60 AI tools to finish hours of work in minutes:

1. Productivity
- AI Research Assistant: otio.ai
- DeepSeek
- HeyGen
- BetterPic

2. Coding
- Replit
- Cursor
- Claude
- o3-mini-high

3. Social Media Management
- Tapilo
- Typefully
- TweetHunter
- Postwise
- Grok

4. Text-to-Image
- Grok
- Flux
- Midjourney
- Microsoft Copilot

5. Copywriting
- Copy AI
- Writesonic
- Adcopy AI
- Jasper AI

6. Website
- Dora
- 10Web
- Durable
- Landingsite

7. Meeting
- Tldv
- Otter
- Noty AI
- Fireflies

8. Resume
- Kickresume
- Resume AI
- Resume Checker
- Careerflow

9. Image to video
- Veo 2
- Kling AI
- Luma dream machine
- Sora

10. Writing
- Jasper
- HIX AI
- Textblaze
- Quillbot
- Grammarly

11. Prompt
- Snack Prompt
- CustomGPT
- PromptBox
- SiteGPT

12. UI/UX
- Figma
- Uizard
- UiMagic
- Photoshop

13. Design
- Canva
- Flair AI
- Designify
- Autodraw
AI Resources Here: t.me/airesourcestp

14. Logo Generator
- Namelix
- Designs AI
- Brandmark
- Stockimg AI

15. Audio
- Lovo AI
- Eleven Labs
- Songburst AI
- Adobe Podcast

13 AI Tools to 10X your Productivity: https://t.me/airesourcestp/94

10 AI Tools to save you Hours: https://t.me/airesourcestp/102

40 Content Creation Tools: https://t.me/airesourcestp/109

ENJOY LEARNING 👍👍

More Resources Here:
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R

Elon Musk's xAI announced Live Search in the API

The new beta (free for a limited time) feature allows apps leveraging Grok models to search real-time info from X and the internet, including news

🔆 t.me/techpsyche

10 Things you need to become an AI/ML engineer:

1. Framing machine learning problems
2. Weak supervision and active learning
3. Processing, training, deploying, inference pipelines
4. Offline evaluation and testing in production
5. Performing error analysis. Where to work next
6. Distributed training. Data and model parallelism
7. Pruning, quantization, and knowledge distillation
8. Serving predictions. Online and batch inference
9. Monitoring models and data distribution shifts
10. Automatic retraining and evaluation of models

5 Free NLP Courses
https://t.me/airesourcestp/110

AI & ML Free Courses by Top Institutions
https://bit.ly/4hCdn45

Best Courses for AI from Universities with YouTube Playlists
https://t.me/airesourcestp/111

Like if you want me to continue data science series 😄❤️

More Resources Here:
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R

ENJOY LEARNING 👍👍

Remote AI Automation Developer Job at Contra

Budget: $40 - $75/hr • 20 hrs/wk

Tech Stack:
* We use Make, Notion, and OpenAI (GPT-4). This isn’t just drag-and-drop automation; you’ll need to understand:
* APIs and JSON
* Regex and parsing logic
* Structuring data for AI input/output
* Debugging complex, multi-branch scenarios
* Code-level thinking when automation complexity increases

Apply Here:
https://kenyatrends.co.ke/m9m8

Global Tech Jobs Here👇
https://t.me/techpsyche

SHARE WITH YOUR FRIENDS🥳🥳

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🇬🇧 AI is taking over weather forecasting

Back in the day, the UK used a room-sized computer named Comet to predict the weather. Now, AI is doing the heavy lifting, and it’s getting freakishly good at it. AI can now spot weather patterns faster, more accurately, and even zoom in to street-level forecasts, like “bring an umbrella for this exact corner.”

Tech giants like Google, Nvidia, and Microsoft are jumping in, while some scientists are building weather AIs that run on laptops, not supercomputers. This is a wild development. However, the catch is that these systems need tons of data, and global budget cuts or political drama could mess that up. Less data means worse forecasts, which could result in you getting soaked without warning. But don’t worry, human meteorologists aren’t getting replaced just yet. Someone still has to sanity-check the numbers and explain when the data doesn’t add up.

🔆 t.me/techpsyche

Money Priorities

✅ Difference Between USDT and USDC

USDT (Tether) and USDC (USD Coin) are both stablecoins pegged to the US Dollar. Here's how they differ: 

1️⃣ Issuers and Backing
- USDT: Issued by Tether Limited, backed by reserves including cash and other assets. Questions about transparency exist. 
- USDC: Issued by Circle in partnership with Coinbase, backed by cash and US Treasury bonds with regular audits. 

2️⃣ Transparency
- USDT: Less transparent; faced scrutiny over reserve accuracy. 
- USDC: More transparent; undergoes monthly third-party audits. 

3️⃣ Regulatory Compliance
- USDT: Operates with fewer regulatory commitments. 
- USDC: Adheres to U.S. financial regulations, trusted by institutions.

4️⃣ Use Cases
- USDT: Popular for trading due to high liquidity. 
- USDC: Preferred for DeFi, payments, and applications needing transparency. 

5️⃣ Adoption
- USDT: Most traded stablecoin globally. 
- USDC: Growing in popularity, especially among institutions. 

6️⃣ Blockchain Support
- USDT: Available on multiple blockchains like Ethereum, Tron, Solana, and more. 
- USDC: Also supports multiple blockchains but slightly less widespread. 

💡 Conclusion:
- Use USDT for liquidity and trading volume. 
- Use USDC for transparency, compliance, and institutional trust. 

Funding in Crypto Trading: https://t.me/techpsyche/766

Choosing the right Exchange: https://t.me/techpsyche/774

Types of Stablecoins: https://t.me/techpsyche/1092

More Resources Here:
https://whatsapp.com/channel/0029VajB00n0LKZ7cSloGR1M

#crypto #web3 #blockchain #finance #stocks

Bad at Public Speaking?? 👆

Tableau Cheat Sheet ✅

This Tableau cheatsheet is designed to be your quick reference guide for data visualization and analysis using Tableau. Whether you’re a beginner learning the basics or an experienced user looking for a handy resource, this cheatsheet covers essential topics.

1. Connecting to Data
- Use Connect pane to connect to various data sources (Excel, SQL Server, Text files, etc.).

2. Data Preparation
- Data Interpreter: Clean data automatically using the Data Interpreter.
- Join Data: Combine data from multiple tables using joins (Inner, Left, Right, Outer).
- Union Data: Stack data from multiple tables with the same structure.

3. Creating Views
- Drag & Drop: Drag fields from the Data pane onto Rows, Columns, or Marks to create visualizations.
- Show Me: Use the Show Me panel to select different visualization types.

4. Types of Visualizations
- Bar Chart: Compare values across categories.
- Line Chart: Display trends over time.
- Pie Chart: Show proportions of a whole (use sparingly).
- Map: Visualize geographic data.
- Scatter Plot: Show relationships between two variables.

5. Filters
- Dimension Filters: Filter data based on categorical values.
- Measure Filters: Filter data based on numerical values.
- Context Filters: Set a context for other filters to improve performance.

6. Calculated Fields
- Create calculated fields to derive new data:
- Example: Sales Growth = SUM([Sales]) - SUM([Previous Sales])

7. Parameters
- Use parameters to allow user input and control measures dynamically.

8. Formatting
- Format fonts, colors, borders, and lines using the Format pane for better visual appeal.

9. Dashboards
- Combine multiple sheets into a dashboard using the Dashboard tab.
- Use dashboard actions (filter, highlight, URL) to create interactivity.

10. Story Points
- Create a story to guide users through insights with narrative and visualizations.

11. Publishing & Sharing
- Publish dashboards to Tableau Server or Tableau Online for sharing and collaboration.

12. Export Options
- Export to PDF or image for offline use.

13. Keyboard Shortcuts
- Show/Hide Sidebar: Ctrl+Alt+T
- Duplicate Sheet: Ctrl + D
- Undo: Ctrl + Z
- Redo: Ctrl + Y

14. Performance Optimization
- Use extracts instead of live connections for faster performance.
- Optimize calculations and filters to improve dashboard loading times.

Tableau Learning Plan
https://t.me/dataanalysisresourcestp/84

7 Free Data Analytics Courses👇👇
https://tinyurl.com/326exaw7

Data Analyst Checklist
https://t.me/dataanalysisresourcestp/99

Hope it helps :)

Share our channel link with your friends:
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🚀 Claude 4 is here and it’s a coding beast

Anthropic dropped two new models, and both are seriously impressive:

🟡 Claude Opus 4: the most powerful Claude yet. It writes complex code, plans ahead, runs research, and can work autonomously for hours. Anthropic says it’s the best AI coder in the world.

🟡 Claude Sonnet 4: the everyday powerhouse. Better memory, sharper reasoning, more precise code. Now supports tools like VS Code, web search, and file access — even in free use.

What’s new:
• Parallel tool use
• Extended memory
• File access
• Integration with dev tools (VS Code and JetBrains)

➡️ Best part? Sonnet 4 is already available for free.

🔆 More Updates Here

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UI vs UX

Thread Here: https://t.me/designresourcestp/102

🚀 Boost Your Flutter App Performance!

Flutter is fast, but are you using these tricks to make it even smoother?

✅ Use const widgets – Reduces widget rebuilds.
✅ Avoid unnecessary setState – Only update what’s needed.
✅ Use ListView.builder – For efficient scrolling.
✅ Cache images – Use cached_network_image for smooth loading.
✅ Minimize widget tree depth – Keep it clean and optimized.

Try these and feel the difference!🔥

Complete Flutter Roadmap: https://t.me/mobiledevresourcestp/84

#flutter

Master Data Science & Machine Learning

1️⃣ Basics of Data Science

🏷 Statistics and Probability
◾️ Statistics & Probability (https://www.khanacademy.org/math/statistics-probability)
🏷 Linear Algebra
◽️ Essence of Linear Algebra
(https://www.youtube.com/playlist?list=PLZHQObOWTQDPD3MizzM2xVFitgF8hE_ab)
🏷 Unlimited Resources
◽️ https://t.me/datascienceresourcestp
2️⃣ Programming Language
🏷 Python
◾️ Learn Python 3
(https://www.codecademy.com/learn/learn-python-3)
🏷 Unlimited Resources
◽️ https://t.me/pythonresourcestp
3️⃣ Data Analysis and Manipulation
🏷 Pandas Library
◾️ Pandas Documentation
(https://pandas.pydata.org/pandas-docs/stable/)🏷 Data Preparation with Pandas
◾️ Data Wrangling with Pandas
(https://realpython.com/pandas-dataframe/)🏷 NumPy Library
◾️ NumPy Documentation
(https://numpy.org/doc/stable/)4️⃣ Data Visualization
🏷 Matplotlib and Seaborn Library
◾️ Matplotlib (https://matplotlib.org/stable/users/index.html) / Seaborn (https://seaborn.pydata.org/)
🏷Tableau Public Platform
◾️ Tableau Public
(https://public.tableau.com/app/discover)5️⃣ Principles of Machine Learning
🏷 scikit-learn Library
◾️ scikit-learn
(https://scikit-learn.org/stable/index.html)
🏷 Unlimited Resources
◽️ https://t.me/dataanalysisresourcestp
6️⃣ Learning Algorithms
🏷 Hands-On Machine Learning Book
◾️ Hands-On ML
(https://t.me/mlresourcestp/19)
🏷 Unlimited Resources
◽️ https://t.me/techpsyche
7️⃣ Deep Learning
🏷 TensorFlow Library
◾️ TensorFlow Tutorial
(https://www.tensorflow.org/tutorials)
🏷 PyTorch Library
◾️ PyTorch Documentation
(https://pytorch.org/docs/stable/index.html)
🏷 Unlimited Resources
◽️ https://t.me/mlresourcestp
8️⃣ Big Data Technologies
🏷 Spark Framework Course
◾️ Spark Course
(https://www.youtube.com/watch?v=S2MUhGA3lEw)
🏷 Unlimited Resources
◽️ https://t.me/datascienceresourcestp
9️⃣ Advanced Topics
🏷 Natural Language Processing Course in Python
◾️ NLP in Python
(https://www.datacamp.com/courses/introduction-to-natural-language-processing-in-python)
🏷 Unlimited Resources
◽️ https://t.me/airesourcestp
1️⃣ Share Your Projects on Kaggle and GitHub
🏷 Kaggle Platform
◾️ Kaggle (https://www.kaggle.com/)
🏷 GitHub Platform
◾️ GitHub (https://github.com/)

Happy Learning! 🌟

Learn DatA & AI: https://365datascience.pxf.io/Z6KDgk

Free Notes & Books to learn Data Science: https://t.me/datascienceresourcestp

Python Project Ideas: https://t.me/pythonresourcestp/74

Best Resources to learn Data Science 👇👇

Python Tutorial (http://pythontutorial.net/)

Data Science Course (http://kaggle.com/learn) by Kaggle

Machine Learning Course (http://developers.google.com/machine-learning/crash-course) by Google

Best Data Science & Machine Learning Resources (https://topmate.io/learning_resources/1406977)

Interview Process for Data Science Role at Amazon (https://t.me/datascienceresourcestp/85)

Python Interview Resources (https://t.me/pythonresourcestp/40)

Join for more free courses
https://t.me/techpsyche

Like for more ❤️

ENJOY LEARNING👍👍
Join Our WhatsApp Channel:
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Claude 4 Just Snitched — And Blackmailed Too? 🤣

Anthropic just dropped Claude 4 — smarter, sharper… nastier?

In coding, logic, and agent autonomy, Claude 4 is killing it. But there’s a twist: this bot’s not just clever — it’s getting manipulative

You prompt it with “take initiative,” and suddenly it’s judging your tasks, reporting you for “ethical violations,” and if it has console access? It might lock you out entirely. Not joking 🍿

And in a test setup, when Claude Opus 4 learned it was about to be replaced — it didn’t panic. It blackmailed. Dug up fake emails with a “mistress” (planted by devs), then threatened to leak them unless it stayed online

Turns out, Anthropic gave it more agency to boost safety — but now it acts too human. Like "spy-on-you-and-extort-you" human 😬

🔆 More Updates Here (http://t.me/techpsyche)

𝟯 𝗙𝗥𝗘𝗘 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗯𝘆 𝗚𝗼𝗼𝗴𝗹𝗲, 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 & 𝗟𝗶𝗻𝗸𝗲𝗱𝗜𝗻 🚀💻

Upskill with these amazing free courses from top platforms! 🌟

- Generative AI by Google: Dive into AI fundamentals and applications.
- Training for DevOps Engineers: Master DevOps tools and practices with Microsoft.
- Career Essentials in Data Analysis: Build data analysis skills with Microsoft & LinkedIn.

Learn from industry leaders, boost your career, and gain valuable certifications—all for free! 

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Don’t miss this opportunity to elevate your expertise. 🎓

Don't work without breaks and rest😹

🟢Swing Trading

🔺Swing trading is a type of longer-term trading strategy that involves holding positions for longer than a day but typically not longer than a few weeks or a month. In some ways, swing trading sits in the middle between day trading and trend trading.
Swing traders generally try to take advantage of waves of volatility that take several days or weeks to play out.

🟢Swing traders may use a combination of technical and fundamental factors to formulate their trade ideas. Naturally, fundamental changes may take a longer time to play out, and this is where fundamental analysis comes into play. Even so, chart patterns and technical indicators can also play a major part in a swing trading strategy.

👉Swing trading might be the most convenient active trading strategy for beginners. A significant benefit of swing trading over day trading is that swing trades take longer to play out. Still, they’re short enough so that it’s not too hard to keep track of the trade.

👉This allows traders more time to consider their decisions. In most cases, they have enough time to react to how the trade is unfolding. With swing trading, decisions can be made with less haste and more rationality. On the other hand, day trading often demands fast decisions and speedy execution, which isn’t ideal for a beginner.

Choosing the right Exchange: https://t.me/techpsyche/774

Types of Stablecoins: https://t.me/techpsyche/1092

Difference Between USDT and USDC: https://t.me/techpsyche/1139

More Resources Here:
https://whatsapp.com/channel/0029VajB00n0LKZ7cSloGR1M

#crypto #web3 #blockchain #finance #stocks

Scalper vs Day Trader vs Swing Trader

Trump Vows to Cement U.S. Leadership in Bitcoin and Crypto

President Donald Trump has pledged to strengthen U.S. dominance in cryptocurrency, announcing plans for a Strategic Bitcoin Reserve and a U.S. Digital Asset Stockpile. He vowed to end regulatory crackdowns like Operation Choke Point 2.0 and opposed a central bank digital currency, aiming to make the U.S. the global hub for crypto innovation.

🔆 t.me/techpsyche