{"id":28348066,"url":"https://github.com/ashishps1/learn-ai-engineering","last_synced_at":"2025-07-02T17:32:53.341Z","repository":{"id":287359918,"uuid":"964477695","full_name":"ashishps1/learn-ai-engineering","owner":"ashishps1","description":"Learn AI and LLMs from scratch using free resources","archived":false,"fork":false,"pushed_at":"2025-05-23T05:33:49.000Z","size":81,"stargazers_count":1171,"open_issues_count":0,"forks_count":265,"subscribers_count":20,"default_branch":"main","last_synced_at":"2025-06-25T07:02:12.406Z","etag":null,"topics":["agentic-ai","agents","ai","deep-learning","generative-ai","large-language-models","llm","machine-learning","mcp","ml","prompt-engineering","rag"],"latest_commit_sha":null,"homepage":"","language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/ashishps1.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2025-04-11T09:20:56.000Z","updated_at":"2025-06-25T00:04:37.000Z","dependencies_parsed_at":"2025-06-25T07:01:48.082Z","dependency_job_id":"cb3cfcb4-5a67-4d19-9c0a-530e53ab32f0","html_url":"https://github.com/ashishps1/learn-ai-engineering","commit_stats":null,"previous_names":["ashishps1/awesome-ai-resources","ashishps1/awesome-ai-llm-resources","ashishps1/learn-ai-engineering"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/ashishps1/learn-ai-engineering","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ashishps1%2Flearn-ai-engineering","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ashishps1%2Flearn-ai-engineering/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ashishps1%2Flearn-ai-engineering/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ashishps1%2Flearn-ai-engineering/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ashishps1","download_url":"https://codeload.github.com/ashishps1/learn-ai-engineering/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ashishps1%2Flearn-ai-engineering/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":263184703,"owners_count":23427071,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["agentic-ai","agents","ai","deep-learning","generative-ai","large-language-models","llm","machine-learning","mcp","ml","prompt-engineering","rag"],"created_at":"2025-05-27T18:09:57.065Z","updated_at":"2025-07-02T17:32:53.334Z","avatar_url":"https://github.com/ashishps1.png","language":null,"funding_links":[],"categories":["📚 Projects (1974 total)","Others","Other Lists","Don't forget to give a :star: to make the project popular","MCP Resources \u0026 Educational Materials","Domain-Specific AI Agents"],"sub_categories":["MCP Servers","TeX Lists","Gateways","Educational \u0026 Learning Agents"],"readme":"# Learn AI Engineering\n\nA comprehensive collection of free resources to learn everything about AI/ML, LLMs and Agents.\n\n## Mathematical Foundations\n- [Essence of Linear Algebra - 3Blue1Brown](https://www.youtube.com/playlist?list=PLZHQObOWTQDPD3MizzM2xVFitgF8hE_ab)\n- [Probability \u0026 Statistics - Khan Academy](https://www.khanacademy.org/math/statistics-probability)\n- [Statistics Fundamentals - Josh Strarmer](https://www.youtube.com/playlist?list=PLblh5JKOoLUK0FLuzwntyYI10UQFUhsY9)\n- [Mathematics for Machine Learning Specialization - Coursera (Andrew Ng)](https://www.coursera.org/specializations/mathematics-machine-learning)\n\n## Python\n- [AI Python for Beginners - Deeplearning.ai](https://www.deeplearning.ai/short-courses/ai-python-for-beginners/)\n\n## AI \u0026 ML Fundamentals\n- [Machine Learning Crash Course - Google](https://developers.google.com/machine-learning/crash-course)\n- [AI for Beginners – Microsoft](https://microsoft.github.io/AI-For-Beginners/)\n- [Elements of AI – University of Helsinki](https://course.elementsofai.com/)\n- [Machine Learning Playlist - Josh Strarmer](https://www.youtube.com/playlist?list=PLblh5JKOoLUICTaGLRoHQDuF_7q2GfuJF)\n- [Machine Learning Specialization - Coursera](https://www.coursera.org/specializations/machine-learning-introduction)\n\n### Machine Learning Frameworks\n- [Scikit-learn](https://scikit-learn.org/stable/)\n- [XGBoost](https://xgboost.ai/)\n- [LightGBM](https://lightgbm.readthedocs.io/en/stable/)\n- [CatBoost](https://catboost.ai/)\n\n## Deep Learning\n- [Deep Learning Specialization - Coursera (Andrew Ng)](https://www.coursera.org/specializations/deep-learning)\n- [Practical Deep Learning for Coders - Fast.ai](https://course.fast.ai/)\n- [Mathematics for Deep Learning](https://d2l.ai/chapter_appendix-mathematics-for-deep-learning/)\n- [Deep Learning Playlist - Josh Starmer](https://www.youtube.com/playlist?list=PLblh5JKOoLUIxGDQs4LFFD--41Vzf-ME1)\n\n### Deep Learning Frameworks\n- [TensorFlow](https://www.tensorflow.org/)\n- [PyTorch](https://pytorch.org/)\n- [Keras](https://keras.io/)\n\n## Deep Learning Specializations\n### Computer Vision\n- [Deep Learning for Computer Vision - Stanford](https://cs231n.stanford.edu/)\n### Natural Language Processing (NLP)\n- [NLP Specialization - Coursera](https://www.coursera.org/specializations/natural-language-processing)\n### Reinforcement Learning\n- [Deep RL Course - Hugging Face](https://huggingface.co/learn/deep-rl-course/unit0/introduction)\n- [Deep RL Bootcamp - UC Berkeley](https://sites.google.com/view/deep-rl-bootcamp/lectures)\n\n## Generative AI\n- [The Building Blocks of Generative AI](https://shriftman.substack.com/p/the-building-blocks-of-generative)\n- [Generative AI for Beginners - Microsoft](https://github.com/microsoft/generative-ai-for-beginners)\n- [Generative AI for Everyone - Coursera](https://www.coursera.org/learn/generative-ai-for-everyone)\n\n## Large Language Models (LLMs)\n- [The Illustrated Transformer](https://jalammar.github.io/illustrated-transformer/)\n- [Large Language Models explained briefly](https://www.youtube.com/watch?v=LPZh9BOjkQs)\n- [Intro to LLMs](https://www.youtube.com/watch?v=zjkBMFhNj_g\u0026pp=ygUDbGxt)\n- [Understanding Large Language Models](https://magazine.sebastianraschka.com/p/understanding-large-language-models)\n- [A Visual Guide to Reasoning LLMs](https://newsletter.maartengrootendorst.com/p/a-visual-guide-to-reasoning-llms)\n- [Understanding Reasoning LLMs](https://magazine.sebastianraschka.com/p/understanding-reasoning-llms)\n- [Understanding Multimodal LLMs](https://magazine.sebastianraschka.com/p/understanding-multimodal-llms)\n- [A Visual Guide to Mixture of Experts (MoE)](https://newsletter.maartengrootendorst.com/p/a-visual-guide-to-mixture-of-experts)\n- [Finetuning Large Language Models](https://magazine.sebastianraschka.com/p/finetuning-large-language-models)\n- [How Transformer LLMs Work](https://www.deeplearning.ai/short-courses/how-transformer-llms-work/)\n- [Building GPT from scratch - Andrej Karpathy](https://www.youtube.com/watch?v=kCc8FmEb1nY)\n- [LLM Course - GitHub](https://github.com/mlabonne/llm-course)\n- [LLM Course - Hugging Face](https://huggingface.co/learn/llm-course/chapter1/1)\n- [Awesome LLM Apps - GitHub](https://github.com/Shubhamsaboo/awesome-llm-apps)\n\n### LLM Chatbots\n- [ChatGPT](https://chatgpt.com/)\n- [Gemini](https://gemini.google.com/app)\n- [Claude](https://claude.ai/new)\n- [Perplexity](https://www.perplexity.ai/)\n\n### Open Source LLMs\n- [Llama](https://www.llama.com/)\n- [Deepseek](https://chat.deepseek.com/)\n\n### LLM APIs\n- [OpenAI](https://platform.openai.com/docs/overview)\n- [Anthropic](https://docs.anthropic.com/en/docs/overview)\n- [Gemini - Google](https://ai.google.dev/gemini-api/docs)\n- [Groq - Inference](https://groq.com/)\n\n### LLM Tools \u0026 Frameworks\n- [LangChain](https://www.langchain.com/)\n- [LlamaIndex](https://www.llamaindex.ai/)\n- [Ollama](https://ollama.com/)\n- [Instructor](https://python.useinstructor.com/)\n- [Outlines](https://github.com/dottxt-ai/outlines)\n\n### LLM Based IDEs\n- [Cursor](https://www.cursor.com/)\n- [Windsurf](https://windsurf.com/editor)\n- [GitHub Copilot](https://github.com/features/copilot)\n\n## Prompt Engineering\n- [Google Prompting Essentials](https://www.coursera.org/google-learn/prompting-essentials)\n- [ChatGPT Prompt Engineering for Developers - Deeplearning.ai](https://www.deeplearning.ai/short-courses/chatgpt-prompt-engineering-for-developers/)\n- [Advanced Prompting Techniques - Instructor](https://python.useinstructor.com/prompting/)\n- [Prompt Engineering Techniques - Github](https://github.com/NirDiamant/Prompt_Engineering)\n- [Getting Structured LLM Output - Deeplearning.ai](https://www.deeplearning.ai/short-courses/getting-structured-llm-output/)\n\n## Retrieval-Augmented Generation (RAG)\n- [Introduction to RAG - Coursera](https://www.coursera.org/projects/introduction-to-rag)\n- [RAG Techniques - Github](https://github.com/NirDiamant/RAG_Techniques)\n\n## AI Agents\n- [A Visual Guide to LLM Agents](https://newsletter.maartengrootendorst.com/p/a-visual-guide-to-llm-agents)\n- [Agents - Chip Huyen](https://huyenchip.com/2025/01/07/agents.html)\n- [AI Agents Course - Hugging Face](https://huggingface.co/learn/agents-course/)\n- [Building AI Browser Agents - Deeplearning.ai](https://www.deeplearning.ai/short-courses/building-ai-browser-agents/)\n- [GenAI Agents - Github](https://github.com/NirDiamant/GenAI_Agents)\n\n## Model Context Protocol (MCP)\n- [MCP - Anthropic Guide](https://modelcontextprotocol.io/introduction)\n- [Building AI Apps using MCP](https://www.deeplearning.ai/short-courses/mcp-build-rich-context-ai-apps-with-anthropic/)\n- [MCP Course - Hugging Face](https://huggingface.co/learn/mcp-course/unit0/introduction)\n- [Awesome MCP Servers - Github](https://github.com/punkpeye/awesome-mcp-servers)\n\n## MLOps \u0026 Deployment\n- [ML in Production - Coursera](https://www.coursera.org/learn/introduction-to-machine-learning-in-production)\n- [Full Stack Deep Learning](https://fullstackdeeplearning.com/course/2022/)\n- [ML System Design - Stanford](https://stanford-cs329s.github.io/syllabus.html)\n\n### Tools\n- [Streamlit](https://streamlit.io/)\n- [MLflow](https://mlflow.org/docs/latest/index.html)\n\n## Guides\n- [OpenAI Cookbook](https://cookbook.openai.com/)\n- [Anthropic courses](https://github.com/anthropics/courses/tree/master)\n\n## Books\n- [Hands-On Machine Learning](https://www.oreilly.com/library/view/hands-on-machine-learning/9781492032632/)\n- [Deep Learning - Ian Goodfellow](https://www.deeplearningbook.org/)\n- [Deep Learning with Python](https://www.amazon.in/Deep-Learning-Python-Francois-Chollet/dp/1617294438/)\n- [Why Machines Learn](https://www.amazon.com/Why-Machines-Learn-Elegant-Behind/dp/0593185749)\n- [Designing Machine Learning Systems](https://www.oreilly.com/library/view/designing-machine-learning/9781098107956/)\n- [AI Engineering](https://www.oreilly.com/library/view/ai-engineering/9781098166298/)\n- [Build a LLM from Scratch](https://www.manning.com/books/build-a-large-language-model-from-scratch)\n- [Prompt Engineering for LLMs](https://www.oreilly.com/library/view/prompt-engineering-for/9781098156145/)\n- [Natural Language Processing with Transformers](https://www.oreilly.com/library/view/natural-language-processing/9781098136789/)\n\n## YouTube Channels\n- [Andrej Karpathy](https://www.youtube.com/@AndrejKarpathy)\n- [3Blue1Brown](https://www.youtube.com/@3blue1brown)\n\n## Other Resources\n- [Papers with Code](https://paperswithcode.com/)\n- [Kaggle Competitions](https://www.kaggle.com/competitions)\n\n## Must-Read AI Papers\n- [Attention Is All You Need](https://arxiv.org/pdf/1706.03762)\n- [Generative Adversarial Networks (GANs)](https://arxiv.org/abs/1406.2661)\n- [GPT: Improving Language Understanding by Generative Pre-Training](https://cdn.openai.com/research-covers/language-unsupervised/language_understanding_paper.pdf)\n- [GPT-3: Language Models are Few-Shot Learners](https://arxiv.org/abs/2005.14165)\n- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://arxiv.org/abs/1810.04805)\n- [Chain-of-Thought Prompting Elicits Reasoning in LLMs](https://arxiv.org/abs/2201.11903)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fashishps1%2Flearn-ai-engineering","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fashishps1%2Flearn-ai-engineering","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fashishps1%2Flearn-ai-engineering/lists"}