Shushant Lakhyani

Freelance marketer building TechnoBizzVault, where I help professionals discover modern tools so they can be productive without burning out.

Highly skilled content creator with a strong track record in newsletter growth, social media growth, and social media content creation. 

Proven success in building an audience on LinkedIn and Twitter/X and creating engaging content for newsletters. 

Experienced in creating content for LinkedIn, Twitter/X, and newsletters. 

Proficient in content creation and AI, no-code, and automation tools. 

Achievements:
✅ 150,000+ followers on LinkedIn and Twitter/X combined. 
✅ Helped Horizon AI reach 46,000+ newsletter subscribers from 1,800 subscribers in 6 months 
✅ Sold information products to more than 20,000 customers on Gumroad. 
✅ Worked with 5+ clients for ghostwriting 
✅ Gained 100M+ impressions on LinkedIn, Twitter/X, and Medium combined. 

Passionate about technology, content creation, and online business. 

Currently, working on building and growing TechnoBizzVault, an email newsletter where you discover hidden digital gems for free. 

Also, working as a freelance social media growth manager for a leading media brand in AI.

ClickUp Micro-Product Builder

Stop wasting hours on manual data analysis. 

Here are 10 AI tools that will help you get more data analysis work done in less time. 

🔖 Save this post for later 

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1. Quadratic 

Chat with your data and get insights in seconds.

Link: https://lnkd.in/dKHMmQtW  

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2. Rows 

Access the power of AI to analyze, summarize, and transform data. Build better spreadsheets, faster.

Link: rows.com/ai 

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3. SheetAI

Describe what you want in plain English, and watch the magic happen in your spreadsheet with hours of analysis work get done in minutes.

Link: https://www.sheetai.app/ 

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4. ChatCSV

Your new personal data analyst. Upload a CSV and start asking questions. It is an Ask Me Anything for Spreadsheets.

Link: https://www.chatcsv.co/ 

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5. Genius Sheets

Use natural language to connect to internal data and run analysis never before.

Link: https://lnkd.in/dVtyX7xb  

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6. Equals

Go from blank sheet to insight by just prompting.

Link: equals.com/ai 

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7. Numerous AI

It provides the simplest, most powerful and cost-effective solution for using ChatGPT inside Google Sheets.

Link: https://numerous.ai/ 

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8. Gigasheet

Leverage the simplicity of spreadsheet functions to seamlessly manage and analyze vast datasets in their entirety.

Link: https://www.gigasheet.com/ 

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9. ChartPixel

Get AI-assisted charts, presentations slides and actionable insights.

Link: https://chartpixel.com/ 

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10. Arcwise

Use AI with your business context built in, and a model you own, all from your spreadsheet. 

Link: https://arcwise.app/ 

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What other AI analysis tools would you like to recommend?

Let me know in the comments 👇 

---

Discover hidden digital gems for free: https://lnkd.in/daKFh4Gr 

🔁 Repost to help your network use the best AI analysis tools 

---

Stop wasting hours on manual data analysis. 

Here are 10 AI tools that will help you get more data analysis work done in less time. 

🔖 Save this post for later 

1.  Quadratic 

Chat with your data and get insights in seconds.

Link: https://www.quadratichq.com/   

1. Rows 

Access the power of AI to analyze, summarize, and transform data. Build better spreadsheets, faster.

Link: [rows.com/ai](http://rows.com/ai) 

1. SheetAI

Describe what you want in plain English, and watch the magic happen in your spreadsheet with hours of analysis work get done in minutes.

Link: https://www.sheetai.app/ 

1. ChatCSV

Your new personal data analyst. Upload a CSV and start asking questions. It is an Ask Me Anything for Spreadsheets.

Link: https://www.chatcsv.co/ 

1. Genius Sheets

Use natural language to connect to internal data and run analysis never before.

Link: https://www.geniussheets.us/  

1. Equals

Go from blank sheet to insight by just prompting.

Perplexity Deep Research is a game changer. 

You get a top tier business consultant in your pocket. 

Here are 10 Perplexity Deep Research prompts to turn you into a superhuman.

🔖 Save this post for later 

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10 types of prompts you’ll get in the carousel: 

1. Market Analysis for a Specific Industry 
2. Competitor Benchmarking 
3. Investment Opportunity Evaluation 
4. Technology Trends Report 
5. Marketing Strategy Development 
6. Health Research Summary 
7. Sustainability Practices in Business 
8. Travel Planning Guide 
9. Policy Impact Analysis 
10. Startup Feasibility Study 

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Additional Tip-1: Click on the nexus symbol to activate Deep Research before submitting your prompt.

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Additional Tip-2: I’ve not added roles to these prompts, because role prompting doesn’t matter a lot in 2025. But if you think they help you, feel free to add roles to these prompts.

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Additional Tip-3: These are prompt templates, you need to fill in the blanks to make these prompts personalized to your use case. 

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Additional Tip-4: You can also try these prompts on ChatGPT Deep Research.

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Additional Tip-5: Download the PDF and get it transcribed by AI to use these prompts. 

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Why I like Perplexity Deep Research?
✅ Saves hours by automating in-depth research and analysis.
✅ Delivers expert-level, comprehensive reports in just 2–4 minutes.
✅ Synthesizes information from hundreds of credible sources for accuracy.
✅ Enables easy export and sharing of research as PDFs or Perplexity Pages.
✅ Ideal for complex tasks in fields like finance, marketing, and technology.

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Do’s of using Perplexity Deep Research:
✅ Define your research goal.
✅ Use clear, detailed queries.
✅ Check all citations.
✅ Export and share results.
✅ Refine with follow-up questions. 

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Don’ts of using Perplexity Deep Research:
❎ Don’t skip fact-checking results.
❎ Don’t use vague prompts.
❎ Don’t ignore source quality.
❎ Don’t exceed prompting limits.
❎ Don’t assume full coverage.

---

Have you tried to use Perplexity Deep Research?

Let me know in the comments 👇 

---

Discover hidden digital gems for free: https://lnkd.in/daKFh4Gr 

🔁 Repost to help your network use Perplexity Deep Research 

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Perplexity Deep Research Prompts

Here’s a quick short summary of everything that happened in AI last week.

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What do you think will happen in AI this week?

Let me know in the comments 👇  

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Discover hidden digital gems for free: https://lnkd.in/daKFh4Gr 

🔁 Repost this post to help your network stay updated 

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AI Updates: Oct 27 - Nov 2, 2025

I’m sad to see you’re still stuck on ChatGPT.

You gotta try other AI models/LLMs too. 
And you gotta try Gemini. 

Here’s the ultimate Google Gemini Guide to help you use Gemini to its full potential. 

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How often do you use Gemini?

Let me know in the comments 👇  

--- 

Discover hidden digital gems for free: https://lnkd.in/daKFh4Gr 

🔁 Repost to help your network master using Gemini 

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Ultimate Google Gemini Guide

You’re not lazy. 

You’re just not using AI enough.

Here are 12 new AI hacks you can’t miss. 

🔖 Save this post for later 

---

What other new AI hacks would you recommend adding here?

Let me know in the comments 👇 

---

Discover hidden digital gems for free: https://lnkd.in/daKFh4Gr 

🔁 Repost to help your network use AI better 

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12 New AI Hacks

You think ChatGPT is just ok for resume creation. You’re wrong. 

ChatGPT is much better than you think.

Here are 10 ChatGPT prompts that help you with resume creation.

🔖 Save this post for later

---

10 types of ChatGPT prompts covered here:

1. Crafting a Professional Summary 
2. Listing Key Skills 
3. Detailing Work Experience 
4. Education Section 
5. Creating a Technical Skills Section 
6. Highlighting Certifications and Training 
7. Showcasing Achievements 
8. Formatting for Different Industries 
9. Crafting a Cover Letter 
10. Proofreading and Polishing

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Note: 

You should use ChatGPT to create a better resume, 
But always add your human touch to your resume. 
That still matters a lot.

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What do you think of using ChatGPT for resume creation?

Let me know in the comments 👇 

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Discover hidden digital gems for free: https://lnkd.in/daKFh4Gr 

🔁 Repost to help your network create better resume with AI 

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ChatGPT Prompts For Resume Creation

AI skills aren’t built overnight.

They’re built project by project.

Here are 15 AI projects that will help you level up your AI tool skills.

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Have you started to work with AI?

Let me know in the comments 👇 

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Discover hidden digital gems for free: https://lnkd.in/daKFh4Gr 

🔁 Repost to help your network master working with AI 

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AI Projects

You’ve used ChatGPT. 

But I'm sad to see you don’t really know how it works.

What happens behind the scenes will blow your mind.

Here’s how ChatGPT works.

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What more do you want to know about how ChatGPT works?

Let me know in the comments 👇 

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Discover hidden digital gems for free: https://lnkd.in/daKFh4Gr 

🔁 Repost to help your network learn how ChatGPT works 

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How ChatGPT Works Made Easy

You don’t need a PhD to master AI.

I’m sad to see you still think it’s too technical for you.

Here’s the zero to hero AI generalist roadmap. 

🔖 Save this post for later 

--- 

I’m an AI generalist IRL.

I try prompts for different use cases and use them for freelance work, my content brainstorming, and also share them on LinkedIn. 

--- 

I try different AI tools and stick to the ones that help me in the long term and I also keep switching to new and more powerful tools. 

I have to build and use GPTs and prompts for various use cases of my freelance work.

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I use various AI tools to help me not only at work, but in daily life too. 

Like getting help with fitness, relationship management, life design, and personal growth.

--- 

What more would you like to add to this AI generalist roadmap?

Let me know in the comments 👇 

--- 

Discover hidden digital gems for free: https://lnkd.in/daKFh4Gr 

🔁 Repost to help your network be an AI generalist 

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Complete AI Generalist Roadmap

You’re not slow your system is.

But AI systems help you fix that real quick. 

Here are 10 new AI hacks you can’t miss👇 

🔖 Save this post for later 

---

What other new AI hacks would you recommend adding here? 

Let me know in the comments  👇 

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Discover hidden digital gems for free: https://lnkd.in/daKFh4Gr 

🔁 Repost to help your network use AI 

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New AI Hacks

ChatGPT is insanely helpful for freelancing. 

Sadly, many freelancers don’t use it the best way.

Here are 10 ChatGPT prompts for freelancing.

🔖 Save this post for later 

--- 

Tip-1: All these are prompt templates, so you can customize them to your use case while using them. 

--- 

Tip-2: You can transcribe this doc using Mistral. 

--- 

Tip-3: I’ve not added role prompting to these prompts because it is not really necessary in 2025. But you can add roles to these prompts if you think they work for you. 

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What do you think about using ChatGPT for freelancing?

Let me know in the comments 👇 

--- 

Discover hidden digital gems for free: https://lnkd.in/daKFh4Gr 

🔁 Repost to help your network use AI for freelancing 

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ChatGPT Prompts For Freelancers

Everyone wants a personal coach. 

You already have one.

Here are 10 ChatGPT prompts that will help you use ChatGPT as your personal coach.

🔖 Save this post for later 

--- 

Here are the 10 use cases covered in the carousel:

1. Goal-Setting & Strategy Coach
2. Accountability & Habit Coach 
3. Productivity & Time-Blocking Coach
4. Career Strategy & Job Search Coach 
5. Public Speaking & Communication Coach 
6. Writing & Content Coach
7. Learning & Skill Mastery Coach
8. Fitness & Nutrition Coach
9. Negotiation & Difficult Conversations Coach
10. Interview & Mock Practice Coach 

--- 

For what other coaching use case do you use ChatGPT?

Let me know in the comments 👇

--- 

Discover hidden digital gems for free: https://lnkd.in/daKFh4Gr 

🔁 Repost this to help your network use AI 

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ChatGPT Prompts To Use ChatGPT As Your Coach

Here are 10 new AI hacks that will help you get more work done in less time. 

🔖 Save this post for later 

---

What other new AI hacks would you recommend adding here?

Let me know in the comments 👇 

---

Discover hidden digital gems for free: https://lnkd.in/daKFh4Gr 

🔁 Repost to help your network use AI 

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Your brain isn’t slow.

You’re just using outdated learning hacks.

Here are 10 techniques to supercharge your learning.

🔖 Save this post for later 

--- 

What other new learning techniques would you recommend adding here?

Let me know in the comments 👇 

--- 

Discover hidden digital gems for free: https://lnkd.in/daKFh4Gr 

🔁 Repost to help your network learn efficiently 

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Best Learning Techniques

AI isn't taking your job.

But someone with these skills might.

These are the 10 AI skills you need in 2025 to stay ahead.

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--- 

What other AI skill would you like to add here?

Comment below 👇 

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Discover hidden digital gems for free: https://lnkd.in/daKFh4Gr 

🔁 Repost to help your network work on their AI skills 

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AI Skills To Master

Your competition has a secret assistant.

It never sleeps and never complains.

Steal these 10 ChatGPT prompts and beat them at their game.

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I use ChatGPT every day for personal assistance.

And I save my personal assistance chats in projects.

This helps me keep a track too.

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Tip-1: These are prompt templates, so you’ll have to fill in the blanks to create prompts for your situation.

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Tip-2: I’ve not included roles in these prompts, because they don’t matter much in 2025. But you can feel free to add roles to these prompts if role prompting works well for you. 

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Tip-3: To get these prompts in text format, upload this PDF document on Mistral and ask it to transcribe the PDF. I chose Mistral because I think it is the best for PDF transcription. 

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Do you use ChatGPT as your personal assistant?

Let me know in the comments 👇 

--- 

Discover hidden digital gems for free: https://lnkd.in/daKFh4Gr 

♻️ Repost to help your network use ChatGPT as their personal assistant 

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ChatGPT Prompts To Use ChatGPT As Your Personal Assistant

Perplexity isn’t another regular AI tool. 

It’s your 24/7 working brainstorming and productivity assistant. 

Here’s the ultimate Perplexity guide you can’t miss. 

🔖 Save this post for later 

---

Do you use Perplexity regularly?

Let me know in the comments 👇 

---

Discover hidden digital gems for free: https://lnkd.in/daKFh4Gr 

🔁 Repost this post to help your network master using Perplexity AI 

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Ultimate Perplexity Guide

More than 150,000 custom GPTs are available in ChatGPT. 

Sadly, most people waste their time on the bad ones.  

Here are 10 GPTs you must use to save hours of work.

🔖 Save this post for later 

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1. Data Analyst 

Drop in any files and it can help analyze and visualize your data. 

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2. VideoGPT by VEED 

Type a description, set your style, and create full videos with subtitles and voiceovers. 

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3. Presentation and Slides GPT: PowerPoints, PDFs 

Make PowerPoints with a Slides AI PowerPoint Generator. 

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4. AI PDF Drive 

Upload and chat with all your files, create polished PDFs (presentations, reports, resumes, letters) right from the GPT. 

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5. Consensus 

Search references, get simple explanations, write articles backed by academic papers. 

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6. TutorMe 

Your personal AI tutor by Khan Academy. 

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7. Code Copilot 

It helps you code smarter and build faster. 

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8. Form and Survey Maker By Outgrow 

Build and share live surveys. 

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9. Whimsical Diagrams 

Explains and visualizes concepts with flowcharts, mindmaps and sequence diagrams. 

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10. Write for Me 

Write tailored, engaging content with a focus on quality, relevance and precise word count. 

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You can find all these GPTs in ChatGPT. 
But don’t limit yourself to it.
You can build your own GPTs too.

All you need to do is share your knowledge.

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Test and work on making the outputs of GPTs only limited to your knowledge.
And use it in the long term.

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And yes, you can build GPTs to use at work too.
You can share it with your team and let them use it.

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This is not it.
If you want to share your GPT with the world,
You can share it for free.

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And if you want to monetize your GPT, 
You can use a platform like Chipp or CalStudio.

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And don’t worry, you don’t need to learn coding to build GPTs.
You can build them from just prompts.

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Apart from that,
If you need to search a new GPT,
Use the search bar in the GPT store.
Write the keyword.
You’ll get the GPTs for the problem you’re facing.
It’s that easy.

----

What other GPTs would you like to recommend?

Let me know in the comments 👇 

--- 

Discover hidden digital gems for free: https://lnkd.in/daKFh4Gr 

🔁 Repost to help your network use the best GPTs 

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Job search is hard. You’re right.

Sadly most people don't use AI to make the job search process more efficient.

Here are 10 ChatGPT prompts that help with job search.

🔖 Save this post for later 

---

Types of prompts covered here:

1. Resume customization
2. Cover letter creation
3. Interview preparation
4. Networking message
5. Job search strategy
6. Portfolio project ideas
7. Salary negotiation email
8. Career change cover letter
9. LinkedIn summary for job seekers
10. Follow-up email after job interview 

---

What do you think about using ChatGPT for job search? 

Let me know in the comments 👇 

---

Discover hidden digital gems for free: https://lnkd.in/daKFh4Gr 

🔁 Repost to help your network use AI for job search 

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ChatGPT Prompts For Job Search

AI is changing the future of work.

Here are 10 courses that will help you learn AI.

🔖 Save this post for later 

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1. Rundown University

Get access to AI certificate courses, hundreds of real-world AI use cases, live workshops, an exclusive network of AI early adopters, and more.

Link: https://lnkd.in/dKHqQCMm 

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2. Outskill

Master AI skills with industry experts. Flexible learning paths for in-demand careers. Join thousands who transformed their careers with our proven AI learning methodology.

Link: https://www.outskill.com/ 

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3. Learn Prompting

Gain cutting-edge AI knowledge with hands-on, research-backed courses that solve real-world problems.

Link: https://lnkd.in/dD8SpMtF 

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4. Deep Learning AI

Get the latest AI news, courses, events, and insights from Andrew Ng and other AI leaders.

Link: https://lnkd.in/dNDhf7NF 

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5. Codefast

Learn to code in weeks, not months, with AI.

Link: https://codefa.st/ 

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6. AI For Everyone

If you want your organization to become better at using AI, this is the course to tell everyone, especially your non-technical colleagues, to take.

Link: https://lnkd.in/d93_JpVs 

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7. Artificial Intelligence A-Z 2025: Build 7 AI + LLM & ChatGPT

Combine the power of Data Science, Machine Learning and Deep Learning to create powerful AI for Real-World applications!

Link: https://lnkd.in/dQbek4Yu 

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8. Introduction to Generative AI Learning Path

This learning path provides an overview of generative AI concepts, from the fundamentals of large language models to responsible AI principles.

Link: https://lnkd.in/dxtw-Q2r 

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9. AI For Business Specialization

Learn the Fundamentals of AI and Machine Learning. Develop a deployment strategy for incorporating AI, ML, and Big Data into your organization that will take advantage of cutting-edge technologies.

Link: https://lnkd.in/d3sHJPD6 

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10. AI Programming With Python

Develop a strong foundation in Python programming for AI, utilizing tools like NumPy, Pandas, and Matplotlib for data analysis and visualization.

Link: https://lnkd.in/diXHiCW7 

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Have you started learning AI?

Let me know in the comments 👇 

--- 

Discover hidden digital gems for free: https://lnkd.in/daKFh4Gr 

🔁 Repost this post to be the first one to inform your network 

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AI/ML Engineer | 300K+ Impressions | Python & Full-Stack Developer | Building Next-Gen AI Agents 🤖 | Mentor Empowering Students & IT Pros | Passionate About Smart, Scalable Systems

As an AI/ML Engineer and passionate Python developer, I specialize in building intelligent, scalable systems that solve real-world problems. With a strong foundation in Electrical and Electronics Engineering (B.E., CGPA 8.7), I transitioned into the world of artificial intelligence, machine learning, and full-stack development — driven by curiosity, creativity, and a deep commitment to continuous learning.

At Avasoft, I’ve had the opportunity to work on cutting-edge projects, including AI-powered chatbots, voice-based assistants, RAG (Retrieval-Augmented Generation) models, and real-time backend services using FastAPI, Flask, and PyTorch. I’ve also led data automation efforts through web scraping, vector similarity searches, and NLP-driven applications, deploying robust solutions via Docker and CI/CD pipelines.

Beyond engineering, I find great fulfillment in mentoring and uplifting students and IT professionals. I actively guide aspiring engineers and developers through technical challenges, career planning, and project development. Whether it's through code reviews, workshops, or one-on-one sessions, I believe in creating opportunities for others to grow and succeed in tech.

My strengths lie in end-to-end solution design, a deep understanding of modern AI architectures, and the ability to translate business needs into technical deliverables. I’m always excited to collaborate, share ideas, and innovate in the intersection of AI, software, and real-time systems.

Let’s connect if you’re looking to discuss AI, collaborative projects, or mentoring opportunities!

Reshma S

⚡ All-in-One AI Agents Resource Hub 100% Free!

Tired of hunting scattered tutorials, repos, courses, and papers on AI Agents? I did the hard work for you. 

Here’s everything you need to learn AI Agents fast, all in one organized doc  free for anyone who wants to level up!

🎥 Must-Watch Videos
LLM Introduction – https://lnkd.in/dMqbaZdK
LLMs from Scratch – https://lnkd.in/dYYwEhYy
Agentic AI Overview (Stanford) – https://lnkd.in/dArmMt2i

🗂️ Top GitHub Repos
GenAI Agents – https://lnkd.in/d3UDtwwv
Microsoft’s AI Agents for Beginners – https://lnkd.in/dHvTmJnv
Prompt Engineering Guide – https://lnkd.in/gJjGbxQr
Hands-On LLMs – https://lnkd.in/dxaVF86w
 (+ 5+ more inside the doc)

🗺️ Guides & Whitepapers
Google’s Agent Whitepaper – https://lnkd.in/gFvCfbSN
Building Effective Agents (Anthropic) – https://lnkd.in/gRWKANS4
 (+ more inside the doc)

📜 Papers
ReAct – https://lnkd.in/gRBH3ZRq
Generative Agents – https://lnkd.in/gsDCUsWm
Toolformer – https://lnkd.in/gyzrege6

🧑‍🏫 Courses
HuggingFace Agent Course – https://lnkd.in/gmTftTXV
MCP with Anthropic – https://lnkd.in/geffcwdq
Building Vector DBs with Pinecone – https://lnkd.in/gCS4sd7Y
 (+ more inside the doc)

📩 Newsletters
Gradient Ascent
DecodingML
Deep Learning Focus
💡 Grab the full document here:
👉 https://lnkd.in/gie3X5gG

Stop wasting hours searching everything is ready for you in one place!
💾 Save | 👍 Like | ♻️ Repost and Help others learn for free.

Join the learning community: https://lnkd.in/gjDjHn95 to get started 
If you’d like me to create a personalized AI Agents learning roadmap just for you from these free resources, CONNECT & drop a COMMENT "link" and I’ll DM you the link!

AI Engineer | 1M+ Impressions | Helping Students professional to Build Next-Gen AI Agents | Mentor Empowering Students & IT Pros | Passionate About Smart, Scalable Systems

🚨STOP Scrolling: Here’s the ML + DL Cheat Sheet Everyone Was Searching For
(Stanford + MIT Approved)

Most people jump straight into Machine Learning algorithms…
 But the people who actually crack ML & Deep Learning?

 They start where Stanford and MIT teach them to start:
With the math that powers everything.

 If you’ve ever felt stuck, overwhelmed, or confused this cheat sheet clears it.
 The Real ML Learning Path (That Experts Follow)
1️⃣ Probability & Statistics
 → The science of uncertainty, risk, and prediction.
2️⃣ Linear Algebra
 → The engine behind every ML and DL model  from PCA to Transformers.
3️⃣ Optimization
 → Where models truly learn.
4️⃣ Machine & Deep Learning Models
 → All of them built on the above foundations.

💡 If you’re serious about AI in 2025, THIS is your roadmap.
 I wish someone gave me this on day one.

Join the Learning Community https://lnkd.in/gjDjHn95 

And if this post saved you hours of confusion…
 👥 Follow Reshma S | #reshmawithai for more AI content that actually 
Save & 🔁 REPOST  this if it saved you hours of confusion and could help someone else too.

Standford Cheat Sheet

12 GenAI Terms You Must Know to Sound (and Think) Like an AI Pro 

We hear terms like LLMs, RAG, embeddings, and prompt engineering everywhere but how many of us truly know what they mean and why they matter?
Here’s your quick guide  12 essential GenAI terms simplified so you can finally speak the language of modern AI 👇

 1️⃣ LLM (Large Language Model)
The engine behind AI trained on massive text data to understand and generate human-like language.
 It powers chatbots, copilots, and creative tools.

 2️⃣ Transformers (Architecture)
The neural network design that made ChatGPT possible.
 It helps AI focus on context  understanding relationships between words and meaning.

 3️⃣ Prompt Engineering
The art of asking AI the right way.
 Smart prompts lead to clearer, faster, and more accurate outputs.

 4️⃣ Fine-Tuning (Model Specialization)
Teaching a general AI model about a specific task or domain like training ChatGPT to act as a coding mentor or legal assistant.|

 5️⃣ Embeddings (Vector Representations)
AI’s way of understanding meaning.
 It converts words, images, or code into numbers that show how closely concepts relate.

 6️⃣ RAG (Retrieval-Augmented Generation)
Combines external knowledge with AI reasoning.
 Before answering, AI “retrieves” real data  reducing hallucinations and improving factual accuracy.

 7️⃣ Tokens (Text Units)
The building blocks of AI conversation.
 AI doesn’t read word-by-word  it processes tokens, which are small chunks of text.

8️⃣ Hallucination (AI Fabrication)
When AI sounds confident but gets facts wrong.
 Knowing how and why this happens helps us build more reliable models.

9️⃣ Chain-of-Thought (Reasoning Process)
AI’s “inner monologue.”
 By prompting it to explain steps, we get more logical and traceable answers.

 🔟 Context Window (Memory Limit)
Defines how much information an AI can remember at once.
 Larger windows mean longer, more coherent conversations.

 11️⃣ Zero-Shot Learning
AI’s ability to perform a task it’s never been explicitly trained on like answering new types of questions using prior knowledge.

 12️⃣ Temperature (Randomness Setting)
Controls how creative or deterministic AI becomes.
 Lower = focused and factual. Higher = creative and surprising.

💡 Why this matters:
 Understanding these terms isn’t just about jargon  it’s about knowing how today’s intelligent systems think, reason, and learn.

Join the Learning Community https://lnkd.in/gjDjHn95

Save this post for quick reference.
 💬 Comment your favorite term below!
 ♻️ Repost to help more learners speak AI fluently.
 👣 Follow Reshma S for simplified insights on LLMs, RAG, and AI systems that reason.
#GenAI #ArtificialIntelligence #LLM #MachineLearning #reshmawithai #careerbytecode

I Spent Weeks Confused by Deep Learning... Until I Made This Sheet

When I first started with Deep Learning, everything felt like a mystery box.
 Layers, activations, optimizers  they all sounded powerful, but honestly, confusing.

So, I decided to do what I do best  simplify the complex.
I built a one-sheet visual guide that breaks Deep Learning down from beginner to advanced in a way that actually sticks.

 No jargon. No textbook overload. Just pure understanding.
Here’s what’s inside this swipeable sheet ⬇️
 1️⃣ Building blocks  Layers, Losses, Activations & Optimizers
 2️⃣ CNNs vs RNNs  Visual and easy to grasp
 3️⃣ Batch size, Epochs & Flow  Explained clearly, finally!
 4️⃣ Clean visuals  For faster learning and revision

Because real learning isn’t about memorizing formulas 
 it’s about connecting the dots and understanding why things work the way they do.
So whether you’re prepping for your next AI interview or building your first model,
 this visual map will help you move faster, learn smarter, and remember longer.

👉 Join the learning community: https://lnkd.in/gjDjHn95

💡 Follow Reshma S | #ReshmaWithAI for weekly explainers that turn complexity into clarity.
 🔁 Save & repost  help others learn Deep Learning the easy way!

Deep Learning Cheat Sheet

RAG Isn’t One Thing It’s 25 Different Techniques (And Most People Don’t Know This)

Most people think RAG just means:
 retrieve → generate.
But real, production-grade RAG is far more advanced.
There are 25 different RAG variants, each built for a different purpose  from self-correction to graph reasoning to agentic workflows.
Here are a few that people barely talk about:
🔹 Self-RAG → the model critiques and improves its own answer
 🔹 Corrective-RAG → fixes hallucinations in real time
 🔹 Graph-RAG → reasons over structured relationships and knowledge graphs
 🔹 Agentic-RAG → enables multi-step reasoning with autonomous agents
 …and 21 more, each with its own strengths and ideal use cases.

I created a complete guide breaking down all 25 types of RAG with:
 ✔️ What each method does
 ✔️ When to use it
 ✔️ Simple workflow explanations anyone can understand
👉 Swipe through the carousel to explore the full list.
 👉 Which RAG variant are you using (or curious to try)?
Follow Reshma S for deep-dive AI breakdowns that turn complex topics into clarity.
Save it. 🔂 Repost it. Help more people learn real RAG.

RAG Types

Still confused between JSON and TOON?

 Here’s the simplest explanation that finally clears it up 👇
Most developers mix them up  but JSON and TOON are built for two completely different worlds.

🧱 JSON = Human-Friendly
Designed for web apps & APIs
Easy for humans to read
Contains braces, quotes, repeated keys
But heavy and token-expensive for LLMs

⚡ TOON = LLM-Friendly
Designed for AI, agents & large context windows
Minimal syntax, no repeated keys
Compact + predictable
Saves 30–60% tokens on uniform data
Faster parsing, lower cost, better accuracy

🎯 When to use what?
Use JSON when:
 ✔️ Humans need to read/edit the data
 ✔️ APIs, configs, small objects
 ✔️ Structures are non-uniform

Use TOON when:
 ✔️ Sending large datasets to LLMs
 ✔️ Telemetry, catalogs, logs, user lists
 ✔️ Building agents or multi-step workflows
 ✔️ Token cost + speed matter

 Final takeaway
JSON = great for humans.
 TOON = great for LLMs.
If this post finally cleared your confusion,
🔁 Found it helpful, Repost so others can learn too

⚠️ I Almost Lost My LinkedIn Account This Week, Learn From My Mistake

This Wednesday was one of the worst days of my life.
Everything looked normal… until I clicked on a link that appeared in my feed a simple Google Form for a “job opportunity.”
 I thought, Okay, let me check. I can share it with my friends who are job hunting.

That single click almost cost me my entire digital identity.
 And here’s the scary part 👇
It looked safe.
It felt safe.
 But it wasn’t safe.

Inside the form, there was a “Job Description” download button.
 I clicked it casually.
It downloaded a .exe file just a small file.
 I deleted it immediately once I sensed something was off…
…but the damage was already done.

💀 What really happened shocked me:
That .exe file was malware.
 It silently ran in the background even after deleting it.
 It hijacked my session cookies, meaning the attacker could log in as me, even though my:
✔️ Two-factor authentication was ON
 ✔️ 30-character strong password was secure
 ✔️ Recovery email & phone were protected
Nothing mattered.

 Because the hacker didn’t “log in”…
 They copied my active session.
And within minutes,
 👉 Automated messages were sent from my profile
 👉 Suspicious activity triggered LinkedIn security
 👉 My account got restricted
I froze.
 I honestly felt like crying.
 I have built my LinkedIn with hard work every connection, every post, every opportunity.
Losing it would break me.

 But by God’s grace I got it back within a day.
I went through the entire verification, proofs, screenshots  everything.
 LinkedIn finally restored my account.
That relief… I can never forget.

 Why am I sharing this?
Because I don’t want ANYONE to go through this nightmare.
Please read this twice:
⚠️ Don’t click ANY job links without verifying
 ⚠️ Don’t download ANY file from strangers
 ⚠️ Don’t trust “Google Form” just because it looks harmless
 ⚠️ Enable 2FA  but remember it’s NOT bulletproof
 ⚠️ Always check with someone before opening unknown links

❗ Final warning
Hackers don’t need your password.
 They just need one careless second.
I learned it the hard way.
 You don’t have to.
Stay safe. Stay aware.
Reshma S

Join the learning community: https://lnkd.in/gjDjHn95 to get started 

🔁 Please… repost this and share it with everyone you care about, no one should go through what I went through.

Is This the Beginning of AI That Learns Like Humans?

Today I came across something incredibly interesting from Google Research a concept called Nested Learning, and honestly… it feels like a real shift in how we think about AI.

For years, AI models have struggled with one big problem:

❗ Catastrophic Forgetting

Teach them Task A → they learn it
Teach them Task B → they forget Task A
Our brains don’t work like that… but current LLMs do.

That’s why this new approach caught my attention.

💡 Nested Learning: A new paradigm for continual learning

Instead of treating learning as a one-direction process, Nested Learning uses interconnected optimization loops that operate at different time scales fast, medium, and slow similar to how human neuroplasticity works.

Some innovations that stood out:
1.Deep optimizers that learn how to learn
2.Continuum memory systems (short → medium → long-term)
3.Multi-level updates that preserve old knowledge while learning new
4.Self-modifying architecture (yes, AI that improves its own memory)

And the early prototype  HOPE architecture shows improvements in both language modeling and long-context reasoning.

Why this matters
If AI can learn continuously without overwriting what it already knows,
we get closer to systems that can grow, adapt, and accumulate experience 
just like humans.

This isn’t just an upgrade.
It’s a glimpse into the next generation of AI intelligence.

🔁 Repost if you're excited to see AI move from static models to continual learners.

Stop Building 8-Layer AI Stacks —>> Start Shipping Real Agents
Everyone today is busy drawing complex 8-layer AI architecture diagrams.

But after actually shipping agents to production, here’s the brutal truth:
👉 You don’t need 8 layers.
 You need 3.
Most people are over-engineering.
 Real builders are shipping.

🧠 The Foundation That Actually Matters (80% of Your Agent)
These 3 layers ship products  not presentations:
LLM for Reasoning
 Your model is the brain. Keep it simple.
RAG for Context
 Retrieval + grounded data = fewer hallucinations.
Knowledge Base for Domain Expertise
 Let your agent “remember” what matters.
That’s it.

 The Layers You Add Later (Not on Day One)
When you scale, then you add:
Safety / Guardrails
Interaction UI
Governance
Auditability
Operational Independence
These are essential for enterprise…
 …but useless on day one if you don’t even have users yet.

💡 Real Talk: What I Actually Shipped
My first production agent?
✅ GPT-4
 ✅ Pinecone
 ✅ Basic guardrails
Result?

💰 $6K MRR in 6 weeks.
No fancy layers.
 No “enterprise theater.”
 Just speed, clarity, and iteration.

🚨 The Reality Most Builders Ignore
Your beautifully designed 8-layer diagram:
❌ won’t survive first contact with real users
 ❌ won’t help you ship faster
 ❌ won’t bring MRR
Start with the foundation → ship → add layers only when needed.
Complexity slows you down.
 Simplicity ships.

🙌 Massive shoutout to my friend Brij kishore Pandey
for this monster visual that perfectly captures the “over-design vs. real delivery” gap.

♻️ Repost to help more builders stop over-engineering and start shipping AI agents that actually reach production.

🚨 The AI Agent Tech Stack and Why It Matters More Than Ever
Lately, I’ve been diving deep into how AI agents are being built… and honestly, it feels like watching a new software era unfold in real time.

Every layer is evolving so fast that understanding the stack isn’t just “nice to know” anymore it’s becoming a superpower.

Here’s the core stack every modern AI agent relies on, broken down in the simplest way possible 👇
 1. Foundation Models
The large pre-trained language models the “brains” of AI agents.
 They reason, generate text, write code, answer questions, and connect the dots faster than ever.

🗃️ 2. Data Storage
Vector databases + memory stores.
 This is where agents keep what they learn context, embeddings, documents, everything they need to stay grounded and useful.

3. Agent Development Frameworks
The orchestration layer.
 These frameworks help developers build and manage multi-step AI agents, coordinate workflows, and create entire AI systems that behave intelligently.

 4. Observability
One of the most underrated pieces.
 Monitoring, debugging, and logging in real-time so we can actually trust agent behavior and understand why they did what they did.

 5. Tool Execution
APIs, browsers, external systems this is where AI stops “thinking” and starts doing.
 The real-world interface for completing complex tasks.

 6. Memory Management
Short-term + long-term memory.
 Systems that help agents retain context, learn continuously, and become more helpful over time.

That’s my list… but I’m curious:
 👉 What else would YOU add to the AI Agent Tech Stack?
 There’s so much happening in this space, and I’d love to hear what you’re exploring.
Visual credits ByteByteGo

Join the learning community: https://lnkd.in/gjDjHn95 to get started 
Follow Reshma S And🔂Repost and help someone understand AI without confusion!

20,000 Strong. And Growing. 

I gained 5,000+ followers in just 2 weeks  and I’m honestly speechless.
 Not because the number is big… but because the journey behind it was not easy.

This year tested me.
My LinkedIn got restricted, I went emotionally low, I lost my consistency, I doubted myself, and so many things went wrong behind the scenes.

But one thing I never let go of:
 My brand. My voice. My people.
And today, seeing this 20K means:
 You stayed.
 You believed.

 You supported me even on the days I couldn’t support myself.
To everyone who engaged, shared, encouraged, and stood by me 
 Thank you from my heart. 

 One last thing I learned:
 No matter what happens setbacks, restrictions, bad days, keep showing up.
 Consistency is a silent superpower.
 When you show up for your dream, the universe shows up for you

I promise to keep creating, keep learning, and keep showing up for you, for the community, and for everyone chasing something big.
If you’re reading this…
 🔁 Repost this journey
 👥 Follow Reshma S | #reshmawithai for more AI, learning, and real stories
Let’s grow together. 

Join the learning community: https://lnkd.in/gjDjHn95 to get started 

💛 Special thanks to my strongest supporters  my LinkedIn friends who are truly like family to me:
 Brij kishore, Manthan, Shushant, Pooja, Pallavi, Alex, Omkar, Sairam, Om Nalinde, Palanisamy, Kalyan KS, Saurabh, Naresh, Sangeetha B and CareerByteCode.

🚨The AI Evaluation Playbook Nobody Told You About 

Why most teams think they’re improving their models… but aren’t.
Everyone is obsessed with building AI model
 but very few actually know how to evaluate them the right way.

 And without proper evaluation, even the strongest model looks “smart” on paper and “broken” in production.
That’s why I put together this carousel:
 a deep dive into one of the most important modern AI concepts 👇
LLM-as-a-Judge
Inside the guide, I break down:

➡️ Why human evaluation fails at scale
 (opinion variance, slow turnaround, high cost, inconsistent scoring)

➡️ How LLM-as-a-Judge actually works
 (from structured scoring → rubric-based grading → pairwise comparisons → reasoning-trace evals)

➡️ The hidden biases that influence AI judgment
 (Leniency bias, verbosity bias, positional bias, confirmation bias — all backed by research)

➡️ Why SLMs are becoming the new evaluation engine
 (Faster, cheaper, more reproducible, and shockingly close to LLM-level accuracy)

➡️ A practical framework to build your own eval system
Create rubrics
Generate test sets
Run multi-pass scoring
Add reference-free evaluations
Aggregate confidence + justification

➡️ Real evaluation techniques used by AI companies today
 (OpenAI, Anthropic, Meta, industry researchers all using LLM judges)
This is the behind-the-scenes process top teams use to decide whether a model is ready for real users long before deployment.

Join the Learning Community https://lnkd.in/gjDjHn95 

If you truly want to think like an AI engineer, not just a model builder… this guide will change how you see evaluation.
If you found this valuable,
 👉 Follow me for more AI breakdowns
 🔁 Repost to help others learn the right way

LLM GUIDE

2025: The Year AI Agents Stepped Out of the Lab

McKinsey & Company’s State of AI 2025 just dropped and it confirms what many of us in the trenches already knew:
 AI isn’t just being tested anymore. It’s being trusted.

But here’s the twist while 9 out of 10 companies now use AI somewhere in their operations, only a handful have figured out how to scale it system-wide.

The difference?
 They’re not experimenting with prompts.
 They’re redesigning workflows around intelligent agents.

📊 Key Takeaways That Matter:
88% of companies now use AI (up from 78% last year)
Agent adoption is surging in tech, telecom, and healthcare
64% report stronger innovation + higher customer satisfaction
Major cost drops in IT, manufacturing, and software
Marketing and product teams see the biggest revenue jumps
And yet  only 6% of organizations are capturing significant business value.
Why? Because most are running pilots that never graduate to production.

 The winners are the ones who’ve stopped thinking “add AI here” and started thinking “build systems around AI.”
McKinsey’s Playbook for 2025:
 1️⃣ Design for scale from day one  no more endless proofs of concept
 2️⃣ Rewire processes, not just plug in tools
 3️⃣ Set bold goals around innovation and growth, not just efficiency
 4️⃣ Back it with leadership culture changes faster when execs lead adoption
 5️⃣ Balance human + machine collaboration for trust and resilience

💡 My takeaway:
AI Agents didn’t just go mainstream in 2025 
 they quietly became the operating layer of the modern enterprise.
The question now isn’t “Who’s using AI?”
 It’s “Who’s using it well enough to scale it sustainably?”

💾 Save this
 ♻️ Repost if you’re scaling with AI agents
 ➕ Follow Reshma S for more deep dives on how context, memory, and modular design are redefining AI systems.

State of Ai Report

🚨 I Wish Someone Told Me This Before Learning Machine Learning

I spent 3 months diving into ML libraries 
 TensorFlow, Scikit-Learn, PyTorch... you name it.
But here’s the truth no one said out loud 
👉 I wasn’t doing data science.
 I was just training models on dirty data.
And guess what?
 Garbage in = Garbage out.

Then one day I stopped chasing “fancy stuff.”
 I opened the same dataset again  but this time,
 I cleaned it, explored it, and actually understood it.

 Boom. Same data. 10x better results.
That’s when it hit me 
 The real magic isn’t in building models.
 It’s in fixing the mess before the model ever sees it.

 What Nobody Tells You About Data Science:
10% Collecting data
60% Cleaning & exploring
20% Modeling
10% Deployment
Everyone flexes the last 30%.
 But real power lives in the 60%.

⚡ Lessons That Changed My Journey:
Don’t rush to ML. Master Python basics first.
Learn Pandas until it feels like second nature.
Get your hands dirty with SQL.
Use real datasets  not perfect tutorials.
Tools like Scikit-Learn or PyTorch?

 They mean nothing without clean, trustworthy data.
🎯 My Game Plan That Finally Worked:
Started small: Python + Pandas + SQL
Built real projects (Kaggle was gold)
Added ML only when I was ready
Focused on understanding > memorizing
The unglamorous part  data cleaning 
 turned out to be the superpower of every great data scientist.

If you’re feeling stuck in your data science journey,
 stop chasing libraries. Start understanding data.
That’s where the real breakthroughs happen. 

💾 Save it | 💬 Comment where you stuck | 🔁 Repost to help someone avoid the same mistake. | ❤️ Follow for more data truths

🧠 Are you tired of spending hours drafting and creating LinkedIn posts?
I was too.
That’s why I built a Agent in Supervity  where I simply upload my content ideas in an Excel sheet… and the rest happens automatically.

Here’s what it does for me:
1. Creates the full LinkedIn post
 2.Refines the tone and structure
 3. Reviews and cleans the content
 4. Auto-posts it on LinkedIn
 5. Sends detailed analytics after posting

No more manual drafting.
 No more formatting stress.
 No more spending hours to post one piece of content.
Just upload → generate → refine → publish → analyse.
This is how I stay consistent without burnout.
 This is what smart automation looks like.

Follow Reshma S For more Ai insights 
 💬Connect & Comment “Link” • 📌 Save • 🔄 Repost this so someone else can save hours through automation.

#LinkedInAutomation #AItools #Productivity #ContentCreation #ReshmaS #supervity #reshmawithai #careerbytecode CareerByteCode

🚨 ⚠️ URGENT ALERT – My LinkedIn Account Has Been Misused! ⚠️ 🚨
Hi everyone,
 I’m posting this as a serious caution  it appears that messages were sent from my LinkedIn account that I never sent myself. These included a Google Form link related to a supposed “marketing campaign project.”
👉 Please do NOT click, fill, or respond to that link or any similar message appearing to come from me.
 👉 Shockingly, these messages are not even visible in my sent inbox  they only show up if someone replies to them! It honestly feels strange and scary  like messages disappearing on their own.
 👉 I’ve already reported this to LinkedIn and am taking all possible actions to secure my account.
Please:
 🔒 Turn on Two-Factor Authentication (2FA)
 🔑 Change your password immediately
 💬 Repost this alert to help others stay aware
I truly feel sorry for anyone who received such a message this was not from me. 🙏
 Let’s stay alert and help protect our networks from these kinds of account misuse.
Stay safe everyone,
 Reshma S LinkedIn

The Day I Realised AI Isn’t Magic —> It’s Mechanics
When I built my very first ML model, I expected brilliance.

 I thought the system would “just understand.”
Instead… it failed instantly.
 Predictions were random.
 Logic was nowhere.
 And I sat there wondering why my “smart” model behaved like a confused toddler. 

That’s when the truth hit me:
👉 AI isn’t a mysterious superbrain.
 It’s a machine that becomes what we feed it.
And once you see that, the entire field stops feeling magical and starts feeling buildable.

The 6 Mechanics Behind Every AI System
1️⃣ Data -> the experiences you give the machine
 2️⃣ Models -> the rules it uses to find patterns
 3️⃣ Training -> the repetition that makes it less wrong
 4️⃣ Inference -> the moment it applies what it learned
 5️⃣ Feedback -> the corrections that sharpen it
 6️⃣ Deployment -> where real users decide if it actually works
No myths.
 No mystery.
 Just engineering.

A Quick Example From My Journey
I once built a score-prediction assistant for cricket.
 The model kept getting everything wrong. I suspected complex issues…
 But the real problem? Dirty, inconsistent data.
I cleaned it. Retrained it.
 Suddenly the model “got smarter.”
Not magic.
 Just mechanics.

Why This Matters
The future doesn’t belong to people who fear AI.
 It belongs to people who understand how it works.
 Because once you learn the mechanics,
 you stop being a user…
 and start becoming a builder.
AI isn’t replacing humans.
 It’s replacing the idea that AI is magic.

💬 Comment MECHANICS if you want the full PDF Guide / carousel.
 🔁 Save & Repost with someone who needs the reality not the hype.

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The Battle

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