nstuan

[nstuan @nstuan1]

Champions

[Alejo @ecommartinez]

🚨𝗨𝗟𝗧𝗜𝗠𝗔 𝗛𝗢𝗥𝗔: Google Gemini tiene funciones brutales que casi nadie está usando.

La mayoría solo usa Gemini para prompts básicos… mientras Google lo llenó en silencio de herramientas que reemplazan horas de trabajo en segundos.

Probablemente estás usando menos del 5% de lo que Gemini realmente hace.

Aquí van 10 funciones ocultas de Gemini que se sienten casi injustas cuando las empiezas a usar: 👇

[Piers Morgan @piersmorgan]

What a player.. 🔥
What a performance. 🔥
I love @_DeclanRice so much.
Just a magnificent warrior.

[Google AI Studio @GoogleAIStudio]

https://t.co/PfLrKDTmww

[Mr. Buzzoni @polydao]

https://t.co/KwbHZv280S

[Vaishnavi @_vmlops]

The AI Engineer's System Design Interview Guide

https://t.co/VVFxWfibMM

[Ronin @DeRonin_]

Practical tasks for the article "How to become AI engineer in 6 months"

it's been almost 4 days since I published the article, and realized one thing

you already have all the resources, but not everyone fully understands what exactly to do in practice

so I put together a list of practical tasks to help reinforce the knowledge from the article

Week 1: Python + Git + Terminal

1. CLI expense tracker (Python)

Write a program: add an expense, show the list, save it to a JSON file. Only built-in libraries (json, sys, argparse)

2. Weather script via API (HTTP, Python)

Get data from Open-Meteo (no API key needed). Parse the JSON, output temperature and precipitation in a readable format. Handle 404 and timeout

3. First GitHub repository (Git)

Push both projects above to GitHub with a proper README. Create a .gitignore, commit several versions with meaningful messages

4. CSV file analysis with SQL (Python)

Download any CSV (for example, sales data from Kaggle). Load it into SQLite via pandas, then answer 5 questions: top 5 categories, average, filtering by date

5. Async multi-request script (Async)

Write an async script that requests weather for 5 cities simultaneously using asyncio + httpx. Compare the execution time with a synchronous version

⏩---------------------------------------------------⏪

Week 2: FastAPI + first LLM

1. FastAPI service for the tracker (FastAPI)

Rewrite the CLI expense tracker into a REST API: POST /expense, GET /expenses, DELETE /expense/{id}. Use Pydantic models, uvicorn, test it via /docs

2. First LLM API call (LLM)

Connect to the OpenAI or Anthropic API. Write 5 different prompts for one task (for example, text summarization). Compare the quality of the outputs, which one is better and why

3. Invoice parser with structured output (LLM)

Give the LLM raw invoice text and get back a Pydantic object: invoice_number, amount, items[], due_date. Use Instructor or native structured output

4. Streaming responses via FastAPI (LLM, FastAPI)

Connect stream=True to the LLM and return the response through StreamingResponse in FastAPI. Check that tokens appear as they are generated, not all at once

⏩---------------------------------------------------⏪

these are at least the tasks you need to complete over the next 10-14 days

if this tweet gets enough feedback, I'll keep sharing more practical tasks

for each week or even each month, so you can go through this path from A to Z

stay focused pls...

[Nav Toor @heynavtoor]

https://t.co/zYIvZQpyDu

[Ronin @DeRonin_]

https://t.co/J0ULhSHLLH

[Vivo @vivoplt]

Best YouTube Channels To Learn in 2026

1. Cybersecurity – John Hammond
2. Artificial Intelligence – Andrej Karpathy
3. AI Research Breakdown – Yannic Kilcher
4. Web Development – The Net Ninja
5. Python Programming – Corey Schafer
6. DevOps – TechWorld with Nana
7. Cloud Computing – AWS re:Invent
8. Data Analytics – Luke Barousse
9. System Design – Gaurav Sen
10. Databases – Hussein Nasser
11. Low-Level Programming – The Cherno
12. Linux – Learn Linux TV
13. Networking – David Bombal
14. Math for ML – 3Blue1Brown

[Matt Dancho (Business Science) @mdancho84]

Understanding P-Values is essential for improving regression models.

In 2 minutes, I'll crush your confusion.

Let's go:

[Alex Xu @alexxubyte]

https://t.co/mgpzcXcBXN

[DAN KOE @thedankoe]

https://t.co/AiGjkp3513

[Nav Toor @heynavtoor]

BREAKING: AI can now build financial models like Goldman Sachs analysts (for free).

Here are 12 Claude prompts that replace $150K/year investment banking work (Save for later)

[learn skills2.0 @_learnskills]

Exercise that helps children improve concentration and thinking skills.

[Matt Shumer @mattshumer_]

https://t.co/ivXRKXJvQg

[nstuan @nstuan1]

@yclair8 @4484 https://t.co/LMoz7W1rOe

[Md Riyazuddin @riyazmd774]

R.I.P. DUOLINGO.

3 years of Japanese. Nothing worked.
ChatGPT did it in 7 weeks.

Here are the 6 prompts I used :

[nstuan @nstuan1]

@v_computer Good job

[Avinash Singh @AvinashSingh_20]

Become Data Scientist for Free -> Complete GitHub Data Science resources!

Programming & Foundations

1- https://t.co/mZTVTJy7DR
Curated project based tutorials covering Python basics statistics and data analysis with hands on projects

2- https://t.co/JkeO7kFRBC
Beginner friendly Python exercises to build strong programming fundamentals

Mathematics & Statistics for Data Science

3- https://t.co/JE5Bga93Uh
Machine learning concepts explained from scratch using pure Python including math intuition

4- https://t.co/kN61r3dEcy
Code examples supporting the Statistics for Machine Learning book. Covers core stats needed for ML model building and evaluation with Python code you can run locally.

Data Analysis & Visualization

5- https://t.co/Dwc3nx4VVU
Official Pandas repository with examples documentation and real world data analysis use cases

6- https://t.co/AT07Yooqwh
Visualization cheatsheets for Matplotlib seaborn and data storytelling

Machine Learning

7- https://t.co/coEoT2ePJw
Curated list of machine learning libraries frameworks and resources by language

8- https://t.co/YM1ovprZQP
Hands on Machine Learning book code with scikit learn keras and tensorflow

Deep Learning

9- https://t.co/lsQrSTD5tc
Deep learning tutorials projects research papers and tools

10- https://t.co/82TCFaldEs
Free Microsoft 12 week machine learning curriculum with lessons and quizzes

Data Science Projects

11- https://t.co/uQZsaEzJfN
500 plus data science and machine learning projects with source code

12- https://t.co/mvgwPZw6NQ
Statistics driven data analysis projects using Python

SQL Big Data & Analytics

13- https://t.co/LeDLOOddJN
Free course covering SQL data pipelines and analytics foundations useful for data scientists

14- https://t.co/cKpT2CK9GY
Sample SQL database for practicing real world analytical queries

Roadmaps & Interview Prep

15- https://t.co/fOekN0jdWD
Complete data scientist roadmap covering skills tools and learning order

16- https://t.co/qvSgmVCecj
Collection of machine learning and data science interview questions