Телеграм канал «Machine Learning»

The 25 Best Free Resources for Learning AI in 2026

Learning artificial intelligence in 2026 is both easier and harder than it was a couple of years ago. Easier, because the best courses from Stanford and MIT, books by leading researchers, and hands-on lessons from Hugging Face are all openly available. Harder, because there is now far too much material, and the models and tools change every week. We have collected 25 proven free resources and arranged them by stage: from mathematics to LLMs, agents, and reading the latest papers.

Read: https://enghusseinsheikho.substack.com/p/the-25-best-free-resources-for-learning?r=3hwnr8&utm_campaign=post&utm_medium=web&showWelcomeOnShare=true

🔖 637 interactive modules on ML and AI

On VizLearn, you can visually explore:
🫡 Gradient descent;
🫡 SVM and PCA;
🫡 Bayes' theorem;
🫡 BPE tokenization;
🫡 Query, Key, and Value;
🫡 KV cache;
🫡 Quantization;
🫡 Neural networks and LLMs.

Change the input data and immediately see the results of the calculations.

⛓ Link to the tutorial
https://vizlearn.in/

🔥 Free IT & Dev Study Kits – 2026 Prep, No Signup

If you’re prepping for cloud, dev, or AI roles this year, these free kits cover the gaps most people skip — cert basics, hands-on labs, and mock exams. No signup traps, no hidden fees.

📘 Cert E-Book — covers Cisco & AWS fundamentals, good for first-time cert takers
→ https://bit.ly/4yrk1Ti

🪜 Online Free Course — structured path, works as a refresher before exams
→ https://bit.ly/4hUprRP

☁️ Free AI Materials — LLM basics to fine-tuning practice notebooks
→ https://bit.ly/4yt1iXy

📊 Cloud Study Guide — cheat-sheet style, handy for interview prep
→ https://bit.ly/4el4Eod

🧠 Free Mock Exam — test yourself before booking the real thing
→ https://bit.ly/4sbWlkl

📌 Save this or forward it to your dev/study group — good resources are worth sharing. 💪

🌐 Community: https://chat.whatsapp.com/CS7VOvQCLZG5BJPazBGm1v
📲 Personalized help: https://wa.link/xd2fu6
#Python #Cloud #AWS #Cisco #AI #MachineLearning #DevOps #ITCertification #FreeResources #TechCareers

Agentic AI is the future.

If you want to become god-level with AI agents, save these 10 GitHub repos:

1 Awesome LLM Apps

🔗 https://github.com/Shubhamsaboo/awesome-llm-apps

2 Generative AI for Beginners

🔗 https://github.com/microsoft/generative-ai-for-beginners

3 LLM Course

🔗 https://github.com/mlabonne/llm-course

4 Prompt Engineering Guide

🔗 https://github.com/dair-ai/Prompt-Engineering-Guide

5 AI Agents for Beginners

🔗 https://github.com/microsoft/ai-agents-for-beginners

6 AI Agents Projects

🔗 https://github.com/ashishpatel26/500-AI-Agents-Projects

7 Hugging Face Agents Course

🔗 https://github.com/huggingface/agents-course

8 Awesome AI Agents

🔗 https://github.com/e2b-dev/awesome-ai-agents

9 GenAI Agents

🔗 https://github.com/NirDiamant/GenAI_Agents

10 Agents Towards Production

🔗 https://github.com/NirDiamant/agents-towards-production

Anything else you'd add?

📚 7 Best Websites to Learn Computer Science Subjects for Free

More: https://enghusseinsheikho.substack.com/p/7-best-websites-to-learn-computer?r=3hwnr8&utm_campaign=post&utm_medium=web&showWelcomeOnShare=true

https://substack.com/@husseinsheikho?utm_source=share&utm_medium=android&r=3hwnr8

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You can literally enter a sentence and see how the Transformer processes it.

This interactive tool runs a GPT-like model directly in your browser and allows you to trace the entire process:

Tokenization → Embeddings → Q/K/V → Attention Mechanism → MLP → Logits → Probabilities of the next token.

You can explore attention maps, intermediate values, and adjust parameters like temperature, top-k, and top-p to see how they affect the generation.

If Transformers still seem like a collection of blocks connected by arrows, you should definitely try this.

https://poloclub.github.io/transformer-explainer/

telemetr.me/DataAnalyticsX