---
title: "start-llms vs AI-For-Beginners"
type: "comparison"
canonical_url: "https://www.graphcanon.com/compare/louisfb01-start-llms-vs-microsoft-ai-for-beginners"
tools: ["louisfb01-start-llms", "microsoft-ai-for-beginners"]
---

# start-llms vs AI-For-Beginners

*GraphCanon updated Jul 12, 2026*

## Verdict

Pick start-llms when tags unique to start-llms: llama, fine-tuning, large-language-models, rag; pick AI-For-Beginners when tags unique to AI-For-Beginners: deep-learning, microsoft-for-beginners, artificial-intelligence, machine-learning.

[start-llms](https://www.louisbouchard.ai/from-zero-to-hero-with-llms/) reports 978 GitHub stars, 127 forks, and 2 open issues, last pushed Jan 23, 2026. [AI-For-Beginners](https://github.com/microsoft/AI-For-Beginners) has 52k stars, 11k forks, and 4 open issues, last pushed Jul 8, 2026. Figures are from public GitHub metadata via [start-llms's repository](https://github.com/louisfb01/start-llms) and [AI-For-Beginners's repository](https://github.com/microsoft/AI-For-Beginners).

| | [start-llms](/tools/louisfb01-start-llms.md) | [AI-For-Beginners](/tools/microsoft-ai-for-beginners.md) |
| --- | --- | --- |
| Tagline | A comprehensive guide for beginners to advance in LLM skills and stay current with industry developments. | 12 Weeks, 24 Lessons, AI for All! |
| Stars | 978 | 52,098 |
| Forks | 127 | 10,536 |
| Open issues | 2 | 4 |
| Language | - | Jupyter Notebook |
| Adopt for | A comprehensive beginner-friendly guide oriented towards developing Large Language Model (LLM) skills through the latest methods and industry practices. | - |
| Persona | - | - |
| Runtime | - | - |
| License | MIT | MIT |
| Categories | Model Training, Evaluation & Observability | Model Training, Vector Databases, Computer Vision |

## Trust and health

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

| | [start-llms](/tools/louisfb01-start-llms.md) | [AI-For-Beginners](/tools/microsoft-ai-for-beginners.md) |
| --- | --- | --- |
| Maintenance | Slowing (36%) | Very active (96%) |
| Days since push | 168d | 2d |
| Open issues (now) | 2 | 4 |
| Owner type | User | Organization |
| Security scan | No lockfile | 3 low (3 low) |
| Full report | [trust report](/tools/louisfb01-start-llms/trust.md) | [trust report](/tools/microsoft-ai-for-beginners/trust.md) |

## Decision facts: start-llms

- **Adopt for:** A comprehensive beginner-friendly guide oriented towards developing Large Language Model (LLM) skills through the latest methods and industry practices.

## Choose when

### Choose start-llms if…

- Tags unique to start-llms: llama, fine-tuning, large-language-models, rag.
- Also covers Evaluation & Observability.
- You are a newcomer to LLMs looking for an accessible introductory pathway.

### Choose AI-For-Beginners if…

- Tags unique to AI-For-Beginners: deep-learning, microsoft-for-beginners, artificial-intelligence, machine-learning.
- Also covers Vector Databases, Computer Vision.
- More GitHub stars (52k vs 978) - visibility, not fit.

## When NOT to use start-llms

- You already have advanced expertise or are a seasoned professional who prefers to dive deep into specialized areas immediately.
- Your primary objective is real-time collaboration features for model development teams, as the repository does not highlight these aspects.

## When NOT to use AI-For-Beginners

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

## Common questions

### What is the difference between start-llms and AI-For-Beginners?

start-llms: A comprehensive guide for beginners to advance in LLM skills and stay current with industry developments.. AI-For-Beginners: 12 Weeks, 24 Lessons, AI for All!. See the comparison table for live GitHub stats and shared categories.

### When should I choose start-llms over AI-For-Beginners?

Choose start-llms over AI-For-Beginners when Tags unique to start-llms: llama, fine-tuning, large-language-models, rag; Also covers Evaluation & Observability; You are a newcomer to LLMs looking for an accessible introductory pathway.

### When should I choose AI-For-Beginners over start-llms?

Choose AI-For-Beginners over start-llms when Tags unique to AI-For-Beginners: deep-learning, microsoft-for-beginners, artificial-intelligence, machine-learning; Also covers Vector Databases, Computer Vision; More GitHub stars (52k vs 978) - visibility, not fit.

### When should I avoid start-llms?

You already have advanced expertise or are a seasoned professional who prefers to dive deep into specialized areas immediately. Your primary objective is real-time collaboration features for model development teams, as the repository does not highlight these aspects.

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

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

### Is start-llms or AI-For-Beginners more popular on GitHub?

AI-For-Beginners has more GitHub stars (52,098 vs 978). Stars measure visibility, not whether either tool fits your constraints.

### Are start-llms and AI-For-Beginners open source?

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

### Where can I find alternatives to start-llms or AI-For-Beginners?

GraphCanon lists graph-backed alternatives at [start-llms alternatives](/tools/louisfb01-start-llms/alternatives) and [AI-For-Beginners alternatives](/tools/microsoft-ai-for-beginners/alternatives) ([start-llms markdown twin](/tools/louisfb01-start-llms/alternatives.md), [AI-For-Beginners markdown twin](/tools/microsoft-ai-for-beginners/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/louisfb01-start-llms-vs-microsoft-ai-for-beginners.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.

### Which is better maintained, start-llms or AI-For-Beginners?

start-llms: Slowing. AI-For-Beginners: Very active. 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 start-llms and AI-For-Beginners?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [start-llms trust report](/tools/louisfb01-start-llms/trust); [AI-For-Beginners trust report](/tools/microsoft-ai-for-beginners/trust).

---

**Machine-readable endpoints**

- JSON: [`/api/graphcanon/graph?tool=louisfb01-start-llms`](/api/graphcanon/graph?tool=louisfb01-start-llms)
- 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/_