This channels is for Programmers, Coders, Software Engineers.

0️⃣ Python
1️⃣ Data Science
2️⃣ Machine Learning
3️⃣ Data Visualization
4️⃣ Artificial Intelligence
5️⃣ Data Analysis
6️⃣ Statistics
7️⃣ Deep Learning
8️⃣ programming Languages

✅ https://t.me/addlist/8_rRW2scgfRhOTc0

✅ https://t.me/Codeprogrammer

𝗬𝗼𝘂 𝗱𝗼𝗻’𝘁 𝗻𝗲𝗲𝗱 𝗺𝗼𝗿𝗲 𝗰𝗼𝘂𝗿𝘀𝗲𝘀 𝘁𝗼 𝗰𝗿𝗮𝗰𝗸 𝗔𝗜/𝗠𝗟 𝗶𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄𝘀. 𝗬𝗼𝘂 𝗻𝗲𝗲𝗱 𝗮 𝘀𝗵𝗮𝗿𝗽 𝗽𝗿𝗲𝗽 𝘀𝘁𝗮𝗰𝗸.

Most people consume content.
Top candidates train with the right repos.

Here’s a tight 9-repo stack that actually moves the needle:

𝟭 ⤷ 𝗦𝘆𝘀𝘁𝗲𝗺 𝗗𝗲𝘀𝗶𝗴𝗻 𝗣𝗿𝗶𝗺𝗲𝗿 (344k ⭐️)
https://lnkd.in/grVdK9X5
↳ Scale, trade-offs, real architecture thinking
↳ What you say in design rounds starts here

𝟮 ⤷ 𝗔𝗹𝗴𝗼𝗿𝗶𝘁𝗵𝗺𝘀 𝗶𝗻 𝗣𝘆𝘁𝗵𝗼𝗻 (220k ⭐️)
https://lnkd.in/gdeUgjsi
↳ Clean implementations
↳ Sharpens fundamentals for coding + ML logic

𝟯 ⤷ 𝗧𝗲𝗰𝗵 𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄 𝗛𝗮𝗻𝗱𝗯𝗼𝗼𝗸 (139k ⭐️)
https://lnkd.in/gmwpV865
↳ End-to-end prep: DSA + design + behavioral
↳ Use it to structure your weeks

𝟰 ⤷ 𝗔𝘄𝗲𝘀𝗼𝗺𝗲 𝗠𝗟 (72.3k ⭐️)
https://lnkd.in/gSGVvmBB
↳ Curated ML resources, papers, tools
↳ Fill gaps fast without noise

𝟱 ⤷ 𝗔𝘄𝗲𝘀𝗼𝗺𝗲 𝗦𝗰𝗮𝗹𝗮𝗯𝗶𝗹𝗶𝘁𝘆 (76.6k ⭐️)
https://lnkd.in/gt3R-nhm
↳ Real systems, real trade-offs
↳ Turns theory into production thinking

𝟲 ⤷ 𝟭𝟬𝟬 𝗗𝗮𝘆𝘀 𝗼𝗳 𝗠𝗟 (50.7k ⭐️)
https://lnkd.in/gyBQF3dv
↳ Daily reps → consistency
↳ Concepts + code together

𝟳 ⤷ 𝗠𝗮𝘁𝗵 𝗳𝗼𝗿 𝗠𝗟 (15.4k ⭐️)
https://lnkd.in/g_TYTu5J
↳ Linear algebra, stats, optimization
↳ Clears “I kinda get it” confusion

𝟴 ⤷ 𝗠𝗟 𝗧𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄𝘀 (8.1k ⭐️)
https://lnkd.in/dTt3syu2
↳ Focused ML interview questions
↳ Practice how you’ll actually be evaluated

𝟵 ⤷ 𝟲𝟱 𝗠𝗟 𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄 𝗤𝘀 (4.6k ⭐️)
https://lnkd.in/dcT9EksV
↳ Fast revision set
↳ Perfect before interviews

𝟭𝟬 ⤷ 𝗛𝗼𝘄 𝘁𝗼 𝘂𝘀𝗲 𝘁𝗵𝗶𝘀 𝗽𝗿𝗼𝗽𝗲𝗿𝗹𝘆

Fundamentals → Algorithms + Math
▼
System Design → Scalability
▼
ML Concepts → Practice Questions
▼
Daily Coding → Consistency

No jumping. No chaos. Just progression.

𝟭𝟭 ⤷ 𝗪𝗵𝗮𝘁 𝘀𝗲𝗽𝗮𝗿𝗮𝘁𝗲𝘀 𝘁𝗼𝗽 𝗰𝗮𝗻𝗱𝗶𝗱𝗮𝘁𝗲𝘀
↳ They don’t collect resources
↳ They reuse a small, high-signal stack
↳ They practice like it’s a system, not a mood

That’s the edge.

𝗬𝗼𝘂 𝗱𝗼𝗻’𝘁 𝗻𝗲𝗲𝗱 𝟱𝟬 𝗿𝗲𝗽𝗼𝘀. 𝗬𝗼𝘂 𝗻𝗲𝗲𝗱 𝟵 𝗮𝗻𝗱 𝗮 𝗽𝗹𝗮𝗻.
https://t.me/DataAnalyticsX 🩵

🚨 26 Claude Code slash commands you should know already. Save this post !

Most Claude Code users are only using 10% of what it can do
Here are the shortcuts that change how you work :

📌 Session control:
→ /compact [instructions]: compresses your conversation, you control what stays
→ /resume [session]: pick up exactly where you left off
→ /branch [name]: explore an alternative path without touching your main session
→ /rewind: roll back to an earlier point in code or conversation

📌 Cost and usage:
→ /cost: see token usage for the session
→ /usage: check your plan limits and rate limit status
→ /extra-usage: keep working even when rate limits hit

📌 Project setup:
→ /init: creates a CLAUDE.md guide for your project
→ /memory: edits CLAUDE.md files, enables or disables auto-memory
→ /add-dir <path>: adds a working directory for file access

📌 Code quality:
→ /diff: interactive diff viewer, uncommitted changes and per-turn diffs
→ /security-review: scans pending changes for vulnerabilities
→ /plan [description]: enters plan mode before Claude writes a single line

📌 Advanced control:
→ /permissions: manages allow, ask, and deny rules for tool use
→ /agents: configures sub-agent behavior
→ /mcp: manages MCP server connections and OAuth
→ /skills: lists all available skills, built-in and custom

Most people open Claude Code and just start typing
The ones shipping faster are using these before they write the first prompt

Which one did you not know about?
♻️ Repost if this helped someone on your team
https://t.me/DataAnalyticsX 🔰

🔖 10 Stanford courses on AI and ML — with official pages and all materials

▶️ CS221: Artificial Intelligence
▶️ CS229: Machine Learning
▶️ CS229M: Theory of Machine Learning
▶️ CS230: Deep Learning
▶️ CS234: Reinforcement Learning
▶️ CS224N: Natural Language Processing
▶️ CS231N: Deep Learning for Computer Vision
▶️ CME295: Large Language Models
▶️ CS236: Deep Generative Models
▶️ CS336: Modeling Language from Scratch

They cover the entire spectrum: classic ML, LLM, and generative models — with theory and practice.

tags: #python #ML #LLM #AI

➡ https://t.me/MachineLearning9

Language Models Interview Handbook

151 Interview Questions, Foundation Roadmaps, Python Examples,
Architecture Diagrams and Production Playbooks for Modern LLM

Help us grow

https://t.me/DataAnalyticsX ✅

If you want to become a Data Analyst or Data Scientist, these are the Python concepts you should master first:

🧹 Data Cleaning
✔️ dropna() → remove missing values
✔️ fillna() → handle nulls properly
✔️ astype() → fix data types
✔️ unique() → explore categories

📊 Exploratory Data Analysis (EDA)
✔️ describe() → quick statistics
✔️ groupby() → analyze patterns
✔️ corr() → find relationships
✔️ hist() & scatter() → visualize distributions

📈 Data Visualization
✔️ bar() → compare categories
✔️ sns.barplot() → statistical plots
✔️ sns.lineplot() → trends over time
✔️ plotly.express.scatter() → interactive charts

https://t.me/DataAnalyticsX 🤩

LLMs are the new operating system for work. 🚀💻

But most people still don’t know the difference between RAG, Embeddings, and Hallucinations. 🤔🧠

Here’s the vocabulary cheat sheet everyone in AI should know 📚✨

These foundational LLM concepts every professional, creator, founder, and tech enthusiast should know 👩‍💼👨‍💻🎨🚀

#LLM #DataScience #AI #ML

https://t.me/DataAnalyticsX 📎

Here’s a NumPy cheat sheet that depicts the 40 most commonly used methods from NumPy 📝🐍

#NumPy #DataAnalytics #AI #math 📊🤖

https://t.me/DataAnalyticsX 🔗📲

🤔 Where do I learn Claude?

🤖 You could've just asked!

🎓 13 free courses.
✅ With certificates.
📡 Straight from the source.

🧠 Claude teaches Claude. Who knew?

Here's the stash: 📚

1️⃣ Claude 101
https://lnkd.in/gCPUQsRg

2️⃣ AI Fluency: Frameworks & Foundations
https://lnkd.in/gS6ceZ_M

3️⃣ Introduction to Agent Skills
https://lnkd.in/g_wWNiEb

4️⃣ Building with the Claude API
https://lnkd.in/gDr5K_B4

5️⃣ Claude Code in Action
https://lnkd.in/g9wWZbK9

6️⃣ Model Context Protocol
https://lnkd.in/gAj5HqMY

7️⃣ MCP: Advanced Topics
https://lnkd.in/g3eDwBFY

8️⃣ AI Fluency for Students
https://lnkd.in/gKKujHGG

9️⃣ AI Fluency for Educators
https://lnkd.in/gVcKnuhA

🔟 Teaching AI Fluency
https://lnkd.in/g9P4gJFM

1️⃣1️⃣ AI Fluency for Nonprofits
https://lnkd.in/gpsm_BVf

1️⃣2️⃣ Claude with Amazon Bedrock
https://lnkd.in/gbfPjSFt

1️⃣3️⃣ Claude with Google Vertex AI
https://lnkd.in/gvVgB4Ub

🚫 No waitlists.
⏳ No countdown timers.
🚫 No "enrollment closes at midnight."

Just click and learn. 🚀

♻️ Repost for everyone still searching for Claude courses!

https://t.me/DataAnalyticsX 🔗