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This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters. Learn more about bidirectional Unicode charactersOriginal file line number Diff line number Diff line change @@ -30,11 +30,11 @@ This project is **open source** and community-driven. If you'd like to contribut - Fix broken links or typos - Help add more projects For detailed instructions on how to contribute, check the **[Contributing Guide](https://github.com/DocParseAI/Ai-Engineering-Roadmap/blob/main/CONTRIBUTING.md)**. ### **Project Repository** The full curriculum is hosted on GitHub, and you can explore it, contribute, or learn at your own pace: [**Open Source AI Engineering Curriculum**](https://github.com/DocParseAI/Ai-Engineering-Roadmap) This curriculum is **free** and designed to keep pace with the most current advancements in AI, ensuring that learners stay ahead in the field. -
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This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters. Learn more about bidirectional Unicode charactersOriginal file line number Diff line number Diff line change @@ -0,0 +1,41 @@ # 🎓 Open Source AI Engineering Curriculum Welcome to the **Open Source AI Engineering Curriculum**, a complete path for anyone aspiring to become a self-taught AI engineer — from basic programming skills to mastering cutting-edge AI techniques like Large Language Models, Agentic AI, and Prompt Engineering. This curriculum is designed for self-learners and includes all the resources needed to become proficient in AI engineering, powered by **free and open-source** materials. ### **Why This Project Exists** The field of Artificial Intelligence is rapidly evolving, but access to structured, high-quality AI education often comes with high costs. This curriculum aims to provide **free and open** resources to anyone eager to learn, covering essential AI engineering skills, from basic programming to deploying advanced models. ### **Curriculum Overview** The curriculum is divided into multiple sections: - **Programming**: Python, Git, Data Structures - **Mathematics**: Linear Algebra, Probability, Statistics - **Machine Learning**: Supervised, Unsupervised, Model Evaluation - **Deep Learning**: Neural Networks, CNNs, RNNs, Transformers - **Specializations**: Natural Language Processing (NLP), Computer Vision, Reinforcement Learning (RL) - **Modern AI**: Large Language Models (LLMs), Agentic AI, Retrieval-Augmented Generation (RAG), Prompt Engineering - **Capstone Projects**: Real-world AI projects Each section is designed to progressively build knowledge and culminate in hands-on experience with practical projects. ### **Guided Curriculum Path** The curriculum is designed to be followed step-by-step, but you can also jump to any section you're interested in. Each path comes with a list of recommended resources, including free online courses, textbooks, and project ideas. ### **How to Contribute** This project is **open source** and community-driven. If you'd like to contribute, you can: - Suggest additional resources - Improve existing content - Fix broken links or typos - Help add more projects For detailed instructions on how to contribute, check the **[Contributing Guide](https://github.com/your-username/ossu-ai-engineering/blob/main/CONTRIBUTING.md)**. ### **Project Repository** The full curriculum is hosted on GitHub, and you can explore it, contribute, or learn at your own pace: [**Open Source AI Engineering Curriculum**](https://github.com/your-username/ossu-ai-engineering) This curriculum is **free** and designed to keep pace with the most current advancements in AI, ensuring that learners stay ahead in the field. Let's build a community of learners and contribute to the growth of AI engineering knowledge!