Best platforms for AI tutorials

The best platforms for AI tutorials depend on whether you want to learn AI or publish AI tutorials for developers. Here are the strongest options for both in 2026. altalks

Best platforms to learn AI (free and paid)

For structured, hands‑on learning with code:

• fast.ai – Project‑first, free deep learning (PyTorch) from vision to NLP; excellent for builders who learn by doing. altalks
• Hugging Face Learn – Free, practical courses on transformers, NLP, and LLM workflows; ideal for modern AI stacks. altalks
• Kaggle Learn – Free micro‑courses with in‑browser notebooks; great for ML/DL fundamentals and competitions. altalks
• DeepLearning.AI (Andrew Ng) – Short, high‑quality courses (many free) covering ML, DL, and GenAI concepts. altalks
• Coursera (audit mode) – University‑level ML/DL/GenAI courses (e.g., Andrew Ng’s ML specialization) free to audit; pay only for certificates. altalks
• MIT OpenCourseWare / Stanford CS231n – Rigorous, free university materials for deep theory plus assignments (CNNs, vision, etc.). altalks
• Google Cloud Skills Boost / Microsoft Learn – Free labs for TensorFlow, Azure AI, and GenAI; good for cloud‑native AI skills. medium

Best platforms to publish AI tutorials for developers

To reach a technical audience and build authority:

• In Plain English – Strong distribution for AI/ML/Python tutorials; editorial curation plus large dev readership. resources.plainenglish
• DEV Community (dev.to) – Open posting, fast feedback, good for community engagement and iterative tutorials. resources.plainenglish
• Hashnode – Best for personal branding and SEO; you own the blog with built‑in dev traffic and canonical support. resources.plainenglish
• HackerNoon / DZone / The New Stack – Authority‑focused outlets for deeper technical pieces and case studies. resources.plainenglish
• freeCodeCamp News / InfoQ – Editorial sites that favor production‑ready, well‑tested tutorials with diagrams and benchmarks. resources.plainenglish
• Your own blog (GitHub Pages, Hugo, Jekyll, Next.js) – Canonical home for SEO and ownership; syndicate excerpts to the platforms above with canonical links. resources.plainenglish

Practical workflow

1. Write the canonical tutorial on your own blog (full code, versions, tests, diagrams). resources.plainenglish
2. Syndicate to In Plain English and DEV (or Hashnode) with canonical tags or short excerpts linking back. resources.plainenglish
3. For learning content, build a series (e.g., “LLM apps with LangChain”) and publish sequentially to grow a returning audience. altalks

If you tell me your target audience (beginners vs advanced, NLP vs vision vs LLM apps), I can suggest a short list of courses to follow or a publication strategy with specific outlets. altalks