han

[Param @ParamSiddh]

"Introduction to Programming using Python" - from MIT

[Mert Metin Tekdemir @mertmetindev]

Dünyanın En İyi Üniversitelerinin Ücretsiz Açtığı 50 Ders ve Kaynak

1.) https://t.co/fncExGH5jc → Harvard’ın efsanevi bilgisayar dersi
2.) https://t.co/aY6lmk6iiG → MIT’nin tüm ders materyalleri
3.) https://t.co/Dtyhr2AAGB → Stanford ücretsiz ders arşivi
4.) https://t.co/zL3riJrsNa → Yale’in açık ders kayıtları
5.) https://t.co/MdmeoRu0ZU → Berkeley açık eğitim kaynakları
6.) https://t.co/Z9Zzzk4FYM → Michigan açık ders koleksiyonu
7.) https://t.co/6FrWwPO2WE → MIT açık öğrenme platformu
8.) https://t.co/oL9MYqlhtb → Açık Üniversite ücretsiz kursları
9.) https://t.co/ex5cPxQvS1 → Delft mühendislik dersleri
10.) https://t.co/34eCDAm2RR → Dinleyici modunda ücretsiz izleme
11.) https://t.co/OvXJVBCiYu → Dünya üniversitelerinden dersler
12.) https://t.co/fBzmIROlQQ → Ücretsiz kısa kurslar
13.) https://t.co/kxE0rQLcXP → Tüm ücretsiz kursların dizini
14.) https://t.co/PtFBW6iHVd → Sertifikalı ücretsiz üniversite dersleri
15.) https://t.co/GFmlS292M3 → Ücretsiz üniversite ders kitapları
16.) https://t.co/aYC5eAgpuI → Açık erişimli akademik kitaplar
17.) https://t.co/4yzoyqnCaG → Açık eğitim kaynakları arşivi
18.) https://t.co/UwlZTjnY7c → Öğretim materyali koleksiyonu
19.) https://t.co/afNs8D4IEH → Sıfırdan matematik ve fen
20.) https://t.co/LnlL6dYKVh → Problem çözerek öğrenme
21.) https://t.co/qjhr7d8veP → Matematiği görselleştirme
22.) https://t.co/kZAUQgn30s → Matematiği sezgisel anlatma
23.) https://t.co/I40qoYQscb → Adaptif matematik programı
24.) https://t.co/AQdUHUXcND → Kalkülüs ders notları
25.) https://t.co/Jh0K2ZrbPO → Grafikleri canlı çizme
26.) https://t.co/8MPiqpwA4E → Geometri ve cebir aracı
27.) https://t.co/OUOt3guKRb → Adım adım matematik çözümü
28.) https://t.co/UN36zlOUYX → Fizik konularını kavrama
29.) https://t.co/2KRPy1kL00 → Fizik kavram haritası
30.) https://t.co/3cDNeNzz4L → Feynman’ın fizik dersleri
31.) https://t.co/mobQitI1uq → Kimya ders kütüphanesi
32.) https://t.co/n2ZzFRgryN → Biyoloji görsel kaynakları
33.) https://t.co/DgfJIv2A5U → Genetik öğrenme merkezi
34.) https://t.co/C3tIEJ49D2 → Sinirbilim temelleri
35.) https://t.co/AXeEO3nrmy → Stanford felsefe ansiklopedisi
36.) https://t.co/IMIRzoXZMw → İnternet felsefe ansiklopedisi
37.) https://t.co/9ISLv0MDEN → Felsefe giriş kaynakları
38.) https://t.co/QNtd8P9qqM → Her konuda hızlandırılmış ders
39.) https://t.co/sRcK5KiXcI → Uzman anlatımları
40.) https://t.co/Q9OGCGN8kD → Fikir ve bilim içerikleri
41.) https://t.co/oUpcG5ts6N → Derinlemesine deneme yazıları
42.) https://t.co/hPYbSVRl5h → Bilim gazeteciliğinin en iyisi
43.) https://t.co/b1IZmXYpVY → Bilim ve kültür yazıları
44.) https://t.co/4Nwok7W5wn → Bilimsel makale ön baskıları
45.) https://t.co/ojXVoi1jnb → Makine öğrenmesini görselleştirme
46.) https://t.co/WvUtkHkDhR → Pratikten başlayan yapay zeka
47.) https://t.co/vaLziDmUqF → Kod yazarak derin öğrenme
48.) https://t.co/ju8vdExygL → Transistörden bilgisayar kurma
49.) https://t.co/2yocI4NC3j → Bilgisayar bilimi öz müfredatı
50.) https://t.co/JpflM80qAs → Ne öğreneceğinin sırası ve haritası

Dünyanın en iyi eğitimi ücretsiz. Sadece kimse duyurmuyor.

[Andrew Ng @AndrewYNg]

The most important skills for using AI coding agents effectively. Presenting the AI Engineering Skills Map for using coding agents. https://t.co/GrEw7wG5Wz

[Andrew Ng @AndrewYNg]

New: A map of the most important skills in AI Engineering. https://t.co/VVkn1Dqp1N

[Reads with Ravi @readswithravi]

“Stay focused on what really matters.”

— Tim Cook

[Rohit @HeyRohhit]

Instead of watching a 2-hour movie, learn how to actually win at life. Professor Jiang breaks it down with game theory:

[han @hanonu8]

@dnudjejfisks Akdeniz Paktı

[han @hanonu8]

@DuellaSinav Maarif Teşkilatı Kanunu

[Rohit @HeyRohhit]

An MIT professor opened his first finance lecture by auctioning a sealed box and in 90 seconds his students accidentally learned more about finance than most people learn in a lifetime.

Bookmark & watch today, no matter what.

[Mathieu @miniapeur]

Mathematics in the age of AI by Terence Tao
https://t.co/M4hit4bnDf

[Dhairya Karekar @dkare1009]

Google Launches a Completely Free, Full-Length 2-Hour Course for Comprehensive Mastery of Intelligent Agent Engineering! 🚨

A practical guide that takes you from zero to building fully independent systems (from 0% to 100%):
💡 The 5 Stages to Transition from a Simple Prompt to an Agent Network:

← 10% (38:46): Building Your First Intelligent Agent.

← 30% (54:46): Linking and MCP Tool Techniques.

← 55% (1:12:43): Loop Engineering — 4 Different Ways to Run Agents.

← 70% (1:20:57): Graph and Network Engineering.

← 100% (2:22:31): The Complete Software Ecosystem That Works and Executes Tasks While You Sleep!

Most people build one agent and stop there.. This course is the full path to building a completely self-running system without any intervention from you! 🤯⚡️

🔖 Watch it today, and save the tweet! 👇

[Die nagende Kritik @kritisch_kritik]

Alanında daha iyi kitap var mı bilmiyorum ama şu kitap çok çok iyi. Karşılaştırmalı bir metodolojiyi benimsemesi ise okuyucunun işini epey kolaylaştırıyor. Yanı sıra bu büyük teorilerin hangi felsefi, ideolojik öncüllerden hareket ettiklerini ve yine bu teorilerden hangisini benimsemenin nasıl bir politik çıktısı olduğunu da incelemeye dahil etmesi bakımından özgün bir çalışma. Okuması ve anlaması da bekleneceğinin aksine çok kolay.

[Emre Can Kartal @emreckartal]

İnsanın mükemmel sistemlere, her şeyi bilen gurulara değil de; kendine uyacak bir sisteme ihtiyacı var. https://t.co/WHWplEngBV

[Andrew Akbashev @Andrew_Akbashev]

Terence Tao, one of the most well known mathematicians, speaks up on AI in mathematics in his new paper:

“What if an AI tool generates a lengthy proof that is verified to be correct, but which nobody — 𝘯𝘰𝘵 𝘦𝘷𝘦𝘯 𝘵𝘩𝘦 𝘩𝘶𝘮𝘢𝘯𝘴 𝘸𝘩𝘰 𝘱𝘳𝘰𝘮𝘱𝘵𝘦𝘥 𝘵𝘩𝘦 𝘵𝘰𝘰𝘭 — understands? This is no longer hypothetical. Sites devoted to collecting mathematical problems already contain dozens of AI-generated proof submissions. Many of these are likely to be correct; but in a substantial number of cases no human expert has yet volunteered to verify and vouch for them, and in several cases the human submitters have themselves declared that they are not qualified to do so.

We may soon be faced with the very real possibility of a verified proof of a major result that NO HUMAN understands well enough to explain.

For a proof to actually contribute to its field, then, it is NOT enough for it to be correct, and NOT enough for it to be readable. It also needs to be accepted and valued by the community: other mathematicians need to 𝗱𝗶𝗴𝗲𝘀𝘁 𝘁𝗵𝗲 𝗿𝗲𝘀𝘂𝗹𝘁 𝗮𝗻𝗱 𝗶𝗻𝗰𝗼𝗿𝗽𝗼𝗿𝗮𝘁𝗲 𝗶𝘁 𝗶𝗻𝘁𝗼 𝘁𝗵𝗲𝗶𝗿 𝗼𝘄𝗻 𝘄𝗼𝗿𝗸.

Our current publication infrastructure relies on human editors and referees to provide this acceptance, voluntarily and largely without credit. This work is routinely regarded as less prestigious than the work of generating proofs in the first place; but it is an essential component of the profession, and it is precisely the mechanism by which the individual achievements of mathematicians are converted into collective progress and understanding.

Finally, even publication is not the last stage. Key results should ultimately become part of the definitive textbooks and reference material of their subject, in the form in which 𝘁𝗵𝗲𝘆 𝗮𝗿𝗲 𝘁𝗮𝘂𝗴𝗵𝘁 𝘁𝗼 𝘁𝗵𝗲 𝗻𝗲𝘅𝘁 𝗴𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝗼𝗻 𝗼𝗳 𝘀𝘁𝘂𝗱𝗲𝗻𝘁𝘀. This process of canonicalization is the slowest stage of all. It requires broad, deliberative consensus, and it is the stage least amenable to optimization by AI tools.”

📍 Terence Tao concludes:

“We will transition from an era of proof scarcity to an era of proof abundance. Most of our institutions — journals, priority conventions, hiring and promotion criteria, prizes, the very notion of a research program — were designed under the assumption of scarcity, and it should not surprise us if they behave poorly under abundance.

In some areas, particularly in education and in the training of young mathematicians, it will be crucial to emphasize 𝘁𝗵𝗲 𝗶𝗿𝗿𝗲𝗱𝘂𝗰𝗶𝗯𝗹𝘆 𝗵𝘂𝗺𝗮𝗻 𝗮𝘀𝗽𝗲𝗰𝘁 of our work, and to restrict the use of AI tools quite tightly; the goal of training a mathematician is NOT achieved by producing correct homework.

In other areas, we will need to take the initiative on AI usage, and define best practices for incorporating these tools into our workflows on our own terms rather than on terms set for us by vendors.”

__

[I highlighted & capitalized words in the text for clarity]

[One hard Truth @one_hardTruth]

The Telegram CEO says he’s never had depression. Listen to why.

[Neeraj @neeraj_here15]

Ray Dalio explains wealth creation in 42 minutes. Stop relying on short videos to learn how to make money.

More solid than most content.

[Dhairya Karekar @dkare1009]

A masterclass on ‘how to speak’ by MIT professor Patrick Winston - 15 key lessons

[AI_Explorer @ai_explorer25]

STEVE JOBS GOT FIRED FROM APPLE.

Then he walked straight into MIT and dropped the most raw, unfiltered 60-minute business masterclass ever recorded.

Zero PR bullshit. Zero image to protect.

Just pure, brutal honesty from the man who built Apple once and was about to rebuild it even bigger.

Stop scrolling.

Watch this tonight instead of Netflix.

Bookmark it. Come back to it.

[Words & Wisdom @WordsnWisdom26]

“Greatness does not come out of intelligence, it comes from character.

Character is not formed out of smart people: it is formed out of people who have suffered.”

— Nvidia CEO, Jensen Huang

[Reads with Ravi @readswithravi]

“Your time is limited, so don’t waste it living someone else’s life.”

— Steve Jobs