Forwarded from Machine Learning with Python
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⏳ Once those 5 seats go through this link —
I'm not sharing it again. 🔥
I'm sharing this link with my network once — and only the first 5 people who enroll through it lock in a deal that has never been offered before.
👑 Lifetime access to HelloEncyclo — every AI, ML & Data Science course ever built — for ~$41. Once. Forever.
This isn't a drill. This isn't a rerun.
This is the founding-member price — and it disappears the moment the first 250 seats globally are gone.
✅ 13 courses live right now
✅ 40+ more in 2–3 weeks
✅ Every future course included automatically
✅ 15-day money-back — full refund, no questions
Code: PRESALE-BOOK-WAVE-2GFG
(Log in with Gmail · valid once · applies at checkout)
👇 First 5. That's it.
https://helloencyclo.com/?ref=HUSSEINSHEIKHO
⏳ Once those 5 seats go through this link —
I'm not sharing it again. 🔥
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Forwarded from Machine Learning with Python
A new collection of free courses has been added:
🔗 https://github.com/dair-ai/ML-Course-Notes
Those studying ML through dozens of random tabs and unclosed playlists may find this repository useful for organizing their learning. 📚
Machine Learning Course Notes is an open collection of notes on machine learning, NLP, and AI, compiled around full-fledged courses, not just individual videos. 🧠
What's inside:
• Courses from the Machine Learning Specialization, MIT 6.S191, CMU Neural Nets for NLP, CS224N, CS25, and others
• A table with lectures, descriptions, videos, notes, and authors
• Links to the original lectures and accompanying notes
• WIP markers for incomplete materials
• Instructions for contributors on adding and improving notes
The idea was appreciated. 👍
Instead of another collection of hundreds of links, a course map has been created where one can systematically go through the material without getting lost after a week of studying. 🗺️
#MachineLearning #AI #DataScience #TechCommunity #LearningResources #OpenSource
✨ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk
⭐️ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
🚀 Level up your AI & Data Science skills with HelloEncyclo — a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
✅ 13 courses live + 40+ coming soon
🎯 One access, lifetime updates
🔑 Use code: PRESALE-BOOK-WAVE-2GFG
👉 https://helloencyclo.com/?ref=HUSSEINSHEIKHO
🔗 https://github.com/dair-ai/ML-Course-Notes
Those studying ML through dozens of random tabs and unclosed playlists may find this repository useful for organizing their learning. 📚
Machine Learning Course Notes is an open collection of notes on machine learning, NLP, and AI, compiled around full-fledged courses, not just individual videos. 🧠
What's inside:
• Courses from the Machine Learning Specialization, MIT 6.S191, CMU Neural Nets for NLP, CS224N, CS25, and others
• A table with lectures, descriptions, videos, notes, and authors
• Links to the original lectures and accompanying notes
• WIP markers for incomplete materials
• Instructions for contributors on adding and improving notes
The idea was appreciated. 👍
Instead of another collection of hundreds of links, a course map has been created where one can systematically go through the material without getting lost after a week of studying. 🗺️
#MachineLearning #AI #DataScience #TechCommunity #LearningResources #OpenSource
✨ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk
⭐️ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
🚀 Level up your AI & Data Science skills with HelloEncyclo — a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
✅ 13 courses live + 40+ coming soon
🎯 One access, lifetime updates
🔑 Use code: PRESALE-BOOK-WAVE-2GFG
👉 https://helloencyclo.com/?ref=HUSSEINSHEIKHO
GitHub
GitHub - dair-ai/ML-Course-Notes: 🎓 Sharing machine learning course / lecture notes.
🎓 Sharing machine learning course / lecture notes. - dair-ai/ML-Course-Notes
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Join our livestream with Marina Wyss, Senior Applied Scientist at Twitch, as we discuss how to break into AI Engineering in 2026.
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Why should you join?
Many people interested in AI Engineering are asking the same questions:
❓ Where do I start?
🤔 Do I need deep math first?
🧠 Should I focus on ML, LLMs, RAG, or AI agents?
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✦ How to think about becoming hireable in AI
✦ Practical advice from someone already working in the field
Sign up for FREE and save your seat: luma.com/qgz4g4r7
Sign up for FREE and save your seat here: luma.com/qgz4g4r7
Why should you join?
Many people interested in AI Engineering are asking the same questions:
❓ Where do I start?
🤔 Do I need deep math first?
🧠 Should I focus on ML, LLMs, RAG, or AI agents?
🧭 How do I avoid wasting time learning the wrong things?
🚀 How do I go from learning to becoming hireable?
If you’re interested in AI Engineering but unsure how to approach it, this livestream is for you.
What you’ll learn
✦ What AI Engineering really is
✦ Where beginners should start
✦ What skills and topics actually matter
✦ Common mistakes to avoid
✦ Self-study vs bootcamp vs MSc
✦ How to think about becoming hireable in AI
✦ Practical advice from someone already working in the field
Sign up for FREE and save your seat: luma.com/qgz4g4r7