--- title: "Large-Language-Model-Notebooks-Course vs Awesome-LLM-in-Social-Science" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/peremartra-large-language-model-notebooks-course-vs-valuebyte-ai-awesome-llm-in-social-science" tools: ["peremartra-large-language-model-notebooks-course", "valuebyte-ai-awesome-llm-in-social-science"] --- # Large-Language-Model-Notebooks-Course vs Awesome-LLM-in-Social-Science *GraphCanon updated Aug 15, 2026* ## Verdict Pick Large-Language-Model-Notebooks-Course if a developing, comprehensive hands-on course covering a broad array of LLM tools and applications from OpenAI and Hugging Face; pick Awesome-LLM-in-Social-Science if curate research papers on LLM applications in social science, covering topics like alignment, economics, policy, psychology, and more. [Large-Language-Model-Notebooks-Course](https://medium.com/@peremartra/list/large-language-models-practical-course-66b4ce5943ce) reports 1.8k GitHub stars, 447 forks, and 0 open issues, last pushed May 28, 2026. [Awesome-LLM-in-Social-Science](https://github.com/ValueByte-AI/Awesome-LLM-in-Social-Science) has 639 stars, 48 forks, and 0 open issues, last pushed Jun 8, 2026. Figures are from public GitHub metadata via [Large-Language-Model-Notebooks-Course's repository](https://github.com/peremartra/Large-Language-Model-Notebooks-Course) and [Awesome-LLM-in-Social-Science's repository](https://github.com/ValueByte-AI/Awesome-LLM-in-Social-Science). | | [Large-Language-Model-Notebooks-Course](/tools/peremartra-large-language-model-notebooks-course.md) | [Awesome-LLM-in-Social-Science](/tools/valuebyte-ai-awesome-llm-in-social-science.md) | | --- | --- | --- | | Tagline | Practical course about Large Language Models | Awesome papers involving LLMs in Social Science | | Stars | 1,821 | 639 | | Forks | 447 | 48 | | Open issues | 0 | 0 | | Language | Jupyter Notebook | - | | Adopt for | A developing, comprehensive hands-on course covering a broad array of LLM tools and applications from OpenAI and Hugging Face. | Curate research papers on LLM applications in social science, covering topics like alignment, economics, policy, psychology, and more. | | Persona | - | - | | Runtime | - | - | | License | MIT | MIT | | Categories | Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training | Evaluation & Observability, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [Large-Language-Model-Notebooks-Course](/tools/peremartra-large-language-model-notebooks-course.md) | [Awesome-LLM-in-Social-Science](/tools/valuebyte-ai-awesome-llm-in-social-science.md) | | --- | --- | --- | | Days since push | 79d | 49d | | Stars delta | +3 (30d) | Unknown | | Open issues delta | 0 (30d) | Unknown | | Owner type | User | Organization | | Full report | [trust report](/tools/peremartra-large-language-model-notebooks-course/trust.md) | [trust report](/tools/valuebyte-ai-awesome-llm-in-social-science/trust.md) | ## Decision facts: Large-Language-Model-Notebooks-Course - **Adopt for:** A developing, comprehensive hands-on course covering a broad array of LLM tools and applications from OpenAI and Hugging Face. ## Decision facts: Awesome-LLM-in-Social-Science - **Adopt for:** Curate research papers on LLM applications in social science, covering topics like alignment, economics, policy, psychology, and more. ## Choose when ### Choose Large-Language-Model-Notebooks-Course if… - Tags unique to Large-Language-Model-Notebooks-Course: chatbots, fine-tuning-llm, huggingface, langchain. - Also covers Inference & Serving, LLM Frameworks. - You're seeking an evolving curriculum with projects that apply Large Language Model techniques from various libraries. ### Choose Awesome-LLM-in-Social-Science if… - Tags unique to Awesome-LLM-in-Social-Science: alignment, economics, llm-agent, llm-evaluation. - Need to explore academic insights into LLM impacts on specific social areas - More recently updated (last pushed Jun 8, 2026). ## When NOT to use Large-Language-Model-Notebooks-Course - Seeking a complete, finalized course where all content is available for immediate use without future updates. - Looking exclusively for theory; the course emphasizes practical application over theoretical depth. ## When NOT to use Awesome-LLM-in-Social-Science - Looking for a hands-on coding or practical implementation guide of LLMs - In need of real-time data analysis tools for immediate social science research outcomes ## Common questions ### What is the difference between Large-Language-Model-Notebooks-Course and Awesome-LLM-in-Social-Science? Large-Language-Model-Notebooks-Course: Practical course about Large Language Models. Awesome-LLM-in-Social-Science: Awesome papers involving LLMs in Social Science. See the comparison table for live GitHub stats and shared categories. ### When should I choose Large-Language-Model-Notebooks-Course over Awesome-LLM-in-Social-Science? Choose Large-Language-Model-Notebooks-Course over Awesome-LLM-in-Social-Science when Tags unique to Large-Language-Model-Notebooks-Course: chatbots, fine-tuning-llm, huggingface, langchain; Also covers Inference & Serving, LLM Frameworks; You're seeking an evolving curriculum with projects that apply Large Language Model techniques from various libraries. ### When should I choose Awesome-LLM-in-Social-Science over Large-Language-Model-Notebooks-Course? Choose Awesome-LLM-in-Social-Science over Large-Language-Model-Notebooks-Course when Tags unique to Awesome-LLM-in-Social-Science: alignment, economics, llm-agent, llm-evaluation; Need to explore academic insights into LLM impacts on specific social areas; More recently updated (last pushed Jun 8, 2026). ### When should I avoid Large-Language-Model-Notebooks-Course? Seeking a complete, finalized course where all content is available for immediate use without future updates. Looking exclusively for theory; the course emphasizes practical application over theoretical depth. ### When should I avoid Awesome-LLM-in-Social-Science? Looking for a hands-on coding or practical implementation guide of LLMs In need of real-time data analysis tools for immediate social science research outcomes ### Is Large-Language-Model-Notebooks-Course or Awesome-LLM-in-Social-Science more popular on GitHub? Large-Language-Model-Notebooks-Course has more GitHub stars (1,821 vs 639). Stars measure visibility, not whether either tool fits your constraints. ### Are Large-Language-Model-Notebooks-Course and Awesome-LLM-in-Social-Science open source? Yes - both are open-source projects on GitHub (Large-Language-Model-Notebooks-Course: MIT, Awesome-LLM-in-Social-Science: MIT). ### Where can I find alternatives to Large-Language-Model-Notebooks-Course or Awesome-LLM-in-Social-Science? GraphCanon lists graph-backed alternatives at [Large-Language-Model-Notebooks-Course alternatives](/tools/peremartra-large-language-model-notebooks-course/alternatives) and [Awesome-LLM-in-Social-Science alternatives](/tools/valuebyte-ai-awesome-llm-in-social-science/alternatives) ([Large-Language-Model-Notebooks-Course markdown twin](/tools/peremartra-large-language-model-notebooks-course/alternatives.md), [Awesome-LLM-in-Social-Science markdown twin](/tools/valuebyte-ai-awesome-llm-in-social-science/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/peremartra-large-language-model-notebooks-course-vs-valuebyte-ai-awesome-llm-in-social-science.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, Large-Language-Model-Notebooks-Course or Awesome-LLM-in-Social-Science? Large-Language-Model-Notebooks-Course: Steady. Awesome-LLM-in-Social-Science: Steady. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for Large-Language-Model-Notebooks-Course and Awesome-LLM-in-Social-Science? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [Large-Language-Model-Notebooks-Course trust report](/tools/peremartra-large-language-model-notebooks-course/trust); [Awesome-LLM-in-Social-Science trust report](/tools/valuebyte-ai-awesome-llm-in-social-science/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=peremartra-large-language-model-notebooks-course`](/api/graphcanon/graph?tool=peremartra-large-language-model-notebooks-course) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_