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
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
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Forwarded from Machine Learning
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With the CNN Explainer, you can learn about:
You can upload your own image and see how the network processes it step by step.
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🗂 500+ Cheat Sheets on Machine Learning
This repository contains materials on virtually everything: from basic algorithms and mathematics to neural networks, transformers, and advanced Deep Learning.
Each cheat sheet includes theory, formulas, Python examples, and tips on how to apply them.
⛓ You can find it here
https://github.com/gurovic/MLCheatSheets
#MachineLearning #DeepLearning #Python #DataScience #NeuralNetworks #AI
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This repository contains materials on virtually everything: from basic algorithms and mathematics to neural networks, transformers, and advanced Deep Learning.
Each cheat sheet includes theory, formulas, Python examples, and tips on how to apply them.
⛓ You can find it here
https://github.com/gurovic/MLCheatSheets
#MachineLearning #DeepLearning #Python #DataScience #NeuralNetworks #AI
✨ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk
⭐️ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
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10 Python libraries every AI engineer should know:
PyTorch: Deep learning models
Hugging Face Transformers: Pretrained AI models
LangChain: LLM apps & agents
LangGraph: Stateful agent workflows
OpenAI Python SDK: OpenAI model integrations
Pydantic: Data validation
Sentence Transformers: Text embeddings
FAISS: Vector similarity search
FastAPI: Web APIs
MLflow: Experiment tracking & ML lifecycle management
Anything else you'd add to this list?
https://t.me/CodeProgrammer
PyTorch: Deep learning models
Hugging Face Transformers: Pretrained AI models
LangChain: LLM apps & agents
LangGraph: Stateful agent workflows
OpenAI Python SDK: OpenAI model integrations
Pydantic: Data validation
Sentence Transformers: Text embeddings
FAISS: Vector similarity search
FastAPI: Web APIs
MLflow: Experiment tracking & ML lifecycle management
Anything else you'd add to this list?
https://t.me/CodeProgrammer
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Oxford University has launched a free course on "Deep Learning Theory" for the 2026-2027 academic year.
The course focuses on the mathematical foundations of deep neural networks and includes 16 lectures that are freely accessible.
The program covers neural network architectures, nonlinear transformations, convolutional structures, pooling, optimization methods, dictionary learning, transferability of learned features, adversarial examples, random matrix theory, invariance learning, and other topics.
The lectures explore the mathematical theories that explain how deep neural networks learn and what accounts for their unique characteristics.
In my opinion, this is particularly valuable material for those who want to understand the mathematics that underlies modern AI systems.
https://courses.maths.ox.ac.uk/course/view.php?id=6621
https://t.me/CodeProgrammer
The course focuses on the mathematical foundations of deep neural networks and includes 16 lectures that are freely accessible.
The program covers neural network architectures, nonlinear transformations, convolutional structures, pooling, optimization methods, dictionary learning, transferability of learned features, adversarial examples, random matrix theory, invariance learning, and other topics.
The lectures explore the mathematical theories that explain how deep neural networks learn and what accounts for their unique characteristics.
In my opinion, this is particularly valuable material for those who want to understand the mathematics that underlies modern AI systems.
https://courses.maths.ox.ac.uk/course/view.php?id=6621
https://t.me/CodeProgrammer
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pandas-guide.pdf
188.3 KB
pandas — The Mental Model. A practical, example-driven guide in 18 chapters: how tables and indexes actually work, selection and filtering, groupby, reshaping, joins, time series, text, chaining, performance, and what changed in pandas 3.0. Every example is executed, with its real output shown, and the book closes with a one-page cheat sheet.
If the field is short, cut it to: A 31-page practical guide to pandas — 18 chapters, every example executed with real output, from indexes and selection to groupby, performance and pandas 3.0.
https://t.me/MachineLearning9
If the field is short, cut it to: A 31-page practical guide to pandas — 18 chapters, every example executed with real output, from indexes and selection to groupby, performance and pandas 3.0.
https://t.me/MachineLearning9
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NumPy looks like a calculator and behaves like a memory model. 🧮
Most tutorials start with functions. This one starts with the five decisions NumPy made before you opened it: an array is one block of memory, shape is a contract between arrays, a slice is a view you can write through, the loop belongs in C, and the axis tells you which direction collapses.
15 chapters, 25 runnable examples, and every output copied from a real execution on NumPy 2.0.2. 🚀
Arrays, shapes and the machinery under the math:
https://enghusseinsheikho.substack.com/p/numpy-the-mental-model?r=3hwnr8&utmcampaign=post&utmmedium=web&showWelcomeOnShare=true
https://t.me/CodeProgrammer⭐️
Most tutorials start with functions. This one starts with the five decisions NumPy made before you opened it: an array is one block of memory, shape is a contract between arrays, a slice is a view you can write through, the loop belongs in C, and the axis tells you which direction collapses.
15 chapters, 25 runnable examples, and every output copied from a real execution on NumPy 2.0.2. 🚀
Arrays, shapes and the machinery under the math:
https://enghusseinsheikho.substack.com/p/numpy-the-mental-model?r=3hwnr8&utmcampaign=post&utmmedium=web&showWelcomeOnShare=true
https://t.me/CodeProgrammer
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Forwarded from Python Courses & Resources
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Claude FULL COURSE 1 HOUR (Build & Automate Anything) 🚀
✨ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk
⭐️ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
✨ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk
⭐️ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
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🔥 Free IT & Dev Study Kits – 2026 Prep & Double 11 Giveaway
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.
📘 Cert E-Book — Cisco & AWS fundamentals, ideal for first-time cert takers
→ https://tinyurl.com/ynutkhec
🪜 Online Free Course — a structured path that works great as a refresher before exams
→ https://tinyurl.com/4kvuk4m6
☁️ Free AI Materials — from LLM basics to fine-tuning practice notebooks
→ https://tinyurl.com/2z46z8f4
📊 Cloud Study Guide — cheat-sheet style, handy for interview prep
→ https://tinyurl.com/ymncyj5k
🧠 Free Mock Exam — test yourself before booking the real thing
→ https://tinyurl.com/y7ffwecz
🎁 Double 11 Giveaway — win iPhone Duo & Amazon Gift Cards
📌 Save this or forward it to your dev/study group — good resources are worth sharing. 💪
🌐 Join Community to Draw: https://chat.whatsapp.com/KkbnOUuS55aJdZMtTGrVYL
📲 Personalized help: https://wa.link/xd2
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.
📘 Cert E-Book — Cisco & AWS fundamentals, ideal for first-time cert takers
→ https://tinyurl.com/ynutkhec
🪜 Online Free Course — a structured path that works great as a refresher before exams
→ https://tinyurl.com/4kvuk4m6
☁️ Free AI Materials — from LLM basics to fine-tuning practice notebooks
→ https://tinyurl.com/2z46z8f4
📊 Cloud Study Guide — cheat-sheet style, handy for interview prep
→ https://tinyurl.com/ymncyj5k
🧠 Free Mock Exam — test yourself before booking the real thing
→ https://tinyurl.com/y7ffwecz
🎁 Double 11 Giveaway — win iPhone Duo & Amazon Gift Cards
📌 Save this or forward it to your dev/study group — good resources are worth sharing. 💪
🌐 Join Community to Draw: https://chat.whatsapp.com/KkbnOUuS55aJdZMtTGrVYL
📲 Personalized help: https://wa.link/xd2
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A Python library has been released on GitHub that allows you to create your own datasets and use them for machine learning experiments.
Features:
There is a demo version that you can try without installation.
https://github.com/koaning/drawdata
https://t.me/CodeProgrammer
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AI doesn't slow down. Neither does the news.
New models from OpenAI and Anthropic. Startups appearing out of nowhere. Security incidents, major breakthroughs, and billion-dollar deals.
There's always something happening. And keeping up with all of it is getting harder.
TIKRD AI NEWS brings you the AI stories worth knowing about.
Stay in the loop.
Follow TIKRD AI NEWS
New models from OpenAI and Anthropic. Startups appearing out of nowhere. Security incidents, major breakthroughs, and billion-dollar deals.
There's always something happening. And keeping up with all of it is getting harder.
TIKRD AI NEWS brings you the AI stories worth knowing about.
Stay in the loop.
Follow TIKRD AI NEWS
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