Comparison
online-ml-university vs awesome
Verdict
Pick online-ml-university if online ML University is a curated list of free AI and ML courses from leading universities like Stanford, Harvard, MIT, and CMU; pick awesome if a curated collection of resources on a variety of technological topics, emphasizing hardware and robotics.
Markdown twin · online-ml-university alternatives · awesome alternatives
GraphCanon updated Oct 4, 2026
8views this month
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Trust & integrity
| Signal | online-ml-university | awesome |
|---|---|---|
| Maintenance | Dormant (892d since push) As of Sep 25, 2026 · github_public_v1 | Steady (32d since push) As of Oct 4, 2026 · github_public_v1 |
| Provenance | Not a fork · Personal account As of Sep 25, 2026 · github_public_v1 | Not a fork · Personal account As of Oct 4, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | No lockfile (source not queried) As of Sep 6, 2026 · deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Published findings As of Aug 16, 2026 · openssf-scorecard@v1 |
Tagline
- online-ml-university
- Curated list of free AI and ML courses from top universities
- awesome
- 😎 Awesome lists about all kinds of interesting topics
Stars
- online-ml-university
- 229
- awesome
- 514k
Forks
- online-ml-university
- 52
- awesome
- 37k
Open issues
- online-ml-university
- 0
- awesome
- 107
Language
- online-ml-university
- -
- awesome
- -
Adopt for
- online-ml-university
- Online ML University is a curated list of free AI and ML courses from leading universities like Stanford, Harvard, MIT, and CMU.
- awesome
- A curated collection of resources on a variety of technological topics, emphasizing hardware and robotics.
Persona
- online-ml-university
- -
- awesome
- -
Runtime
- online-ml-university
- -
- awesome
- -
License
- online-ml-university
- LGPL-2.1
- awesome
- CC0-1.0
Last pushed
- online-ml-university
- Apr 15, 2024
- awesome
- Sep 2, 2026
Categories
- online-ml-university
- Developer Tools
- awesome
- Developer Tools
Trust and health
Maintenance
- online-ml-university
- Dormant (18%)
- awesome
- Steady (60%)
Days since push
- online-ml-university
- 892d
- awesome
- 32d
Open issues (now)
- online-ml-university
- 0
- awesome
- 107
Stars delta
- online-ml-university
- +6 (30d)
- awesome
- +22k (30d)
Open issues delta
- online-ml-university
- 0 (30d)
- awesome
- +7 (30d)
deps.dev advisories
- online-ml-university
- Not queried
- awesome
- No lockfile (source not queried)
OpenSSF Scorecard
- online-ml-university
- Not queried
- awesome
- Published findings
Full report
- online-ml-university
- Trust report
- awesome
- Trust report
Choose online-ml-university if…
- License: online-ml-university is LGPL-2.1, awesome is CC0-1.0.
- Tags unique to online-ml-university: ai, artificial-intelligence, computer-science, computer-vision.
- When seeking detailed and structured online learning paths in data science, machine learning, deep learning, and other related fields from reputable universities
When NOT to use online-ml-university
- When your learning needs are focused on proprietary or specific to newer technologies not covered deeply by traditional universities
- If you require personalized guidance that is outside of the scope of available material from institutional courses
- In scenarios where certification or college credit from these institutions is required as the repository mainly aggregates free resources
Choose awesome if…
- License: awesome is CC0-1.0, online-ml-university is LGPL-2.1.
- Tags unique to awesome: awesome, awesome-list, lists, resources.
- When you need well-organized access to diverse technical subjects from IoT to robotics
When NOT to use awesome
- If seeking specific coding frameworks or libraries for software development rather than hardware-focused resources
- In scenarios requiring real-time interactive support or forums, as the content is static lists without active discussion
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (azminewasi/online-ml-university) · observed Sep 25, 2026
- GitHub forks (azminewasi/online-ml-university) · observed Sep 25, 2026
- Last push (azminewasi/online-ml-university) · observed Apr 15, 2024
- License file (LGPL-2.1) · observed Sep 25, 2026
- Decision facts (enrichment) · observed Jul 15, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (sindresorhus/awesome) · observed Oct 4, 2026
- GitHub forks (sindresorhus/awesome) · observed Oct 4, 2026
- Last push (sindresorhus/awesome) · observed Sep 2, 2026
- License file (CC0-1.0) · observed Oct 4, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: online-ml-university 229 · awesome 514k (synced Sep 25, 2026).
Common questions
- What is the difference between online-ml-university and awesome?
- online-ml-university: Curated list of free AI and ML courses from top universities. awesome: 😎 Awesome lists about all kinds of interesting topics. See the comparison table for live GitHub stats and shared categories.
- When should I choose online-ml-university over awesome?
- Choose online-ml-university over awesome when License: online-ml-university is LGPL-2.1, awesome is CC0-1.0; Tags unique to online-ml-university: ai, artificial-intelligence, computer-science, computer-vision; When seeking detailed and structured online learning paths in data science, machine learning, deep learning, and other related fields from reputable universities.
- When should I choose awesome over online-ml-university?
- Choose awesome over online-ml-university when License: awesome is CC0-1.0, online-ml-university is LGPL-2.1; Tags unique to awesome: awesome, awesome-list, lists, resources; When you need well-organized access to diverse technical subjects from IoT to robotics.
- When should I avoid online-ml-university?
- When your learning needs are focused on proprietary or specific to newer technologies not covered deeply by traditional universities If you require personalized guidance that is outside of the scope of available material from institutional courses In scenarios where certification or college credit from these institutions is required as the repository mainly aggregates free resources
- When should I avoid awesome?
- If seeking specific coding frameworks or libraries for software development rather than hardware-focused resources In scenarios requiring real-time interactive support or forums, as the content is static lists without active discussion
- Is online-ml-university or awesome more popular on GitHub?
- awesome has more GitHub stars (514,268 vs 229). Stars measure visibility, not whether either tool fits your constraints.
- Are online-ml-university and awesome open source?
- Yes - both are open-source projects on GitHub (online-ml-university: LGPL-2.1, awesome: CC0-1.0).
- Where can I find alternatives to online-ml-university or awesome?
- GraphCanon lists graph-backed alternatives at online-ml-university alternatives and awesome alternatives (online-ml-university markdown twin, awesome markdown twin), 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 mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, online-ml-university or awesome?
- online-ml-university: Dormant. awesome: 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 online-ml-university and awesome?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: online-ml-university trust report; awesome trust report.