{"id":13456089,"url":"https://github.com/aishwaryanr/awesome-generative-ai-guide","last_synced_at":"2025-09-27T10:30:27.664Z","repository":{"id":221458164,"uuid":"753750990","full_name":"aishwaryanr/awesome-generative-ai-guide","owner":"aishwaryanr","description":"A one stop repository for generative AI research updates, interview resources, notebooks and much more!","archived":false,"fork":false,"pushed_at":"2024-04-10T21:28:35.000Z","size":23396,"stargazers_count":3614,"open_issues_count":0,"forks_count":697,"subscribers_count":94,"default_branch":"main","last_synced_at":"2024-04-11T18:57:15.695Z","etag":null,"topics":["awesome","awesome-list","generative-ai","interview-questions","large-language-models","llms","notebook-jupyter","vision-and-language"],"latest_commit_sha":null,"homepage":"https://www.linkedin.com/in/areganti/","language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/aishwaryanr.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE.md","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}},"created_at":"2024-02-06T18:14:14.000Z","updated_at":"2024-04-18T02:45:22.235Z","dependencies_parsed_at":"2024-04-18T02:45:21.566Z","dependency_job_id":"d72537b4-8b0f-4a9a-b443-9ca068f791f5","html_url":"https://github.com/aishwaryanr/awesome-generative-ai-guide","commit_stats":null,"previous_names":["aishwaryanr/awesome-generative-ai-guide"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/aishwaryanr%2Fawesome-generative-ai-guide","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/aishwaryanr%2Fawesome-generative-ai-guide/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/aishwaryanr%2Fawesome-generative-ai-guide/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/aishwaryanr%2Fawesome-generative-ai-guide/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/aishwaryanr","download_url":"https://codeload.github.com/aishwaryanr/awesome-generative-ai-guide/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":234338057,"owners_count":18816449,"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":["awesome","awesome-list","generative-ai","interview-questions","large-language-models","llms","notebook-jupyter","vision-and-language"],"created_at":"2024-07-31T08:01:16.015Z","updated_at":"2025-09-27T10:30:27.657Z","avatar_url":"https://github.com/aishwaryanr.png","language":null,"funding_links":[],"categories":["Others","awesome","HTML","Awesome","A01_文本生成_文本对话","AI","HarmonyOS","Other Lists","关键资源","Repos",":speaker: Announcements","Uncategorized","Miscellaneous","资源中心","🤖 Machine Learning \u0026 AI","Research \u0026 Data Analysis","📚 Learning \u0026 Resources","Attribution","Open-Source LLM \u0026 Agent Projects","🏆 القائمة الكاملة Top 200"],"sub_categories":["其他_文本生成_文本对话","Windows Manager","TeX Lists","学习资源","Uncategorized","Resources","AI-Assisted CG Software"],"readme":"# :star: :bookmark: awesome-generative-ai-guide\n\nGenerative AI is experiencing rapid growth, and this repository serves as a comprehensive hub for updates on generative AI research, interview materials, notebooks, and more!\n\n\u003ca href=\"https://trendshift.io/repositories/7663\" target=\"_blank\"\u003e\u003cimg src=\"https://trendshift.io/api/badge/repositories/7663\" alt=\"aishwaryanr%2Fawesome-generative-ai-guide | Trendshift\" style=\"width: 250px; height: 55px;\" width=\"250\" height=\"55\"/\u003e\u003c/a\u003e\n\nExplore the following resources:\n\n1. [Monthly Best GenAI Papers List](https://github.com/aishwaryanr/awesome-generative-ai-guide?tab=readme-ov-file#star-best-genai-papers-list-january-2024)\n2. [GenAI Interview Resources](https://github.com/aishwaryanr/awesome-generative-ai-guide?tab=readme-ov-file#computer-interview-prep)\n3. [Applied LLMs Mastery 2024 (created by Aishwarya Naresh Reganti) course material](https://github.com/aishwaryanr/awesome-generative-ai-guide?tab=readme-ov-file#ongoing-applied-llms-mastery-2024)\n4. [Generative AI Genius 2024 (created by Aishwarya Naresh Reganti) course material](https://github.com/aishwaryanr/awesome-generative-ai-guide/blob/main/free_courses/generative_ai_genius/README.md)\n5. [List of all GenAI-related free courses (over 90 listed)](https://github.com/aishwaryanr/awesome-generative-ai-guide?tab=readme-ov-file#book-list-of-free-genai-courses)\n6. [List of code repositories/notebooks for developing generative AI applications](https://github.com/aishwaryanr/awesome-generative-ai-guide?tab=readme-ov-file#notebook-code-notebooks)\n\nWe'll be updating this repository regularly, so keep an eye out for the latest additions!\n\nHappy Learning!\n\n---\n## :star: Top AI Tools List\n\nDiscover our favorite AI tools spanning every layer of AI application development. Click [here](https://github.com/aishwaryanr/awesome-generative-ai-guide/blob/main/resources/our_favourite_ai_tools.md) to learn more.\n\n---\n\n## :speaker: Announcements\n\n- Applied LLMs Mastery full course content has been released!!! ([Click Here](https://github.com/aishwaryanr/awesome-generative-ai-guide/blob/main/free_courses/Applied_LLMs_Mastery_2024))\n- 5-day roadmap to learn LLM foundations out now! ([Click Here](https://github.com/aishwaryanr/awesome-generative-ai-guide/blob/main/resources/genai_roadmap.md))\n- 60 Common GenAI Interview Questions out now! ([Click Here](https://github.com/aishwaryanr/awesome-generative-ai-guide/blob/main/interview_prep/60_gen_ai_questions.md))\n- ICLR 2024 paper summaries ([Click Here](https://areganti.notion.site/06f0d4fe46a94d62bff2ae001cfec22c?v=d501ca62e4b745768385d698f173ae14))\n- List of free GenAI courses ([Click Here](https://github.com/aishwaryanr/awesome-generative-ai-guide#book-list-of-free-genai-courses))\n- Generative AI resources and roadmaps\n  - [3-day RAG roadmap](https://github.com/aishwaryanr/awesome-generative-ai-guide/blob/main/resources/RAG_roadmap.md)\n  - [5-day LLM foundations roadmap](https://github.com/aishwaryanr/awesome-generative-ai-guide/blob/main/resources/genai_roadmap.md)\n  - [5-day LLM agents roadmap](https://github.com/aishwaryanr/awesome-generative-ai-guide/blob/main/resources/agents_roadmap.md)\n  - [Agents 101 guide](https://github.com/aishwaryanr/awesome-generative-ai-guide/blob/main/resources/agents_101_guide.md)\n  - [Introduction to MM LLMs](https://github.com/aishwaryanr/awesome-generative-ai-guide/blob/main/resources/mm_llms_guide.md)\n  - [LLM Lingo Series: Commonly used LLM terms and their easy-to-understand definitions](https://github.com/aishwaryanr/awesome-generative-ai-guide/blob/main/resources/llm_lingo)\n\n---\n\n\n## :mortar_board: Courses\n\n#### [Ongoing] Applied LLMs Mastery 2024\n\nJoin 1000+ students on this 10-week adventure as we delve into the application of LLMs across a variety of use cases\n\n#### [Link](https://areganti.notion.site/Applied-LLMs-Mastery-2024-562ddaa27791463e9a1286199325045c) to the course website\n\n##### [Feb 2024] Registrations are still open [click here](https://forms.gle/353sQMRvS951jDYu7) to register\n\n🗓️\\*Week 1 [Jan 15 2024]**\\*: [Practical Introduction to LLMs](https://github.com/aishwaryanr/awesome-generative-ai-guide/blob/main/free_courses/Applied_LLMs_Mastery_2024/week1_part1_foundations.md)**\n\n- Applied LLM Foundations\n- Real World LLM Use Cases\n- Domain and Task Adaptation Methods\n\n🗓️\\*Week 2 [Jan 22 2024]**\\*: [Prompting and Prompt\nEngineering](https://github.com/aishwaryanr/awesome-generative-ai-guide/blob/main/free_courses/Applied_LLMs_Mastery_2024/week2_prompting.md)**\n\n- Basic Prompting Principles\n- Types of Prompting\n- Applications, Risks and Advanced Prompting\n\n🗓️\\*Week 3 [Jan 29 2024]**\\*: [LLM Fine-tuning](https://github.com/aishwaryanr/awesome-generative-ai-guide/blob/main/free_courses/Applied_LLMs_Mastery_2024/week3_finetuning_llms.md)**\n\n- Basics of Fine-Tuning\n- Types of Fine-Tuning\n- Fine-Tuning Challenges\n\n🗓️\\*Week 4 [Feb 5 2024]**\\*: [RAG (Retrieval-Augmented Generation)](https://github.com/aishwaryanr/awesome-generative-ai-guide/blob/main/free_courses/Applied_LLMs_Mastery_2024/week4_RAG.md)**\n\n- Understanding the concept of RAG in LLMs\n- Key components of RAG\n- Advanced RAG Methods\n\n🗓️\\*Week 5 [ Feb 12 2024]**\\*: [Tools for building LLM Apps](https://github.com/aishwaryanr/awesome-generative-ai-guide/blob/main/free_courses/Applied_LLMs_Mastery_2024/week5_tools_for_LLM_apps.md)**\n\n- Fine-tuning Tools\n- RAG Tools\n- Tools for observability, prompting, serving, vector search etc.\n\n🗓️\\*Week 6 [Feb 19 2024]**\\*: [Evaluation Techniques](https://github.com/aishwaryanr/awesome-generative-ai-guide/blob/main/free_courses/Applied_LLMs_Mastery_2024/week6_llm_evaluation.md)**\n\n- Types of Evaluation\n- Common Evaluation Benchmarks\n- Common Metrics\n\n🗓️\\*Week 7 [Feb 26 2024]**\\*: [Building Your Own LLM Application](https://github.com/aishwaryanr/awesome-generative-ai-guide/blob/main/free_courses/Applied_LLMs_Mastery_2024/week7_build_llm_app.md)**\n\n- Components of LLM application\n- Build your own LLM App end to end\n\n🗓️\\*Week 8 [March 4 2024]**\\*: [Advanced Features and Deployment](https://github.com/aishwaryanr/awesome-generative-ai-guide/blob/main/free_courses/Applied_LLMs_Mastery_2024/week8_advanced_features.md)**\n\n- LLM lifecycle and LLMOps\n- LLM Monitoring and Observability\n- Deployment strategies\n\n🗓️\\*Week 9 [March 11 2024]**\\*: [Challenges with LLMs](https://github.com/aishwaryanr/awesome-generative-ai-guide/blob/main/free_courses/Applied_LLMs_Mastery_2024/week9_challenges_with_llms.md)**\n\n- Scaling Challenges\n- Behavioral Challenges\n- Future directions\n\n🗓️\\*Week 10 [March 18 2024]**\\*: [Emerging Research Trends](https://github.com/aishwaryanr/awesome-generative-ai-guide/blob/main/free_courses/Applied_LLMs_Mastery_2024/week10_research_trends.md)**\n\n- Smaller and more performant models\n- Multimodal models\n- LLM Alignment\n\n🗓️*Week 11 *Bonus\\* [March 25 2024]**\\*: [Foundations](https://github.com/aishwaryanr/awesome-generative-ai-guide/blob/main/free_courses/Applied_LLMs_Mastery_2024/week11_foundations.md)**\n\n- Generative Models Foundations\n- Self-Attention and Transformers\n- Neural Networks for Language\n\n---\n\n#### :book: List of Free GenAI Courses\n\n##### LLM Basics and Foundations\n\n1. [Large Language Models](https://rycolab.io/classes/llm-s23/) by ETH Zurich\n\n2. [Understanding Large Language Models](https://www.cs.princeton.edu/courses/archive/fall22/cos597G/) by Princeton\n\n3. [Transformers course](https://huggingface.co/learn/nlp-course/chapter1/1) by Huggingface\n\n4. [NLP course](https://huggingface.co/learn/nlp-course/chapter1/1) by Huggingface\n\n5. [CS324 - Large Language Models](https://stanford-cs324.github.io/winter2022/) by Stanford\n\n6. [Generative AI with Large Language Models](https://www.coursera.org/learn/generative-ai-with-llms) by Coursera\n\n7. [Introduction to Generative AI](https://www.coursera.org/learn/introduction-to-generative-ai) by Coursera\n\n8. [Generative AI Fundamentals](https://www.cloudskillsboost.google/paths/118/course_templates/556) by Google Cloud\n9. [5-Day Gen AI Intensive Course](https://www.youtube.com/watch?v=kpRyiJUUFxY\u0026list=PLqFaTIg4myu-b1PlxitQdY0UYIbys-2es) by Google \u0026 Kaggle\n\n10. [Introduction to Large Language Models](https://www.cloudskillsboost.google/paths/118/course_templates/539) by Google Cloud\n11. [Introduction to Generative AI](https://www.cloudskillsboost.google/paths/118/course_templates/536) by Google Cloud\n12. [Generative AI Concepts](https://www.datacamp.com/courses/generative-ai-concepts) by DataCamp (Daniel Tedesco Data Lead @ Google)\n13. [1 Hour Introduction to LLM (Large Language Models)](https://www.youtube.com/watch?v=xu5_kka-suc) by WeCloudData\n14. [LLM Foundation Models from the Ground Up | Primer](https://www.youtube.com/watch?v=W0c7jQezTDw\u0026list=PLTPXxbhUt-YWjMCDahwdVye8HW69p5NYS) by Databricks\n15. [Generative AI Explained](https://courses.nvidia.com/courses/course-v1:DLI+S-FX-07+V1/) by Nvidia\n16. [Transformer Models and BERT Model](https://www.cloudskillsboost.google/course_templates/538) by Google Cloud\n17. [Generative AI Learning Plan for Decision Makers](https://explore.skillbuilder.aws/learn/public/learning_plan/view/1909/generative-ai-learning-plan-for-decision-makers) by AWS\n18. [Introduction to Responsible AI](https://www.cloudskillsboost.google/course_templates/554) by Google Cloud\n19. [Fundamentals of Generative AI](https://learn.microsoft.com/en-us/training/modules/fundamentals-generative-ai/) by Microsoft Azure\n20. [Generative AI for Beginners](https://github.com/microsoft/generative-ai-for-beginners?WT.mc_id=academic-122979-leestott) by Microsoft\n21. [ChatGPT for Beginners: The Ultimate Use Cases for Everyone](https://www.udemy.com/course/chatgpt-for-beginners-the-ultimate-use-cases-for-everyone/) by Udemy\n22. [[1hr Talk] Intro to Large Language Models](https://www.youtube.com/watch?v=zjkBMFhNj_g) by Andrej Karpathy\n23. [ChatGPT for Everyone](https://learnprompting.org/courses/chatgpt-for-everyone) by Learn Prompting\n24. [Large Language Models (LLMs) (In English)](https://www.youtube.com/playlist?list=PLxlkzujLkmQ9vMaqfvqyfvZV_o8EqjAk7) by Kshitiz Verma (JK Lakshmipat University, Jaipur, India)\n25. [Generative AI for Beginners](https://codekidz.ai/lesson-intro/generative-a-362093) By CodeKidz, based on Microsoft's open sourced course.\n\n##### Building LLM Applications\n\n1. [LLMOps: Building Real-World Applications With Large Language Models](https://www.udacity.com/course/building-real-world-applications-with-large-language-models--cd13455) by Udacity\n\n2. [Full Stack LLM Bootcamp](https://fullstackdeeplearning.com/llm-bootcamp/) by FSDL\n\n3. [Generative AI for beginners](https://github.com/microsoft/generative-ai-for-beginners/tree/main) by Microsoft\n\n4. [Large Language Models: Application through Production](https://www.edx.org/learn/computer-science/databricks-large-language-models-application-through-production) by Databricks\n\n5. [Generative AI Foundations](https://www.youtube.com/watch?v=oYm66fHqHUM\u0026list=PLhr1KZpdzukf-xb0lmiU3G89GJXaDbAIF) by AWS\n\n6. [Introduction to Generative AI Community Course](https://www.youtube.com/watch?v=ajWheP8ZD70\u0026list=PLmQAMKHKeLZ-iTT-E2kK9uePrJ1Xua9VL) by ineuron\n\n7. [LLM University](https://docs.cohere.com/docs/llmu) by Cohere\n8. [LLM Learning Lab](https://lightning.ai/pages/llm-learning-lab/) by Lightning AI\n9. [LangChain for LLM Application Development](https://learn.deeplearning.ai/login?redirect_course=langchain\u0026callbackUrl=https%3A%2F%2Flearn.deeplearning.ai%2Fcourses%2Flangchain) by Deeplearning.AI\n10. [LLMOps](https://learn.deeplearning.ai/llmops) by DeepLearning.AI\n11. [Automated Testing for LLMOps](https://learn.deeplearning.ai/automated-testing-llmops) by DeepLearning.AI\n12. [Building Generative AI Applications Using Amazon Bedrock](https://explore.skillbuilder.aws/learn/course/external/view/elearning/17904/building-generative-ai-applications-using-amazon-bedrock-aws-digital-training) by AWS\n13. [Efficiently Serving LLMs](https://learn.deeplearning.ai/courses/efficiently-serving-llms/lesson/1/introduction) by DeepLearning.AI\n14. [Building Systems with the ChatGPT API](https://www.deeplearning.ai/short-courses/building-systems-with-chatgpt/) by DeepLearning.AI\n15. [Serverless LLM apps with Amazon Bedrock](https://www.deeplearning.ai/short-courses/serverless-llm-apps-amazon-bedrock/) by DeepLearning.AI\n16. [Building Applications with Vector Databases](https://www.deeplearning.ai/short-courses/building-applications-vector-databases/) by DeepLearning.AI\n17. [Automated Testing for LLMOps](https://www.deeplearning.ai/short-courses/automated-testing-llmops/) by DeepLearning.AI\n18. [Build LLM Apps with LangChain.js](https://www.deeplearning.ai/short-courses/build-llm-apps-with-langchain-js/) by DeepLearning.AI\n19. [Advanced Retrieval for AI with Chroma](https://www.deeplearning.ai/short-courses/advanced-retrieval-for-ai/) by DeepLearning.AI\n20. [Operationalizing LLMs on Azure](https://www.coursera.org/learn/llmops-azure) by Coursera\n21. [Generative AI Full Course – Gemini Pro, OpenAI, Llama, Langchain, Pinecone, Vector Databases \u0026 More](https://www.youtube.com/watch?v=mEsleV16qdo) by freeCodeCamp.org\n22. [Training \u0026 Fine-Tuning LLMs for Production](https://learn.activeloop.ai/courses/llms) by Activeloop\n    \n\n##### Prompt Engineering, RAG and Fine-Tuning\n\n1. [LangChain \u0026 Vector Databases in Production](https://www.youtube.com/redirect?event=video_description\u0026redir_token=QUFFLUhqbVhnQW8xNDdhSU9IUDVLXzFhV2N0UkNRMkZrQXxBQ3Jtc0traUxHMzZJcGJQYjlyckYxaGxYVWlsOFNGUFlFVEdhNzdjTWpPUlQ2TF9XczRqNkxMVGpJTnd5YmYzV0prQ0IwZURNcHhIZ3h1Z051VTl5MXBBLUN0dkM0NHRkQTFua1Jpc0VCRFJUb0ZQZG95b0JqMA\u0026q=https%3A%2F%2Flearn.activeloop.ai%2Fcourses%2Flangchain\u0026v=gKUTDC13jys) by Activeloop\n\n2. [Reinforcement Learning from Human Feedback](https://learn.deeplearning.ai/reinforcement-learning-from-human-feedback) by DeepLearning.AI\n\n3. [Building Applications with Vector Databases](https://learn.deeplearning.ai/building-applications-vector-databases) by DeepLearning.AI\n\n4. [Finetuning Large Language Models](https://learn.deeplearning.ai/finetuning-large-language-models) by Deeplearning.AI\n5. [LangChain: Chat with Your Data](http://learn.deeplearning.ai/langchain-chat-with-your-data/) by Deeplearning.AI\n\n6. [Building Systems with the ChatGPT API](https://learn.deeplearning.ai/chatgpt-building-system) by Deeplearning.AI\n7. [Prompt Engineering with Llama 2](https://www.deeplearning.ai/short-courses/prompt-engineering-with-llama-2/) by Deeplearning.AI\n8. [Building Applications with Vector Databases](https://learn.deeplearning.ai/building-applications-vector-databases) by Deeplearning.AI\n9. [ChatGPT Prompt Engineering for Developers](https://learn.deeplearning.ai/chatgpt-prompt-eng/lesson/1/introduction) by Deeplearning.AI\n10. [Advanced RAG Orchestration series](https://www.youtube.com/watch?v=CeDS1yvw9E4) by LlamaIndex\n11. [Prompt Engineering Specialization](https://www.coursera.org/specializations/prompt-engineering) by Coursera\n12. [Augment your LLM Using Retrieval Augmented Generation](https://courses.nvidia.com/courses/course-v1:NVIDIA+S-FX-16+v1/) by Nvidia\n13. [Knowledge Graphs for RAG](https://www.deeplearning.ai/short-courses/knowledge-graphs-rag/) by Deeplearning.AI\n14. [Open Source Models with Hugging Face](https://www.deeplearning.ai/short-courses/open-source-models-hugging-face/) by Deeplearning.AI\n15. [Vector Databases: from Embeddings to Applications](https://www.deeplearning.ai/short-courses/vector-databases-embeddings-applications/) by Deeplearning.AI\n16. [Understanding and Applying Text Embeddings](https://www.deeplearning.ai/short-courses/google-cloud-vertex-ai/) by Deeplearning.AI\n17. [JavaScript RAG Web Apps with LlamaIndex](https://www.deeplearning.ai/short-courses/javascript-rag-web-apps-with-llamaindex/) by Deeplearning.AI\n18. [Quantization Fundamentals with Hugging Face](https://www.deeplearning.ai/short-courses/quantization-fundamentals-with-hugging-face/) by Deeplearning.AI\n19. [Preprocessing Unstructured Data for LLM Applications](https://www.deeplearning.ai/short-courses/preprocessing-unstructured-data-for-llm-applications/) by Deeplearning.AI\n20. [Retrieval Augmented Generation for Production with LangChain \u0026 LlamaIndex](https://learn.activeloop.ai/courses/rag) by Activeloop\n21. [Quantization in Depth](https://www.deeplearning.ai/short-courses/quantization-in-depth/) by Deeplearning.AI\n\n##### Evaluation\n\n1. [Building and Evaluating Advanced RAG Applications](https://learn.deeplearning.ai/building-evaluating-advanced-rag) by DeepLearning.AI\n2. [Evaluating and Debugging Generative AI Models Using Weights and Biases](https://learn.deeplearning.ai/evaluating-debugging-generative-ai) by Deeplearning.AI\n3. [Quality and Safety for LLM Applications](https://www.deeplearning.ai/short-courses/quality-safety-llm-applications/) by Deeplearning.AI\n4. [Red Teaming LLM Applications](https://www.deeplearning.ai/short-courses/red-teaming-llm-applications/?utm_campaign=giskard-launch\u0026utm_medium=headband\u0026utm_source=dlai-homepage) by Deeplearning.AI\n\n##### Multimodal\n\n1. [How Diffusion Models Work](https://www.deeplearning.ai/short-courses/how-diffusion-models-work/) by DeepLearning.AI\n2. [How to Use Midjourney, AI Art and ChatGPT to Create an Amazing Website](https://www.youtube.com/watch?v=5wdCev86RYE) by Brad Hussey\n3. [Build AI Apps with ChatGPT, DALL-E and GPT-4](https://scrimba.com/learn/buildaiapps) by Scrimba\n4. [11-777: Multimodal Machine Learning](https://www.youtube.com/playlist?list=PL-Fhd_vrvisNM7pbbevXKAbT_Xmub37fA) by Carnegie Mellon University\n5. [Prompt Engineering for Vision Models](https://www.deeplearning.ai/short-courses/prompt-engineering-for-vision-models/) by Deeplearning.AI\n\n##### Agents\n1. [Building RAG Agents with LLMs](https://courses.nvidia.com/courses/course-v1:DLI+S-FX-15+V1/) by Nvidia\n2. [Functions, Tools and Agents with LangChain](https://learn.deeplearning.ai/functions-tools-agents-langchain) by Deeplearning.AI\n3. [AI Agents in LangGraph](https://www.deeplearning.ai/short-courses/ai-agents-in-langgraph/) by Deeplearning.AI\n4. [AI Agentic Design Patterns with AutoGen](https://www.deeplearning.ai/short-courses/ai-agentic-design-patterns-with-autogen/) by Deeplearning.AI\n5. [Multi AI Agent Systems with crewAI](https://www.deeplearning.ai/short-courses/multi-ai-agent-systems-with-crewai/) by Deeplearning.AI\n6. [Building Agentic RAG with LlamaIndex](https://www.deeplearning.ai/short-courses/building-agentic-rag-with-llamaindex/) by Deeplearning.AI\n7. [LLM Observability: Agents, Tools, and Chains](https://courses.arize.com/p/agents-tools-and-chains) by Arize AI\n8. [Building Agentic RAG with LlamaIndex](https://www.deeplearning.ai/short-courses/building-agentic-rag-with-llamaindex/) by Deeplearning.AI\n9. [Agents Tools \u0026 Function Calling with Amazon Bedrock (How-to)](https://www.youtube.com/watch?app=desktop\u0026v=2L_XE6g3atI) by AWS Developers\n10. [ChatGPT \u0026 Zapier: Agentic AI for Everyone](https://www.coursera.org/learn/agentic-ai-chatgpt-zapier) by Coursera\n11. [Multi-Agent Systems with AutoGen](https://www.manning.com/books/multi-agent-systems-with-autogen) by Victor Dibia [Book]\n12. [Large Language Model Agents MOOC, Fall 2024](https://llmagents-learning.org/f24) by Dawn Song \u0026 Xinyun Chen – A comprehensive course covering foundational and advanced topics on LLM agents.\n13. [CS294/194-196 Large Language Model Agents](https://rdi.berkeley.edu/llm-agents/f24) by UC Berkeley\n\n\n\n\n\n#### Miscellaneous\n\n1. [Avoiding AI Harm](https://www.coursera.org/learn/avoiding-ai-harm) by Coursera\n2. [Developing AI Policy](https://www.coursera.org/learn/developing-ai-policy) by Coursera\n\n---\n\n## :paperclip: Resources\n\n- [ICLR 2024 Paper Summaries](https://areganti.notion.site/06f0d4fe46a94d62bff2ae001cfec22c?v=d501ca62e4b745768385d698f173ae14)\n\n---\n\n## :computer: Interview Prep\n\n#### Topic wise Questions:\n\n1. [Common GenAI Interview Questions](https://github.com/aishwaryanr/awesome-generative-ai-guide/blob/main/interview_prep/60_gen_ai_questions.md)\n2. Prompting and Prompt Engineering\n3. Model Fine-Tuning\n4. Model Evaluation\n5. MLOps for GenAI\n6. Generative Models Foundations\n7. Latest Research Trends\n\n#### GenAI System Design (Coming Soon):\n\n1. Designing an LLM-Powered Search Engine\n2. Building a Customer Support Chatbot\n3. Building a system for natural language interaction with your data.\n4. Building an AI Co-pilot\n5. Designing a Custom Chatbot for Q/A on Multimodal Data (Text, Images, Tables, CSV Files)\n6. Building an Automated Product Description and Image Generation System for E-commerce\n\n---\n\n## :notebook: Code Notebooks\n\n#### RAG Tutorials\n\n- [AWS Bedrock Workshop Tutorials](https://github.com/aws-samples/amazon-bedrock-workshop) by Amazon Web Services\n- [Langchain Tutorials](https://github.com/gkamradt/langchain-tutorials) by gkamradt\n- [LLM Applications for production](https://github.com/ray-project/llm-applications/tree/main) by ray-project\n- [LLM tutorials](https://github.com/ollama/ollama/tree/main/examples) by Ollama\n- [LLM Hub](https://github.com/mallahyari/llm-hub) by mallahyari\n- [RAG cookbook](https://docs.camel-ai.org/cookbooks/agents_with_rag.html) by CAMEL-AI\n\n#### Fine-Tuning Tutorials\n\n- [LLM Fine-tuning tutorials](https://github.com/ashishpatel26/LLM-Finetuning) by ashishpatel26\n- [PEFT](https://github.com/huggingface/peft/tree/main/examples) example notebooks by Huggingface\n- [Free LLM Fine-Tuning Notebooks](https://levelup.gitconnected.com/14-free-large-language-models-fine-tuning-notebooks-532055717cb7) by Youssef Hosni\n\n\n#### Comprehensive LLM Code Repositories \n- [LLM-PlayLab](https://github.com/Sakil786/LLM-PlayLab) This playlab encompasses a multitude of projects crafted through the utilization of Transformer Models\n\n\n---\n\n## :black_nib: Contributing\n\nIf you want to add to the repository or find any issues, please feel free to raise a PR and ensure correct placement within the relevant section or category.\n\n---\n\n## :pushpin: Cite Us\n\nTo cite this guide, use the below format:\n\n```\n@article{areganti_generative_ai_guide,\nauthor = {Reganti, Aishwarya Naresh},\njournal = {https://github.com/aishwaryanr/awesome-generative-ai-resources},\nmonth = {01},\ntitle = {{Generative AI Guide}},\nyear = {2024}\n}\n```\n\n## License\n\n[MIT License]\n\n\n\n\u003csup\u003e**\u003c/sup\u003e This section is sponsored. We do not endorse or guarantee the product/service and are not responsible for any issues arising from its use. Please evaluate and use at your discretion.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Faishwaryanr%2Fawesome-generative-ai-guide","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Faishwaryanr%2Fawesome-generative-ai-guide","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Faishwaryanr%2Fawesome-generative-ai-guide/lists"}