooHyun Date: Wed, 27 Dec 2023 14:23:16 +0900 Subject: [PATCH 5/6] update readme.ko --- translations/README.ko.md | 24 ++++++++---------------- 1 file changed, 8 insertions(+), 16 deletions(-) diff --git a/translations/README.ko.md b/translations/README.ko.md index e7f16ee7..acc0920f 100644 --- a/translations/README.ko.md +++ b/translations/README.ko.md @@ -10,39 +10,31 @@ [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/microsoft/ai-for-beginners/HEAD) [![Gitter](https://badges.gitter.im/Microsoft/ai-for-beginners.svg)](https://gitter.im/Microsoft/ai-for-beginners?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge) - # 초보자를 위한 인공지능 - 교육과정 |![ Sketchnote by [(@girlie_mac)](https://twitter.com/girlie_mac) ](/lessons/sketchnotes/ai-overview.png)| |:---:| | AI For Beginners - _Sketchnote by [@girlie_mac](https://twitter.com/girlie_mac)_ | - 마이크로 소프트와 함께 12주, 24개의 강의를 통해 **인공지능**의 세계를 탐험하세요! 심볼릭(Symbolic) AI, 인공신경망, 컴퓨터비전, 자연어처리 등을 탐구하세요. 실습형 강의와 퀴즈, 자유로운 실험을 통해 학습하세요. 본 과정은 텐서플로우, 파이토치, AI윤리를 기반으로 초보자에게 적합하게 고안되었습니다. 인공지능으로의 여행을 시작하세요! - 이 과정에서 배울 것은 아래와 같습니다: - * **지식 표현**과 추론처럼 "좋지만 오래된" 기호주의적 접근 등의 다양한 인공지능을 해석하는 관점. * 근대 AI의 핵심인 **인공신경망**과 **심층신경망**. 가장 유명한 프레임워크인 [텐서플로우](http://Tensorflow.org)와 [파이토치](http://pytorch.org)를 사용하여 두 주제에 대한 개념을 코드로 이해할 것입니다. * 사진과 글자에 사용되는 **신경망 구조**. 오래되지 않은 모델을 배울것이지만 완전 최신이라고 하기엔 부족할 수도 있습니다. * **유전 알고리즘**과 **다중 에이전트 시스템**같은 덜 유명한 AI기법. -What we will not cover in this curriculum: +아래와 같은 주제는 본 과정에서 다루지 않습니다: -* Business cases of using **AI in Business**. Consider taking [Introduction to AI for business users](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-cacaste) learning path on Microsoft Learn, or [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-cacaste), developed in cooperation with [INSEAD](https://www.insead.edu/). -* **Classic Machine Learning**, which is well described in our [Machine Learning for Beginners Curriculum](http://github.com/Microsoft/ML-for-Beginners). -* Practical AI applications built using **[Cognitive Services](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-cacaste)**. For this, we recommend that you start with modules Microsoft Learn for [vision](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-cacaste), [natural language processing](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-cacaste), **[Generative AI with Azure OpenAI Service](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** and others. -* Specific ML **Cloud Frameworks**, such as [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-cacaste), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum), or [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-cacaste). Consider using [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-cacaste) and [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-cacaste) learning paths. -* **Conversational AI** and **Chat Bots**. There is a separate [Create conversational AI solutions](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-cacaste) learning path, and you can also refer to [this blog post](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) for more detail. -* **Deep Mathematics** behind deep learning. For this, we would recommend [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) by Ian Goodfellow, Yoshua Bengio and Aaron Courville, which is also available online at [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/). - -For a gentle introduction to *AI in the Cloud* topics you may consider taking the [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-cacaste) Learning Path. +* 기업에서의 **AI 활용사례**. MS Learn의 [기업 사용자를 위한 AI 소개](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-cacaste)나, 세계 최고의 경영대학 중 하나인 [INSEAD](https://www.insead.edu/)와 협력하여 만든 [Microsoft AI를 통한 비즈니스 혁신](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-cacaste) 학습경로를 참고하세요. +* **기계학습**, 이를 위한 교육과정은 [초보자를 위한 기계학습](http://github.com/Microsoft/ML-for-Beginners)에 따로 준비되어있습니다. +* **애저 AI 서비스**를 사용한 AI 구축. [컴퓨터 비전](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-cacaste), [자연어 처리](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-cacaste), **[애저 오픈AI를 사용한 생성형 AI](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** 등과 같은 학습경로를 참고하세요. +* [애저 기계학습](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-cacaste), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum), or [애저 Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-cacaste)과 같은 특정 **클라우드 프레임워크**. [애저 기계 학습 작업 영역 살펴보기](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-cacaste)와 [Azure Databricks를 사용한 기계 학습](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-cacaste) 학습경로를 참고하세요. +* **대화형 AI**와 **챗봇**. MS Learn의 [대화형 AI 만들기](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-cacaste) 학습경로를 참고하세요. 자세히 알고 싶다면 [이 블로그 글](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/)을 참고하세요. +* **AI 수학**. [심층학습](https://product.kyobobook.co.kr/detail/S000001916915) 책을 추천합니다. +*클라우드에서의 AI*에 간단히 알고 싶다면 [Microsoft 애저 AI 기본 사항: AI 개요](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-cacaste) 학습경로를 참고하세요. ## Announcement - New Curriculum on Generative AI was just released! From 6371cd54996c4748e9b45108d86cc87b60a34d32 Mon Sep 17 00:00:00 2001 From: JooHyun Date: Mon, 8 Jan 2024 13:12:23 +0900 Subject: [PATCH 6/6] complete translate to korean --- translations/README.ko.md | 187 +++++++++++++++++++------------------- 1 file changed, 93 insertions(+), 94 deletions(-) diff --git a/translations/README.ko.md b/translations/README.ko.md index acc0920f..860a86ba 100644 --- a/translations/README.ko.md +++ b/translations/README.ko.md @@ -10,25 +10,25 @@ [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/microsoft/ai-for-beginners/HEAD) [![Gitter](https://badges.gitter.im/Microsoft/ai-for-beginners.svg)](https://gitter.im/Microsoft/ai-for-beginners?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge) -# 초보자를 위한 인공지능 - 교육과정 +# 초보자를 위한 인공지능 |![ Sketchnote by [(@girlie_mac)](https://twitter.com/girlie_mac) ](/lessons/sketchnotes/ai-overview.png)| |:---:| | AI For Beginners - _Sketchnote by [@girlie_mac](https://twitter.com/girlie_mac)_ | -마이크로 소프트와 함께 12주, 24개의 강의를 통해 **인공지능**의 세계를 탐험하세요! 심볼릭(Symbolic) AI, 인공신경망, 컴퓨터비전, 자연어처리 등을 탐구하세요. 실습형 강의와 퀴즈, 자유로운 실험을 통해 학습하세요. 본 과정은 텐서플로우, 파이토치, AI윤리를 기반으로 초보자에게 적합하게 고안되었습니다. 인공지능으로의 여행을 시작하세요! - +마이크로 소프트와 함께 12주, 24개의 강의를 통해 **인공지능**의 세계를 탐험하세요! 기호주의(Symbolic) AI, 인공신경망, 컴퓨터비전, 자연어처리 등을 탐구하세요. 실습형 강의와 퀴즈, 자유로운 실험을 통해 학습하세요. 본 과정은 텐서플로우, 파이토치, AI윤리를 기반으로 초보자에게 적합하게 고안되었습니다. 인공지능으로의 여행을 시작하세요! +심볼 이 과정에서 배울 것은 아래와 같습니다: * **지식 표현**과 추론처럼 "좋지만 오래된" 기호주의적 접근 등의 다양한 인공지능을 해석하는 관점. -* 근대 AI의 핵심인 **인공신경망**과 **심층신경망**. 가장 유명한 프레임워크인 [텐서플로우](http://Tensorflow.org)와 [파이토치](http://pytorch.org)를 사용하여 두 주제에 대한 개념을 코드로 이해할 것입니다. +* 근대 AI의 핵심인 **인공신경망**과 **심층신경망**. 가장 유명한 프레임워크인 [텐서플로우(Tensorflow)](http://Tensorflow.org)와 [파이토치(Pytorch)](http://pytorch.org)를 사용하여 두 주제에 대한 개념을 코드로 이해할 것입니다. * 사진과 글자에 사용되는 **신경망 구조**. 오래되지 않은 모델을 배울것이지만 완전 최신이라고 하기엔 부족할 수도 있습니다. * **유전 알고리즘**과 **다중 에이전트 시스템**같은 덜 유명한 AI기법. 아래와 같은 주제는 본 과정에서 다루지 않습니다: * 기업에서의 **AI 활용사례**. MS Learn의 [기업 사용자를 위한 AI 소개](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-cacaste)나, 세계 최고의 경영대학 중 하나인 [INSEAD](https://www.insead.edu/)와 협력하여 만든 [Microsoft AI를 통한 비즈니스 혁신](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-cacaste) 학습경로를 참고하세요. -* **기계학습**, 이를 위한 교육과정은 [초보자를 위한 기계학습](http://github.com/Microsoft/ML-for-Beginners)에 따로 준비되어있습니다. +* **기계학습**, 이를 위한 학습과정은 [초보자를 위한 기계학습](http://github.com/Microsoft/ML-for-Beginners)에 따로 준비되어있습니다. * **애저 AI 서비스**를 사용한 AI 구축. [컴퓨터 비전](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-cacaste), [자연어 처리](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-cacaste), **[애저 오픈AI를 사용한 생성형 AI](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** 등과 같은 학습경로를 참고하세요. * [애저 기계학습](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-cacaste), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum), or [애저 Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-cacaste)과 같은 특정 **클라우드 프레임워크**. [애저 기계 학습 작업 영역 살펴보기](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-cacaste)와 [Azure Databricks를 사용한 기계 학습](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-cacaste) 학습경로를 참고하세요. * **대화형 AI**와 **챗봇**. MS Learn의 [대화형 AI 만들기](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-cacaste) 학습경로를 참고하세요. 자세히 알고 싶다면 [이 블로그 글](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/)을 참고하세요. @@ -36,114 +36,113 @@ *클라우드에서의 AI*에 간단히 알고 싶다면 [Microsoft 애저 AI 기본 사항: AI 개요](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-cacaste) 학습경로를 참고하세요. -## Announcement - New Curriculum on Generative AI was just released! - -We just released a 12 lesson curriculum on generative AI. Come learn things like: +## 안내사항 - 생성형 AI에 대한 학습과정이 새로 출시되었습니다! -- prompting and prompt engineering -- text and image app generation -- search apps +생성형 AI에 대한 12개의 강의를 통해 배울 것은 아래와 같습니다: -As usual, there's a lesson, assignments to complete, knowledge checks and challenges. +- 프롬프트 엔지니어링 (생성형 AI에게 좋은 질문을 만드는 것을 의미합니다.) +- 텍스트 및 이미지 생성 앱 +- 검색 앱 -Check it out: +이 과정 역시 강의와, 과제, 퀴즈 등으로 구성되어 있습니다. > https://aka.ms/genai-beginners --- -# Content +# 강의 목록 - + - - + + - - - - + + + - + - - + + - - + + - + - - - - - - - - - + + + + + + + + + - + - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + +
NoLessonIntroPyTorchKeras/TensorFlowLab
순번강의명개요PyTorchKeras/TensorFlowLab
IIntroduction to AI
1Introduction and History of AIText
IAI 소개
1AI의 역사읽기
IISymbolic AI
2 Knowledge Representation and Expert SystemsTextExpert System, Ontology, Concept Graph
IIIIntroduction to Neural Networks
3PerceptronText +
2 지식표현과 전문가시스템읽기전문가시스템, 온톨로지, 개념 그래프
III신경망 소개
3퍼셉트론읽기 NotebookLab
4 Multi-Layered Perceptron and Creating our own FrameworkTextNotebookLab
4 다층 퍼셉트론
나만의 프레임워크 만들기		TextNotebookLab
5Intro to Frameworks (PyTorch/TensorFlow) and OverfittingText프레임워크(PyTorch/TensorFlow) 개요
과적합		읽기 PyTorch Keras/TensorFlow Lab
IVComputer VisionMicrosoft Azure AI Fundamentals: Explore Computer Vision
IV컴퓨터 비전Microsoft 애저 AI 기본 사항: 컴퓨터 비전
Microsoft Learn Module on Computer Vision
컴퓨터 비전에 대한 Microsoft Learn 모듈 PyTorch TensorFlow
6Intro to Computer Vision. OpenCVTextNotebookLab
7Convolutional Neural Networks
CNN Architectures		Text
Text		PyTorchTensorFlowLab
8Pre-trained Networks and Transfer Learning
Training Tricks		Text
Text		PyTorchTensorFlow
Dropout sample
Adversarial Cat		Lab
9Autoencoders and VAEsTextPyTorchTensorFlow
10Generative Adversarial Networks
Artistic Style Transfer		TextPyTorchTensorFlow GAN
Style Transfer
11Object DetectionTextPyTorchTensorFlowLab
12Semantic Segmentation. U-NetTextPyTorchTensorFlow
VNatural Language ProcessingMicrosoft Azure AI Fundamentals: Explore Natural Language Processing
6컴퓨터 비전 개요, OpenCV읽기NotebookLab
7CNN, 합성곱 신경망읽기
읽기		PyTorchTensorFlowLab
8사전 학습 모델과 전이학습
학습 기법들		읽기
읽기		PyTorchTensorFlow
드롭아웃 예제
Adversarial Cat		Lab
9오토인코더와 VAE읽기PyTorchTensorFlow
10생성적 적대 신경망
미술 스타일 학습		읽기PyTorchTensorFlow GAN
Style Transfer
11객체 인식읽기PyTorchTensorFlowLab
12의미적 분할, U-Net읽기PyTorchTensorFlow
V자연어 처리Microsoft 애저 AI 기본 사항: 자연어 처리
Microsoft Learn Module on Natural language processing
자연어 처리에 대한 Microsoft Learn 모듈 PyTorch TensorFlow
13Text Representation. Bow/TF-IDFTextPyTorchTensorFlow
14Semantic word embeddings. Word2Vec and GloVeTextPyTorchTensorFlow
15Language Modeling. Training your own embeddingsTextPyTorchTensorFlowLab
16Recurrent Neural NetworksTextPyTorchTensorFlow
17Generative Recurrent NetworksTextPyTorchTensorFlowLab
18Transformers. BERT.TextPyTorchTensorFlow
19Named Entity RecognitionTextTensorFlowLab
20Large Language Models, Prompt Programming and Few-Shot TasksTextPyTorch
VIOther AI Techniques
21Genetic AlgorithmsTextNotebook
22Deep Reinforcement LearningTextPyTorchTensorFlowLab
23Multi-Agent SystemsText
VIIAI Ethics
24AI Ethics and Responsible AITextMS Learn: Responsible AI Principles
Extras
X1Multi-Modal Networks, CLIP and VQGANTextNotebook
13글자 표현, Bow/TF-IDF읽기PyTorchTensorFlow
14의미적 단어 임베딩, Word2Vec과 GloVe읽기PyTorchTensorFlow
15언어 모델링, 나만의 임베딩 만들기읽기PyTorchTensorFlowLab
16순환 신경망읽기PyTorchTensorFlow
17생성적 순환 신경망읽기PyTorchTensorFlowLab
18트랜스포머, BERT읽기PyTorchTensorFlow
19개체명 인식읽기TensorFlowLab
20LLM, 대규모 언어 모델
프롬프트 프로그래밍과 Few-Shot 학습		읽기PyTorch
VI다른 AI 기법
21유전 알고리즘읽기Notebook
22심층 강화학습읽기PyTorchTensorFlowLab
23다중 에이전트 시스템읽기
VIIAI 윤리
24AI 윤리와 책임있는 AI읽기MS Learn: Responsible AI Principles(링크 없음)
기타
X1멀티모달 신경망, CLIP과 VQGAN읽기Notebook
-**[Mindmap of the Course](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)** - -Each lesson contains some pre-reading material (linked as **Text** above), and some executable Jupyter Notebooks, which are often specific to the framework (**PyTorch** or **TensorFlow**). The executable notebook also contains a lot of theoretical material, so to understand the topic you need to go through at least one version of the notebooks (either PyTorch or TensorFlow). There are also **Labs** available for some topics, which give you an opportunity to try applying the material you have learned to a specific problem. +**[마인드맵](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)** -Some sections also contain links to **MS Learn** modules that cover related topics. Microsoft Learn provides a convenient GPU-enabled learning environment, although in terms of content you can expect this curriculum to go a bit deeper. +각 강의는 링크 되어있는 **읽기**와, **Pytorch**나 **Tensorflow** 등의 프레임워크로 코드를 실행할 수 있는 주피터 노트북(**Notebook**)으로 구성됩니다. 주피터 노트북에는 이론적인 설명도 많으니 두 프레임워크 중 하나는 꼭 확인해 주세요. **Labs**가 있는 강의도 있습니다. 이는 배운 것을 실습해 볼 수 있도록 가이드와 함께 문제가 준비되어 있습니다. -# Are you a student? +몇몇 주제는 **MS Learn**과 링크되어 있습니다. 그 주제를 좀 더 공부하고 싶으시다면 참고하시길 바랍니다. -Get started with the following resources: +# 학생인가요? -- [Student Hub page](https://docs.microsoft.com/learn/student-hub?WT.mc_id=academic-77998-cacaste) In this page, you will find beginner resources, Student packs and even ways to get a free cert voucher. This is one page you want to bookmark and check from time to time as we switch out content at least monthly. -- [Microsoft Student Learn ambassadors](https://studentambassadors.microsoft.com?WT.mc_id=academic-77998-cacaste) Join a global community of student ambassadors, this could be your way into Microsoft. +아래의 사이트도 확인해보세요: -# Getting Started +- [Microsoft 학생 허브](https://docs.microsoft.com/learn/student-hub?WT.mc_id=academic-77998-cacaste) +학생을 위한 다양한 학습자료, 개발도구 재공하고 있습니다. +- [Microsoft 커뮤니티리더](https://studentambassadors.microsoft.com?WT.mc_id=academic-77998-cacaste) +글로벌 학생 커뮤니티에 참여하세요. -**Students**, there are a couple of ways to use the curriculum. First of all, you can just read the text and look through the code directly on GitHub. If you want to run the code in any of the notebook - [read our instructions](./etc/how-to-run.md), and find more advice on how to do it [in this blog post](https://soshnikov.com/education/how-to-execute-notebooks-from-github/). +# 시작하기 -> **Note**: [Instructions on how to run the code in this curriculum](./etc/how-to-run.md) +**학생**이십니까? 이 과정을 사용하는 몇가지 방법을 소개하겠습니다. 우선 단순히 읽기 자료를 읽고 코드를 확인해 볼 수 있습니다. 주피터 노트북 코드 실행이 궁금하다면 [여기를 참고하세요](./etc/how-to-run.md), 더 자세한 설명은 [이 영문 블로그](https://soshnikov.com/education/how-to-execute-notebooks-from-github/)에도 있습니다. -However, if you would like to take the course as a self-study project, we suggest that you fork the entire repo to your own GitHub account and complete the exercises on your own or with a group: +> **안내사항**: [제공되는 코드를 실행하는 방법](./etc/how-to-run.md) -- Start with a pre-lecture quiz. -- Read the intro text for the lecture. -- If the lecture has additional notebooks, go through them, reading and executing the code. If both TensorFlow and PyTorch notebooks are provided, you can focus on one of them - choose your favorite framework. -- Notebooks often contain some of the challenges that require you to tweak the code a little bit to experiment. -- Take the post-lecture quiz. -- If there is a lab attached to the module - complete the assignment. -- Visit the [Discussion board](https://github.com/microsoft/AI-For-Beginners/discussions) to "learn out loud". +하지만, 깃허브를 통해 전체 레포지토리를 포크하고 혼자 혹은 그룹으로 과제들을 완료하는 것을 추천합니다. +- 사전 퀴즈를 먼저 풀어보세요. +- 강의 개요 읽기자료를 읽으세요. +- 주피터 노트북 자료가 있으면 코드를 읽어보고 실행해보세요. 프레임워크는 텐서플로우/파이토치 아무거나 하나만 집중하여 학습하세요. +- 노트북 자료에는 가끔 약간의 수정이 필요한 과제가 있을 수 있습니다. +- 강의 수강 후 퀴즈를 풀어보세요. +- lab이 있는 경우 그 과제를 완료하세요. +- [토의장](https://github.com/microsoft/AI-For-Beginners/discussions)에 방문하여 "다 같이 공부하세요". -> For further study, we recommend following these [Microsoft Learn](https://docs.microsoft.com/en-us/users/dmitrysoshnikov-9132/collections/31zgizg2p418yo/?WT.mc_id=academic-77998-cacaste) modules and learning paths. +> 더 자세한 공부를 위한다면, 이 [Microsoft Learn](https://docs.microsoft.com/en-us/users/dmitrysoshnikov-9132/collections/31zgizg2p418yo/?WT.mc_id=academic-77998-cacaste) 모듈과 학습경로를 따라 학습하는 것을 추천합니다. -**Teachers**, we have [included some suggestions](/etc/for-teachers.md) on how to use this curriculum. +**교육자**를 위한 [몇 가지의 활용법](/etc/for-teachers.md)을 적어두었습니다. --- @@ -155,41 +154,41 @@ However, if you would like to take the course as a self-study project, we sugges **✅ Quiz Creator:** [Lateefah Bello](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/)
**🙏 Core Contributors:** [Evgenii Pishchik](https://github.com/Pe4enIks) -## Meet the Team +## 제작자를 만나보세요 [![Promo video](/lessons/sketchnotes/ai-for-beginners.png)](https://youtu.be/m2KrAk0cC1c "Promo video") -> 🎥 Click the image above for a video about the project and the folks who created it! +> 🎥 제작자와 프로젝트에 대한 비디오를 보시려면 위의 그림을 클릭하세요! --- -## Pedagogy +## 학습철학 -We have chosen two pedagogical tenets while building this curriculum: ensuring that it is hands-on **project-based** and that it includes **frequent quizzes**. +**프로젝트 기반 실습**과 **잦은 퀴즈**, 두가지 목적을 가지고 이 과정을 기획하였습니다. -By ensuring that the content aligns with projects, the process is made more engaging for students and retention of concepts will be augmented. In addition, a low-stakes quiz before a class sets the intention of the student towards learning a topic, while a second quiz after class ensures further retention. This curriculum was designed to be flexible and fun and can be taken in whole or in part. The projects start small and become increasingly complex by the end of the 12 week cycle. +프로젝트 기반의 콘텐츠는 학생들의 흥미를 돋우고 내용을 기억하는 것에 도움이 됩니다. 그리고 사전 퀴즈는 이번에 어떤 것을 배우게 되는지 인지시키기 위해, 강의 후 퀴즈는 학습 내용의 보존을 위해 마련하였습니다. 재미있고 유연하게 기획되었기 때문에 전체를 학습하는 것이 아니라 원하는 부분만을 학습해도 괜찮도록 만들었습니다. 처음에는 간단하겠지만 강의가 계속 될수록 점점 복잡해집니다. -> Find our [Code of Conduct](etc/CODE_OF_CONDUCT.md), [Contributing](etc/CONTRIBUTING.md), and [Translation](etc/TRANSLATIONS.md) guidelines. Find our [Support Documentation here](etc/SUPPORT.md) and [security information here](etc/SECURITY.md). We welcome your constructive feedback! +> [행동규칙](etc/CODE_OF_CONDUCT.md), [기여](etc/CONTRIBUTING.md) 그리고 [번역](etc/TRANSLATIONS.md) 가이드라인을 확인해보세요. Find our [지원](etc/SUPPORT.md)과 [보안](etc/SECURITY.md) 문서를 확인해보세요. 여러분의 피드백을 환영합니다! -> **A note about quizzes**: All quizzes are contained [in this app](https://red-field-0a6ddfd03.1.azurestaticapps.net/), for 50 total quizzes of three questions each. They are linked from within the lessons but the quiz app can be run locally; follow the instruction in the `etc/quiz-app` folder. +> **퀴즈에 대한 안내사항**: 모든 퀴즈는 [여기](https://red-field-0a6ddfd03.1.azurestaticapps.net/)를 통해 풀 수 있습니다. 총 50개의 퀴즈에 각 3개의 문제가 있습니다. 웹앱이지만, 모든 내용은 프로젝트에 있으니 로컬로도 실행할 수 있습니다; `etc/quiz-app`을 확인해보세요. ## Offline access -You can run this documentation offline by using [Docsify](https://docsify.js.org/#/). Fork this repo, [install Docsify](https://docsify.js.org/#/quickstart) on your local machine, and then in the `etc/docsify` folder of this repo, type `docsify serve`. The website will be served on port 3000 on your localhost: `localhost:3000`. A pdf of the curriculum is available [at this link](/etc/pdf/readme.pdf). +> 내용이 부정확하여 번역을 하지 않았습니다. -## Help Wanted! +You can run this documentation offline by using [Docsify](https://docsify.js.org/#/). Fork this repo, [install Docsify](https://docsify.js.org/#/quickstart) on your local machine, and then in the `etc/docsify` folder of this repo, type `docsify serve`. The website will be served on port 3000 on your localhost: `localhost:3000`. A pdf of the curriculum is available [at this link](/etc/pdf/readme.pdf). -Would you like to contribute a translation? Please read our [translation guidelines](etc/TRANSLATIONS.md). +## 번역 -## Other Curricula +번역을 원하시면 [번역 가이드라인](etc/TRANSLATIONS.md)을 확인하세요. -Our team produces other curricula! Check out: +## 다른 학습과정 -- [AI for Beginners](https://aka.ms/ai-beginners) -- [Data Science for Beginners](https://aka.ms/datascience-beginners) -- [Generative AI for Beginners](https://aka.ms/genai-beginners) -- [Web Dev for Beginners](https://aka.ms/webdev-beginners) -- [IoT for Beginners](https://aka.ms/iot-beginners) -- [Machine Learning for Beginners](https://aka.ms/ml-beginners) -- [XR Development for Beginners](https://aka.ms/xr-dev-for-beginners) -- [Mastering GitHub Copilot for AI Paired Programming](https://aka.ms/GitHubCopilotAI) +- [초보자를 위한 인공지능](https://aka.ms/ai-beginners) +- [초보자를 위한 데이터 사이언스](https://aka.ms/datascience-beginners) +- [초보자를 위한 생성형 AI](https://aka.ms/genai-beginners) +- [초보자를 위한 웹 개발](https://aka.ms/webdev-beginners) +- [초보자를 위한 IoT](https://aka.ms/iot-beginners) +- [초보자를 위한 기계학습](https://aka.ms/ml-beginners) +- [초보자를 위한 XR 개발](https://aka.ms/xr-dev-for-beginners) +- [AI와 함께하는 개발: 깃허브 Copilot](https://aka.ms/GitHubCopilotAI)