James Arthur

20th september

[Amaxa AI @coder_amaxaAi]

You can earn $7000/month if you have ChatGPT, a laptop, and 60 mins a day.

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[How To Learn Computer @Computerlearn_]

3 websites to get online certificates!

[Nafis Ahmed @iam_nafisahmed]

10 GitHub repos that print money while you sleep:

1. AutoHedge
https://t.co/cLk3AZvByJ

2. Vibe-Trading
https://t.co/gBo2LypYnp

3. Claude Ads
https://t.co/418v7ZdXnY

4. Toprank
https://t.co/MbwRYFgwEE

5. Fincept Terminal
https://t.co/oOjXXpnEfu

6. Agentic Inbox
https://t.co/CKc5lizVQA

7. ClawRouter
https://t.co/eOQECeZa1q

8. Camofox Browser
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9. Open Higgsfield AI
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10. Hyperframes
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[Liam Holt @liam_holt7]

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[Dipanshu Kushwaha @Dipanshu_AI]

Don't waste 2 years learning to become an AI agentic engineer in 2026.

Andrew Ng, the godfather of AI, gave the complete playbook to become one from scratch.

1 hour course. Free:

• 00:00 - AI agent basics
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I watched it last night.

Halfway through, I realized I could get into Anthropic in weeks, not years.

Bookmark now. Watch it. Then build your own AI agent

[Tanay Harinkhede @Tanaypawar27]

Top YouTube Channels to Master Tech Skills.

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14. Generative AI
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Follow @Tanaypawar27 for more of these free courses. productivity content.
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[Shraddha Bharuka @BharukaShraddha]

Goldmine for AI Engineers! 📌

If you're learning AI, ML, LLMs, or AI agents, don't waste hours jumping between random tutorials.

These are 10 repositories I'd actually keep bookmarked - from Python fundamentals to ML, LLMs, agents, and production AI.

1. Python - 100 Days

jackfrued/Python-100-Days

A 100-day Python learning path covering fundamentals, data analysis, web development, and more.

GitHub:
https://t.co/sw1ujP1Wnp

2. Generative AI for Beginners

microsoft/generative-ai-for-beginners

A practical introduction to building Generative AI applications.

Covers:

• LLM fundamentals
• Prompt engineering
• RAG
• AI agents
• Fine-tuning
• AI application development

GitHub:
https://t.co/xR9iu9EtzU

3. LLMs From Scratch

rasbt/LLMs-from-scratch

Want to understand what's actually happening inside an LLM?

Build one step by step.

Covers:

• Tokenization
• Embeddings
• Attention
• Transformers
• Training
• Fine-tuning

GitHub:
https://t.co/XIZYVfPosz

4. Machine Learning for Beginners

microsoft/ML-For-Beginners

A structured 12-week, 26-lesson curriculum covering classical machine learning.

A good starting point if you want ML fundamentals before jumping into LLMs.

GitHub:
https://t.co/4f85TPlIgv

5. OpenAI Cookbook

openai/openai-cookbook

A collection of practical examples and guides for building applications with OpenAI models.

Useful when you want to move from:

Learning → Building

GitHub:
https://t.co/qQTT34a36j

6. Stable Diffusion

CompVis/stable-diffusion

Interested in generative image models?

This repository contains the original Stable Diffusion implementation and research code.

GitHub:
https://t.co/yy9iV7AMNd

7. AI Agents for Beginners

microsoft/ai-agents-for-beginners

A practical course for understanding and building AI agents.

Covers:

• Agentic AI
• RAG
• Agent frameworks
• Tool use
• Multi-agent systems

GitHub:
https://t.co/kkXpu3tkW7

8. AI for Beginners

microsoft/AI-For-Beginners

A structured 12-week, 24-lesson introduction to AI.

Covers:

• Neural networks
• Computer vision
• NLP
• Deep learning
• Classical AI

GitHub:
https://t.co/uZqsZ77IyP

9. LLM App

pathwaycom/llm-app

Focused on building practical LLM applications.

Explore:

• RAG
• AI pipelines
• Enterprise search
• Real-time data
• Vector search

GitHub:
https://t.co/dKa96swuWu

10. Segment Anything

facebookresearch/segment-anything

A foundation model for promptable image segmentation.

Worth exploring if you're interested in computer vision and multimodal AI.

GitHub:
https://t.co/A22w8WrhZv

Don't bookmark all 10 and forget about them.

Pick based on where you are:

Python → Python-100-Days

ML → ML-For-Beginners

AI Fundamentals → AI-For-Beginners

LLMs → LLMs-from-scratch

Generative AI → Generative-AI-for-Beginners

Agents → AI-Agents-for-Beginners

Building → OpenAI Cookbook / LLM App

Computer Vision → Segment Anything

Pick one.

Build something.

Then move to the next.

[Jay Bisen @JayBisen473370]

🚨 Harvard just made its AI course free.

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1. Introduction to Generative AI
A step-by-step guide to how GenAI actually works.
Link: https://t.co/KvRFUSHAUM

2. Prompt Engineering
Real tips for improving output quality from any LLM.
Link: https://t.co/yPyl78h6mh

3. Beyond Chatbots: System Prompts, RAG
Move past surface use cases into scalable applications.
Link: https://t.co/av1VC8sw6q

4. Generative AI in Teaching & Learning
How educators can adapt and lead with AI.
Playlist: https://t.co/hj53aOurDL

5. Teaching with AI in the Classroom
Frameworks for trainers and educators.
Link: https://t.co/swesiOQeHJ

6. The Basics of Generative AI
No jargon. Just clarity.
Link: https://t.co/dvue3TwjfH

BONUS

🟩 CS50x 2025 – Artificial Intelligence Lecture
LLMs, neural nets, and real-world use cases
Link: https://t.co/NeVwcbT5TX

🟩 CS50 Extension – AI / Prompt Engineering
Design prompts that think with you
Link: https://t.co/30h7lWYCYe

🟩 GPT-4: How it works + how to build with it
Behind the curtain on GPT-4
Video: https://t.co/IolEp3KSTB

🟩 LLMs and the End of Programming
Why prompting is the new coding
Video: https://t.co/RleJNw3U4y
---

💡 REALITY CHECK

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👇 Which lecture are you starting with?

♻️ Repost to help others learn AI

🔖 Save this (you’ll need it later)

🔔 Follow @JayBisen473370 for more AI insights

[Forge Physique @ForgePhysique]

If You Want Bigger Shoulders... Do These 5 Dumbbell Exercises

[Avinash Singh @AvinashSingh_20]

1500+ Startups That Recently Raised Funding https://t.co/lnULbpPv3e

1300+ Hidden Companies Hiring List:
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Bookmark it , get more lists from here- https://t.co/gFxeLKc4QY

[Jami @expertwith_AI]

All Paid Courses (Free for First 4500 People)

𝗣𝗮𝗶𝗱 𝗖𝗼𝘂𝗿𝘀𝗲 𝗙𝗥𝗘𝗘 (PART - 1)
1. Artificial Intelligence
2. Machine Learning
3. Prompt Engineering
4. Claude,Chatgpt,Grok
5. Data Analytics
6. AWS Certified
7. Data Science
8. BIG DATA
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10. Ethical Hacking

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[Kiran Kanwar @kiranrathore123]

Claude Masterclass FULL COURSE 4 HOUR (Build & Automate Anything)

[Esan @esandurrani]

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[Job Corner @JOBCORNER247]

Free Online Cybersecurity Courses and Certifications in 2026.

Here are 15 FREE courses to help you master Cybersecurity 👇👇

1. IBM Cybersecurity Analyst Professional Certificate

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4. Developing Applications with Google Cloud Specialization

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5. Introduction to Cloud Computing

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6. Understanding Google Cloud Security and Operations

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7. Innovating with Data and Google Cloud

🔗 https://t.co/dnZ59ZTC9w

8. Microsoft Azure Fundamentals: Describe cloud concepts

🔗 https://t.co/gdHd2SlIra

9. GoogleCloud: Google Cloud Computing Foundations: Cloud Computing Fundamentals

🔗 https://t.co/b3CitYIFtB

10. Cloud Computing Basics (Cloud 101)

🔗https://t.co/vyKDyTcr1o

11. IT Fundamentals for Cybersecurity Specialization

🔗https://t.co/OgWdCensVa

12. Introduction to Cybersecurity Tools & Cyber Attacks

🔗 https://t.co/UbkohxmgJA

13. Cyber Security Course for Beginners
https://t.co/bBDau5ujRI

14. Introduction to Cyber Security
https://t.co/wpNGAmynDK

15. For Beginners
https://t.co/NGiPmE6aCt

Happy Learning 🌟

[Elon Musk @elonmusk]

Where will AI be in 1, 2 or 3 years?

[Anatoli Kopadze @AnatoliKopadze]

the engineer who built Claude Code just dropped a 28-minute video on how to write prompts that actually work

I've seen $300 courses that don't cover what he shows in the first 10 minutes

CLAUDE.md files, memory shortcuts, parallel sessions, prompting patterns

all in one video and completely free

works whether you're a developer, a beginner, or someone who's been using Claude for months

based on this, I put together 18 things you can copy and use in Claude today

full guide in the article below

[Yash @_Ai_Yash_]

🚨 Cambridge just dropped 10 FREE AI & ML textbooks (quietly).
University-level. Zero cost. Absolute gold for builders & learners.

Here’s the list with direct links 🧵👇

1️⃣ Understanding Machine Learning
Theory meets algorithms
https://t.co/oRUZrOPx6p

2️⃣ Mathematics for ML
Linear algebra → calculus made intuitive
https://t.co/gPmIYfYr7A

3️⃣ Mathematical Analysis of ML
The theory behind the code
https://t.co/aqBKRXZ70h

4️⃣ Deep Learning Principles
Neural networks explained clearly
https://t.co/2VheWhQODU

5️⃣ ML with Networks
Neurons → backpropagation
https://t.co/RlffNf2V3r

6️⃣ Deep Learning on Graphs
Graph Neural Networks & modern architectures
https://t.co/mAJmzJO0C0

7️⃣ Algorithmic ML
Complexity & optimization theory
https://t.co/VHl51bZtcv

8️⃣ Probability Theory
Statistical foundations with examples
https://t.co/hYW6pYHHte

9️⃣ Elementary Probability
Beginner-friendly + real-world use
https://t.co/qqD6pnwp0P

🔟 Advanced Data Analysis
Statistical learning for production systems
https://t.co/gXlfP0YVcP

💡 Free textbooks. Cambridge quality.
Perfect for students, engineers & AI builders.

Save 🔖 | Repost ♻️ | Follow for more AI resources 🤝

#AI #MachineLearning #DeepLearning #FreeResources #DataScience #StudyAI

[Fabrizio Romano @FabrizioRomano]

❤️🇧🇷 Manchester United fans: “One more year, one more year, Casemiro!” 🎶

The Brazilian had announced in January his decision to leave #MUFC in June. 👋🏽

[Python Coding @clcoding]

Free Web scraping with Python

https://t.co/gDimemiRSc