---
title: "AI-For-Beginners vs human-eval"
type: "comparison"
canonical_url: "https://www.graphcanon.com/compare/microsoft-ai-for-beginners-vs-openai-human-eval"
tools: ["microsoft-ai-for-beginners", "openai-human-eval"]
---

# AI-For-Beginners vs human-eval

*GraphCanon updated Jul 11, 2026*

## Verdict

Pick AI-For-Beginners when aI-For-Beginners is primarily Jupyter Notebook; human-eval is Python; pick human-eval when human-eval is primarily Python; AI-For-Beginners is Jupyter Notebook.

[AI-For-Beginners](https://github.com/microsoft/AI-For-Beginners) reports 52k GitHub stars, 11k forks, and 4 open issues, last pushed Jul 8, 2026. [human-eval](https://github.com/openai/human-eval) has 3.3k stars, 449 forks, and 42 open issues, last pushed Jan 17, 2025. Figures are from public GitHub metadata via [AI-For-Beginners's repository](https://github.com/microsoft/AI-For-Beginners) and [human-eval's repository](https://github.com/openai/human-eval).

| | [AI-For-Beginners](/tools/microsoft-ai-for-beginners.md) | [human-eval](/tools/openai-human-eval.md) |
| --- | --- | --- |
| Tagline | 12 Weeks, 24 Lessons, AI for All! | Code for the paper "Evaluating Large Language Models Trained on Code" |
| Stars | 52,098 | 3,294 |
| Forks | 10,536 | 449 |
| Open issues | 4 | 42 |
| Language | Jupyter Notebook | Python |
| Adopt for | - | - |
| Persona | - | - |
| Runtime | - | - |
| License | MIT | MIT |
| Categories | Vector Databases, Model Training, Computer Vision | Model Training, LLM Frameworks, Evaluation & Observability |

## Trust and health

_Sourced signals - not a safety guarantee. No winner column._

| | [AI-For-Beginners](/tools/microsoft-ai-for-beginners.md) | [human-eval](/tools/openai-human-eval.md) |
| --- | --- | --- |
| Maintenance | Very active (96%) | Dormant (18%) |
| Days since push | 2d | 540d |
| Open issues (now) | 4 | 42 |
| Security scan | 3 low (3 low) | No criticals |
| Full report | [trust report](/tools/microsoft-ai-for-beginners/trust.md) | [trust report](/tools/openai-human-eval/trust.md) |

## Choose when

### Choose AI-For-Beginners if…

- AI-For-Beginners is primarily Jupyter Notebook; human-eval is Python.
- Tags unique to AI-For-Beginners: deep-learning, microsoft-for-beginners, ai, artificial-intelligence.
- Also covers Vector Databases, Computer Vision.

### Choose human-eval if…

- human-eval is primarily Python; AI-For-Beginners is Jupyter Notebook.
- Tags unique to human-eval: python.
- Also covers LLM Frameworks, Evaluation & Observability.

## When NOT to use AI-For-Beginners

- Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.
- Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.

## When NOT to use human-eval

- Last GitHub push was 540 days ago (dormant maintenance, Jan 17, 2025). Validate activity before betting a new project on human-eval.
- Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
- Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers.

## Common questions

### What is the difference between AI-For-Beginners and human-eval?

AI-For-Beginners: 12 Weeks, 24 Lessons, AI for All!. human-eval: Code for the paper "Evaluating Large Language Models Trained on Code". See the comparison table for live GitHub stats and shared categories.

### When should I choose AI-For-Beginners over human-eval?

Choose AI-For-Beginners over human-eval when AI-For-Beginners is primarily Jupyter Notebook; human-eval is Python; Tags unique to AI-For-Beginners: deep-learning, microsoft-for-beginners, ai, artificial-intelligence; Also covers Vector Databases, Computer Vision.

### When should I choose human-eval over AI-For-Beginners?

Choose human-eval over AI-For-Beginners when human-eval is primarily Python; AI-For-Beginners is Jupyter Notebook; Tags unique to human-eval: python; Also covers LLM Frameworks, Evaluation & Observability.

### When should I avoid AI-For-Beginners?

Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.

### When should I avoid human-eval?

Last GitHub push was 540 days ago (dormant maintenance, Jan 17, 2025). Validate activity before betting a new project on human-eval. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers.

### Is AI-For-Beginners or human-eval more popular on GitHub?

AI-For-Beginners has more GitHub stars (52,098 vs 3,294). Stars measure visibility, not whether either tool fits your constraints.

### Are AI-For-Beginners and human-eval open source?

Yes - both are open-source projects on GitHub (AI-For-Beginners: MIT, human-eval: MIT).

### Where can I find alternatives to AI-For-Beginners or human-eval?

GraphCanon lists graph-backed alternatives at [AI-For-Beginners alternatives](/tools/microsoft-ai-for-beginners/alternatives) and [human-eval alternatives](/tools/openai-human-eval/alternatives) ([AI-For-Beginners markdown twin](/tools/microsoft-ai-for-beginners/alternatives.md), [human-eval markdown twin](/tools/openai-human-eval/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/microsoft-ai-for-beginners-vs-openai-human-eval.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.

### Which is better maintained, AI-For-Beginners or human-eval?

AI-For-Beginners: Very active. human-eval: Dormant. 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 AI-For-Beginners and human-eval?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [AI-For-Beginners trust report](/tools/microsoft-ai-for-beginners/trust); [human-eval trust report](/tools/openai-human-eval/trust).

---

**Machine-readable endpoints**

- JSON: [`/api/graphcanon/graph?tool=microsoft-ai-for-beginners`](/api/graphcanon/graph?tool=microsoft-ai-for-beginners)
- 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/_