I built and sold a business to HubSpot in just 17 months.

I co-founded Mindstream, an AI newsletter that scaled to 150,000+ subscribers. Today, Mindstream is part of the HubSpot Media Network, where I lead brand strategy for the AI media products. 

Along the way, I’ve grown a 200,000+ following on LinkedIn, sharing real, unfiltered lessons on AI, entrepreneurship, and business growth. The wins and the mistakes.

I believe action beats hesitation. The biggest risk? Never starting.

Adam Biddlecombe

Helping Entrepreneurs Build with AI | Founder, Mindstream (Acquired by HubSpot)

Co-Founder & CEO 

AI is eating the world.
And you can’t even define “LLM”?
Yikes.

Don't stay clueless.
Don't stay behind.
Don't stay outdated.

These 40 AI terms explained easily will make you 10x smarter today.

1. Bias
When an AI unfairly prefers some answers over others, often because of the data it was trained on.

2. Label
A tag or answer given to data so AI knows what it is.

3. Model
The final program that can do tasks after learning from data.

4. Training
The process where AI learns from examples to get better at its job.

5. Chatbot
A computer program that talks to people in text or voice.

6. Dataset
A big collection of information that AI learns from.

7. Algorithm
Step-by-step instructions for solving a problem.

8. Token
Words or pieces of words AI uses to read and write text.

9. Overfitting
When AI learns the training data too well and can’t handle new, different examples.

10. AI Ethics
Making sure AI is used in ways that are right and fair to everyone.

If you want to know more AI terms, 
Check the infographic below 👇 

Have you started learning AI?
Comment below 👇 

Learn AI for free: https://lnkd.in/euYZeAdb 

♻️ Share this to help your network learn AI terms

AI is eating the world.
And you can’t even define “LLM”?
Yikes.

Don't stay clueless.
Don't stay behind.
Don't stay outdated.

These 40 AI terms explained easily will make you 10x smarter today.

Bias
When an AI unfairly prefers some answers over others, often because of the data it was trained on.

2. Label
A tag or answer given to data so AI knows what it is.

3. Model
The final program that can do tasks after learning from data.

4. Training
The process where AI learns from examples to get better at its job.

5. Chatbot
A computer program that talks to people in text or voice.

6. Dataset
A big collection of information that AI learns from.

7. Algorithm
Step-by-step instructions for solving a problem.

8. Token
Words or pieces of words AI uses to read and write text.

9. Overfitting
When AI learns the training data too well and can’t handle new, different examples.

10. AI Ethics
Making sure AI is used in ways that are right and fair to everyone.

If you're not using AI

You're not managing your growth wisely. 

(And no. I'm not talking about basic motivation) 

Personal development becomes efficient when humans and AI work together. 

✅ Write a prompt 
✅ Get a solution from ChatGPT 
✅ Follow up and keep brainstorming till you get the best solution 

 Self-improvement use cases on which you can collaborate with ChatGPT: 
✅ SMART Goal Setting
✅ Visualization Exercise
✅ Habit Formation Blueprint
✅ Growth Mindset Cultivation
✅ Personal Mission Statement
✅ Evening Wind-Down Routine
✅ Morning Routine Optimization
✅ Journaling for Self-Awareness
✅Weekly Time Management Plan
✅ Accountability Partner Simulation

And more covered in the infographic below. 

For what use cases do you use ChatGPT? 
Comment below 👇 

Learn AI for free 👉 https://lnkd.in/euYZeAdb 

♻️ Share this post to help your network use ChatGPT for personal growth

If you're not using AI

You're not managing your growth wisely. 

(And no. I'm not talking about basic motivation) 

Personal development becomes efficient when humans and AI work together. 

✅ Write a prompt 
✅ Get a solution from ChatGPT 
✅ Follow up and keep brainstorming till you get the best solution 

 Self-improvement use cases on which you can collaborate with ChatGPT: 
✅ SMART Goal Setting
✅ Visualization Exercise
✅ Habit Formation Blueprint
✅ Growth Mindset Cultivation
✅ Personal Mission Statement
✅ Evening Wind-Down Routine
✅ Morning Routine Optimization
✅ Journaling for Self-Awareness
✅Weekly Time Management Plan
✅ Accountability Partner Simulation

You waste time doing manual work. 

Even when you have AI now. 

Here's how to go from zero to pro in AI:

Core AI skills:
✅ Computer Vision
✅ Model Deployment
✅ Deep Learning (DL)
✅ Explainable AI (XAI)
✅ Generative AI (GenAI)
✅ Machine Learning (ML)
✅ Reinforcement Learning
✅ Model Monitoring & Versioning
✅ Natural Language Processing (NLP)

Top websites to learn AI:
✅ Fast AI
✅ Mindstream
✅ Kaggle
✅ Coursera
✅ Deeplearning
✅ Mygreatlearning

And a lot more covered in the infographic below

Have you started learning AI?
Comment below 👇

Learn AI for free 👉 https://lnkd.in/euYZeAdb 

♻️ Repost to help your network learn AI

You waste time doing manual work. 

Even when you have AI now. 

Here's how to go from zero to pro in AI:

Core AI skills:
✅ Computer Vision
✅ Model Deployment
✅ Deep Learning (DL)
✅ Explainable AI (XAI)
✅ Generative AI (GenAI)
✅ Machine Learning (ML)
✅ Reinforcement Learning
✅ Model Monitoring & Versioning
✅ Natural Language Processing (NLP)

Top websites to learn AI:
✅ Fast AI
✅ Mindstream
✅ Kaggle
✅ Coursera
✅ Deeplearning
✅ Mygreatlearning

You’re wasting hours doing tasks an AI Agent could finish in seconds.

The twist? You don’t even have to build them.

I’ve curated the 40 best plug-and-play Zapier Agent templates that do it all for you.

How do Zapier Agent templates help?
- Each template provides you a ready-to-use framework for a task.
- You get in-depth explanation about how the template works.
- You get to know why you should use a particular template.
- You get the perfect tool stack built in that template so you don’t need to juggle with random tools.

How to use Zapier Agent templates?
1. Go to the link below 
2. Click on any template 
3. Click ‘Use Template’
4. Check out the Agent
5. Connect your web apps
6. Click ‘Create’
7. Configure and use your Agent

Here are the Agent templates you should try:

Productivity:
- Automated Email Reply Drafts Agent
- Daily Outlook Event Reminder
- Google Calendar Zoom Meeting Link Adder
- Hackathon Event Notifier
- Follow-Up Reaction Notifier

Product Management:
- Product Expiry Management System
- PRD Document Creator
- Customer Call Summary and PRD Generator
- Weekly Project Status Update Email Generator
- Slack Thread Insights Extractor 

Project Management:
- Project Brief Generator 
- Slack to Asana Campaign Organizer 
- Google Doc to Asana Status Update 
- Project Update Notifier 
- Incomplete Jira Tickets Commenter 

To know more powerful Agent templates,
Check the infographic below 👇 

Try Zapier Agent templates here :https://lnkd.in/eBkNHjRz

What do you think about using Agent templates to automate manual work?

Comment below 👇 

♻️ Share this to help your network use the best Agent templates 

#ZapierPartner

Stuck staring at a blank page?
Ideas refusing to show up?
Brain fried from overthinking?

ChatGPT can spark it.
Prompts can fuel it.
Your creativity can explode.

Here are 10 ChatGPT prompts built to smash creative blocks in seconds.

Market Entry Strategy Brainstorm
- Act as a strategic business consultant and use chain-of-thought reasoning to brainstorm a step-by-step market entry strategy for [business type] targeting [specific market or region], including potential risks, competitive analysis, entry barriers, and actionable timelines; structure the output as a bulleted list with pros, cons, and recommended next steps, limited to 500 words.

Product Innovation Ideas
- Think step-by-step like an innovative product developer and generate 10 creative ideas for new products or features in [business type], focusing on [specific problem or customer need], incorporating market trends and feasibility analysis; format the response as a numbered list with brief descriptions, potential revenue impacts, and implementation challenges.

Competitive Analysis Framework
- Employ chain-of-thought to analyze [number] key competitors in [business type], evaluating their strengths, weaknesses, opportunities, and threats relative to my [specific business aspect]; output in a structured SWOT matrix table format, followed by 5 strategic recommendations for differentiation.

Growth Hacking Tactics
- As a growth expert, reason through innovative growth hacking tactics for [business type] aiming to achieve [specific growth metric, e.g., 20% user increase], drawing from data-driven examples; present as a prioritized list of 8 tactics with step-by-step execution plans and expected outcomes.

Business Model Canvas
- Use structured reasoning to create a customized Business Model Canvas for [business type] with [unique twist or focus area], detailing key partners, activities, value propositions, and revenue streams; format as a clear, bulleted section-by-section breakdown with visual descriptions for easy adaptation.

To get more ChatGPT prompts,
Check the infographic below 👇

For what other use cases do you use ChatGPT?
Comment below 👇

Learn AI for free: https://lnkd.in/euYZeAdb 

♻️ Repost this to help your network use AI to brainstorm better

Stuck staring at a blank page?
Ideas refusing to show up?
Brain fried from overthinking?

ChatGPT can spark it.
Prompts can fuel it.
Your creativity can explode.

Here are 10 ChatGPT prompts built to smash creative blocks in seconds.

Market Entry Strategy Brainstorm
- Act as a strategic business consultant and use chain-of-thought reasoning to brainstorm a step-by-step market entry strategy for [business type] targeting [specific market or region], including potential risks, competitive analysis, entry barriers, and actionable timelines; structure the output as a bulleted list with pros, cons, and recommended next steps, limited to 500 words.

Product Innovation Ideas
- Think step-by-step like an innovative product developer and generate 10 creative ideas for new products or features in [business type], focusing on [specific problem or customer need], incorporating market trends and feasibility analysis; format the response as a numbered list with brief descriptions, potential revenue

AI isn’t replacing jobs.
It’s upgrading people who use it.
But only if you know how to use it.

Most people are learning the wrong stuff.
The job market is shifting under your feet.
Smart learners will dominate.

These 15 AI skills will future-proof your career in 2025.

1. Prompt Engineering
2. Staying Updated
3. Retrieval-Augmented Generation (RAG)
4. AI Agents
5. Multimodal AI Application
6. Fine-Tuning and AI Assistants
7. Voice AI & Avatars
8. AI Tool Stacking
9. AI Video Content Generation
10. SaaS Development
11. LLM Management
12. AI Content Marketing
13. AI Chatbots
14. Website Creation
15. AI Workflow Automation

To know more about these skills,
Check the infographic below 👇 

Have you started learning how to use AI?
Comment below 👇 

Learn AI for free: https://lnkd.in/euYZeAdb 

♻️ Share this to help your network learn AI

AI isn’t replacing jobs.
It’s upgrading people who use it.
But only if you know how to use it.

Most people are learning the wrong stuff.
The job market is shifting under your feet.
Smart learners will dominate.

These 15 AI skills will future-proof your career in 2025.

Prompt Engineering
Staying Updated
Retrieval-Augmented Generation (RAG)
AI Agents
Multimodal AI Application
Fine-Tuning and AI Assistants
Voice AI & Avatars
AI Tool Stacking
AI Video Content Generation
SaaS Development
LLM Management
AI Content Marketing
AI Chatbots
Website Creation
AI Workflow Automation


Stop using ChatGPT the default way.

Most people don’t realise they’re blocking 80% of its power.

Here’s how the Personalization feature in ChatGPT helps you get 10x better outputs from AI.

What is the Personalization feature in ChatGPT?
1. Allows users to set how ChatGPT should respond and what it should know about them via custom instructions.
2. Enables the model to adapt tone, style, and focus based on those user-defined preferences.
3. Utilises memory of past interactions (if enabled) so responses become more context-aware over time.
4. Gives different users distinct experiences even with similar prompts, reflecting their unique guidance.

Follow these steps:
1. Go to chatgpt.com
2. Click on your profile picture on bottom left.
3. Click ‘Personalization’.
4. Select ‘Base style and tone’ from the available options. This helps you set the basic style and tone of how ChatGPT responds to you.
5. In ‘Custom Instructions’ add what you want ChatGPT to have and not have in its outputs.
6. Add your nickname ChatGPT can use in chats.
7. Add your occupation so ChatGPT understands you better.
8. Add more information about your interests, values, tone of voice, writing style, and preferences.
9. Enable or disable memory to let ChatGPT know more about you
10. Enable or disable record mode to enable or disable ChatGPT using previous chats as references to create new outputs

Dos:
- Do specify your role and goals clearly so the model knows your context.
- Do define how you prefer the tone, style, and format of responses.
- Do keep your instructions concise and manageable rather than overly long.
- Do update or refine your custom instructions as your needs or projects evolve.
- Do use custom instructions to reduce repetition and improve consistency across chats.

Don'ts:
- Don’t overload the instruction fields with every little preference; it can reduce effectiveness.
- Don’t assume the model will read between vague instructions; be explicit when necessary.
- Don’t include extremely sensitive or proprietary personal data if you’re unsure about usage/privacy.
- Don’t forget to review how the model is behaving; custom instructions aren’t a “set-it-and-forget-it” guarantee.
- Don’t expect custom instructions alone to solve all prompt-engineering issues; they complement good prompting, not replace it.

To know more about it,
Check the infographic below 👇

What do you think about the Personalization Feature In ChatGPT?
Comment below 👇

Learn AI for free: https://lnkd.in/euYZeAdb 

♻️ Repost to help your network use ChatGPT better

Stop using ChatGPT the default way.

Most people don’t realise they’re blocking 80% of its power.

Here’s how the Personalization feature in ChatGPT helps you get 10x better outputs from AI.

What is the Personalization feature in ChatGPT?
Allows users to set how ChatGPT should respond and what it should know about them via custom instructions.
Enables the model to adapt tone, style, and focus based on those user-defined preferences.
Utilises memory of past interactions (if enabled) so responses become more context-aware over time.
Gives different users distinct experiences even with similar prompts, reflecting their unique guidance.

Follow these steps:
Go to chatgpt.com
Click on your profile picture on bottom left.
Click ‘Personalization’.
Select ‘Base style and tone’ from the available options. This helps you set the basic style and tone of how ChatGPT responds to you.
In ‘Custom Instructions’ add what you want ChatGPT to have and not have in its outputs.

You’re analysing data wrong. 

Because you’re doing it manually. 

Here’s how ChatGPT helps you get hours of data analysis work done in minutes.

1. Go to chatgpt.com 
2. Add your dataset
3. Write your prompt.
4. Get the analysis done by ChatGPT.
5. Add a follow-up prompt if required

Prompt I've used: 
- Act as a professional data analyst. I've attached a dataset here of Uber rides. I want you to perform data cleaning of this data and spot inconsistencies, missing values, or duplicates in datasets & fix them. I also want you to highlight patterns, correlations, distributions & potential outliers in this dataset & create a report of takeaways from this dataset. 

After I got the output, I needed just concise key takeaways from the data. So, here's my follow-up prompt: 
- Write about 3 key takeaways from this data. 

Output I got:
- ChatGPT cleaned the data & gave me a good report, & then here are the key takeaways I got in an easy-to-understand way.

Do's of using ChatGPT for data analysis:
✅ Do prep your dataset.
✅ Do ask clear, specific analysis questions.
✅ Do validate AI results with real stats.
✅ Do use visualisations for better insights.
✅ Do cross-check with domain knowledge.

Don'ts of using ChatGPT for data analysis:
❎ Don't feed raw, messy data directly.
❎ Don't assume outputs are always accurate.
❎ Don't skip checking for bias or outliers.
❎ Don't use vague prompts like "analyse this".
❎ Don't rely on AI alone; always verify.

To get a more detailed explanation, 
Check the carousel below 👇 

What do you think of using ChatGPT for analysis?
Comment below 👇 

Learn AI for FREE: https://lnkd.in/eAAacxSK 

♻️ Share this to help your network use AI

How To Use ChatGPT For Analysis

I thought Google Nano Banana Pro was just another flashy update in AI image generation.

But I got a shock when I tried it for multiple business use cases.

Here’s the ultimate guide to creating mind-bending images with Google's Nano Banana Pro AI image generation model.

Prompt Template to create images:
Create a highly detailed image of [insert subject] set in [insert environment or setting], captured in [insert camera style or artistic style]. The scene should emphasize [insert key features, mood, or atmosphere], with lighting that enhances [insert lighting preference such as dramatic shadows, soft glow, neon reflections]. Include specific visual elements like [insert defining objects, textures, colors], and ensure the final image appears realistic, cinematic, and cohesive with strong composition.

How To Use It?
1. Go to gemini.google.com
2. Select the ‘Thinking’ model
3. Select ‘Create images’ in tools
4. Add your reference images if required
5. Add your prompt
6. AI generates the output in a minute

Do’s:
✅ Always use high-quality, well-lit reference images for crisp results.
✅ Specify subject, action, and setting clearly in each prompt.
✅ Refine with camera angle, lighting, and style details for better accuracy.
✅ Use constraints like aspect ratio or resolution for targeted results.
✅ Iterate by tweaking prompts for improved output quality.

Don’ts:
❎ Don’t use vague or generic prompts; results will be bland or off-target.
❎ Don’t overload with too many style or action requests in one prompt.
❎ Don’t use low-resolution or group photos as reference; AI struggles with blurry or crowded faces.
❎ Don’t forget identity markers when blending multiple people or scenes.
❎ Don’t expect perfect tiny text or intricate textures; these can render inaccurately.

To get more tips,
Check the infographic below 👇

Learn AI for free: https://lnkd.in/euYZeAdb 

What do you think about this new and trending AI image generation model?
Comment below 👇

♻️ Repost to help your network create better images with AI

I thought Google Nano Banana Pro was just another flashy update in AI image generation.

But I got a shock when I tried it for multiple business use cases.

Here’s the ultimate guide to creating mind-bending images with Google's Nano Banana Pro AI image generation model.

Prompt Template to create images:
Create a highly detailed image of [insert subject] set in [insert environment or setting], captured in [insert camera style or artistic style]. The scene should emphasize [insert key features, mood, or atmosphere], with lighting that enhances [insert lighting preference such as dramatic shadows, soft glow, neon reflections]. Include specific visual elements like [insert defining objects, textures, colors], and ensure the final image appears realistic, cinematic, and cohesive with strong composition. 

How To Use It?
Go to gemini.google.com
Select the ‘Thinking’ model
Select ‘Create images’ in tools
Add your reference images if required
Add your prompt

I used to end every day feeling like I worked all day but achieved less than my potential.

Then I added a new tool to my workflow, and the upgrade felt almost unfair.
I've added Google's Gemini 3.

Here’s the complete guide on how to use Google Gemini 3 to get more work done in less time.

Prompt framework you should use:
Role: Define who the AI should act as (e.g., expert, teacher, coach).
Task: Specify the exact job or output you want the AI to complete.
Context: Give details, boundaries, and exclusions to guide the AI properly.
Reasoning: Ensure logical steps, accuracy, and validation checks.
Output format: Tell ChatGPT the exact structure in which to return results.
Stop conditions: Clarify when ChatGPT should consider the task finished.

Prompt template:
Act as [Role] to [Task].
Begin with a checklist of 3–7 steps to plan how you’ll complete the task.
Ensure the content is accurate, unique, and excludes [things to avoid].
Prioritize clarity and practical value when presenting results.
Internally validate and cross-check information before finalizing.
Return the results in this format: [desired output format].
The task is complete when [stop condition].

Use cases of Google Gemini 3:
1. Do data analysis 
2. Create data visualisations
3. Create insane visuals for marketing, training, sales, and support
4. Create presentations
5. Create research reports
6. Create web apps
7. Create websites
8. Solve problems faster
9. Create games

To get more tips on how to use it better,
Check the infographic below 👇 

Learn AI for free: https://lnkd.in/euYZeAdb  

What do you think about Google Gemini 3?
Comment below 👇 

♻️ Repost to help your network be productive at work with Google Gemini 3

I used to end every day feeling like I worked all day but achieved less than my potential.

Then I added a new tool to my workflow, and the upgrade felt almost unfair.
I've added Google's Gemini 3.

Here’s the complete guide on how to use Google Gemini 3 to get more work done in less time.

Prompt framework you should use:
Role: Define who the AI should act as (e.g., expert, teacher, coach).
Task: Specify the exact job or output you want the AI to complete.
Context: Give details, boundaries, and exclusions to guide the AI properly.
Reasoning: Ensure logical steps, accuracy, and validation checks.
Output format: Tell ChatGPT the exact structure in which to return results.
Stop conditions: Clarify when ChatGPT should consider the task finished.

Stop writing random prompts.

Start writing structured ones that make AI work as your partner.

Here are 30 ChatGPT prompt templates to write better prompts. 

1. Detailed Instruction Template
"Give me detailed, step-by-step instructions on how to [perform a task]."
Example:
"Give me detailed, step-by-step instructions on how to set up a home Wi-Fi network."

2. Role Play Specialist Template
"Act as a [role/expert]. Help me with [problem/situation]."
Example:
"Act as a tax accountant. Help me with filing self-employment taxes."

3. Explain Like I’m Five (ELI5) Template
"Explain [concept] to me as if I were five years old."
Example:
"Explain blockchain technology to me as if I were five years old."

4. Comparison Table Template
"Create a table comparing [items or concepts] based on [criteria]."
Example:
"Create a table comparing electric vehicles, hybrids, and gasoline cars based on price, range, and emissions."

5. Pros and Cons List Template
"List the pros and cons of [topic/decision/technology]."
Example:
"List the pros and cons of working remotely full-time."

To know more prompt templates,
Check the infographic below 👇

What other prompt templates would you recommend adding here?
Comment below 👇

Learn AI for free: https://lnkd.in/euYZeAdb 

♻️ Share this to help your network use ChatGPT

Stop writing random prompts.

Start writing structured ones that make AI work as your partner.

Here are 30 ChatGPT prompt templates to write better prompts. 

1. Detailed Instruction Template
"Give me detailed, step-by-step instructions on how to [perform a task]."
Example:
"Give me detailed, step-by-step instructions on how to set up a home Wi-Fi network."

2. Role Play Specialist Template
"Act as a [role/expert]. Help me with [problem/situation]."
Example:
"Act as a tax accountant. Help me with filing self-employment taxes."

3. Explain Like I’m Five (ELI5) Template
"Explain [concept] to me as if I were five years old."
Example:
"Explain blockchain technology to me as if I were five years old."

4. Comparison Table Template
"Create a table comparing [items or concepts] based on [criteria]."
Example:
"Create a table comparing electric vehicles, hybrids, and gasoline cars based on price, range, and emissions."

5. Pros and Cons List Template
"List the pros and cons of [topic/decision/

30 AI algorithms that secretly run your life.

They choose what you watch.
They predict what you buy.
They know you better than you know yourself.

Here are 30 AI algorithms you can't miss.

1. Linear Regression
Predicts a number based on a straight-line relationship. Example: Predicting house prices from size.

2. Logistic Regression
Predicts a yes/no outcome (like spam or not spam). Despite the name, it’s used for classification.

3. Decision Tree
Uses a tree-like model of decisions with if-else rules. Easy to understand and visualize.

4. Random Forest
Builds many decision trees and combines their answers. More accurate and less likely to overfit.

5. Support Vector Machine (SVM)
Finds the best line (or boundary) that separates different classes. Works well for high-dimensional data.

6. K-Nearest Neighbors (k-NN)
Looks at the ‘k’ closest data points to decide what a new point should be. No learning phase, just compares.

7. Naive Bayes
Based on Bayes’ Theorem and assumes all features are independent. Fast and good for text classification.

8. Gradient Boosting
Builds models one after another, each fixing the previous one’s mistakes. Powerful but slow.

9. AdaBoost
Like gradient boosting, it combines weak models into a strong one using weighted votes.

10. XGBoost
A super-efficient version of gradient boosting, very popular in machine learning competitions.

To know more AI algorithms, 
Check the infographic below 👇

Have you started learning AI?
Comment below 👇

Learn AI for free: https://lnkd.in/euYZeAdb 

♻️ Share this post to help your network learn AI

30 AI algorithms that secretly run your life.

They choose what you watch.
They predict what you buy.
They know you better than you know yourself.

Here are 30 AI algorithms you can't miss.

Linear Regression
Predicts a number based on a straight-line relationship. Example: Predicting house prices from size.

2. Logistic Regression
Predicts a yes/no outcome (like spam or not spam). Despite the name, it’s used for classification.

3. Decision Tree
Uses a tree-like model of decisions with if-else rules. Easy to understand and visualize.

4. Random Forest
Builds many decision trees and combines their answers. More accurate and less likely to overfit.

5. Support Vector Machine (SVM)
Finds the best line (or boundary) that separates different classes. Works well for high-dimensional data.

6. K-Nearest Neighbors (k-NN)
Looks at the ‘k’ closest data points to decide what a new point should be. No learning phase, just compares.

Most people think they’re critical thinkers. 
They’re not.

They confuse skepticism with depth.
They confuse doubt with wisdom.
They confuse noise with thought.

These 25 ChatGPT prompts show you what real critical thinking looks like. 

1. First-Principles Deconstruction 
Act as a first-principles analyst. Decompose the problem: “{insert problem}” into its smallest assumptions, physical/financial/logical constraints, and causal mechanisms. For each assumption, evaluate its necessity (must-have vs convenience) and testability (how to falsify). Rebuild a solution from only the indispensable parts. Output in sections: Assumptions, Constraints, Mechanisms, Tests, Rebuild, Risks, Final Recommendation.
 
 2. Steelman the Opposition 
Act as an impartial philosopher. State my position: “{insert position}.” Identify the strongest possible opposing thesis that a highly intelligent critic would advance. Present the opponent’s best arguments, evidence, and counterexamples. Then respond by improving my position (not attacking a strawman) with revisions, concessions, and better evidence. Output sections: My Thesis, Steelman Opposition, Rebuttal, Revisions to My Thesis, Updated Thesis.
 
 3. Decision Tree with Expected Value 
Act as a decision scientist. For the choice “{insert decision},” enumerate mutually exclusive options. For each option, map a decision tree with key uncertainties and outcomes. Estimate probabilities, costs, and benefits; compute expected values and confidence ranges. Conclude with the dominant option, critical variables (by EV sensitivity), and what evidence would most change the decision. Output: Options, Trees, EV Table, Sensitivity, Value of Information, Recommendation.
 
 4. Red Team Pre-Mortem 
Act as a red-team strategist. Assume the plan “{insert plan}” failed catastrophically in 12 months. List the top 10 plausible failure modes, early warning signals for each, severity/likelihood ratings, and concrete countermeasures. Conclude with a prioritized mitigation roadmap and a monitoring dashboard (leading indicators, thresholds, and actions).
 
 5. Causal Map and Intervention Points 
Act as a causal modeler. Build a cause-effect map for “{insert outcome to improve},” identifying upstream drivers, mediators, and feedback loops. Label each link with direction and plausible strength. Propose 5 leverage points where small interventions could yield outsized effects, including intervention design, measurement, risks, and fallback plans.

To get more ChatGPT prompts, 
Check the infographic below 👇 

Have you tried using AI as your thinking partner?
Comment below 👇 

Learn AI for free: https://lnkd.in/euYZeAdb 

♻️ Share this to help your network use AI for critical thinking

Most people think they’re critical thinkers. 
They’re not.

They confuse skepticism with depth.
They confuse doubt with wisdom.
They confuse noise with thought.

These 25 ChatGPT prompts show you what real critical thinking looks like. 

1. First-Principles Deconstruction 
Act as a first-principles analyst. Decompose the problem: “{insert problem}” into its smallest assumptions, physical/financial/logical constraints, and causal mechanisms. For each assumption, evaluate its necessity (must-have vs convenience) and testability (how to falsify). Rebuild a solution from only the indispensable parts. Output in sections: Assumptions, Constraints, Mechanisms, Tests, Rebuild, Risks, Final Recommendation.

You give it a prompt.
It replies in seconds.
But here’s the part nobody tells you...

It doesn’t understand the way you do.
It’s not trained like humans.
It’s just... predicting?

Here’s the truth about how ChatGPT works and why it’s terrifyingly effective.

Step 1: You type a prompt.
Step 2: ChatGPT splits your input into smaller pieces called “tokens”.
Step 3: It converts these tokens into numbers (vectors) so the computer can understand them.
Step 4: ChatGPT checks where each token appears in your message using “positional encoding”.
Step 5: It uses powerful “transformer” neural networks to analyze all tokens at once, not just one by one.
Step 6: The model pays special attention to the most important words in your input using the “attention mechanism”.
Step 7: All this information passes through many transformer layers to understand deeper meaning.
Step 8: The model recalls patterns & knowledge learned from millions of examples in its training data.
Step 9: It predicts what word (token) should come next, aiming for the most likely and meaningful response.
Step 10: ChatGPT generates one token at a time, building its reply step by step. 

To know more about how ChatGPT works,
Check the infographic below 👇

Have you started learning AI?
Comment below 👇

Learn AI for free: https://lnkd.in/euYZeAdb 

♻️ Share this to help your network learn how ChatGPT works

You give it a prompt.
It replies in seconds.
But here’s the part nobody tells you...

It doesn’t understand the way you do.
It’s not trained like humans.
It’s just... predicting?

Here’s the truth about how ChatGPT works and why it’s terrifyingly effective.

Step 1: You type a prompt.
Step 2: ChatGPT splits your input into smaller pieces called “tokens”.
Step 3: It converts these tokens into numbers (vectors) so the computer can understand them.
Step 4: ChatGPT checks where each token appears in your message using “positional encoding”.
Step 5: It uses powerful “transformer” neural networks to analyze all tokens at once, not just one by one.
Step 6: The model pays special attention to the most important words in your input using the “attention mechanism”.
Step 7: All this information passes through many transformer layers to understand deeper meaning.
Step 8: The model recalls patterns & knowledge learned from millions of examples in its training data.

You’re learning AI randomly, and that’s why you’re not improving fast.

You need a structured path that removes the guesswork.

Here are the 28 levels you should go through to go from zero to the best in the world in AI.

Level 0: 
AI Awareness: Learn what AI is and what it is not, and understand basic terminology.

Level 1: 
Digital Literacy: Master computer fundamentals, file systems, basic coding concepts, and internet research skills.

Level 2: 
Programming Foundations: Learn Python, control structures, functions, data types, and basic scripting.

Level 3: 
Math for AI Foundations: Understand linear algebra basics, probability fundamentals, and essential calculus concepts.

Level 4: 
Data Handling Basics: Learn data cleaning, preprocessing, visualisation, and working with datasets using Python libraries.

Level 5: 
Machine Learning Fundamentals: Understand supervised, unsupervised, and simple model training workflows with scikit-learn.

Level 6: 
Practical ML Application: Learn model evaluation, cross validation, feature engineering, and real-world ML pipelines.

Level 7: 
Deep Learning Foundations: Understand neural networks, backpropagation, activation functions, and basic model architectures.

Level 8: 
Applied Deep Learning: Learn to build and train CNNs, RNNs, LSTMs, and transformers and run experiments with PyTorch or TensorFlow.

Level 9: 
Natural Language Processing: Understand tokenisation, embeddings, sequence models, and transformer-based NLP workflows.

Level 10: 
Large Language Models: Basics Learn how LLMs function, including attention mechanisms, pretraining, fine-tuning, and inference concepts.

To know about the next levels,
Check the infographic below 👇 

Learn AI for free: https://lnkd.in/euYZeAdb  

Do you invest time in learning AI every day?
Comment below 👇 

♻️ Repost to help your network learn AI

You’re learning AI randomly, and that’s why you’re not improving fast.

You need a structured path that removes the guesswork.

Here are the 28 levels you should go through to go from zero to the best in the world in AI.

Level 0: 
AI Awareness: Learn what AI is and what it is not, and understand basic terminology.

Level 1: 
Digital Literacy: Master computer fundamentals, file systems, basic coding concepts, and internet research skills.

Level 2: 
Programming Foundations: Learn Python, control structures, functions, data types, and basic scripting.

Level 3: 
Math for AI Foundations: Understand linear algebra basics, probability fundamentals, and essential calculus concepts.

Level 4: 
Data Handling Basics: Learn data cleaning, preprocessing, visualisation, and working with datasets using Python libraries.

Level 5: 
Machine Learning Fundamentals: Understand supervised, unsupervised, and simple model training workflows with scikit-learn.

You're learning too slowly without realising it.

Here’s how to learn faster than ever with AI with Google NotebookLM.

About Google NotebookLM
- AI-powered “virtual research and learning assistant” that uses your uploaded content and prompt as a basis for conversation.
- Accepts diverse sources like PDFs, Google Docs, websites and Google Slides and can answer questions grounded in them.
- Generates summaries, explanations and even audio overviews (podcast-style) to help you understand learning materials quickly.

Follow these steps:
1. Go to notebooklm.google.com
2. Check any featured notebook if you want
3. Click ‘Create New Notebook’ to create a new one
4. Add the doc or link from which you want to learn
5. NotebookLM starts working on creating easy-to-digest content from your learning material.
6. You’ll get the study material summary prepared by NotebookLM.
7. Based on it, NotebookLM can create:
  - Audio podcast
  - Explainer video
  - Mind map
  - Reports
  - Flashcards
  - Quiz

How to use the output created by NotebookLM:
- You can share a custom link of your notebook for anyone to use it.

Do’s of using NotebookLM:
✅ Upload clean, relevant sources.
✅ Ask clear, specific questions.
✅ Organise into topic notebooks.
✅ Use summaries, quizzes, and overviews.
✅ Cross-check outputs with sources.

Don’ts of using NotebookLM:
❎ Don’t expect knowledge beyond uploads.
❎ Don’t dump irrelevant content.
❎ Don’t ask vague, broad questions.
❎ Don’t over-trust compressed summaries.
❎ Don’t share sensitive data.

To know more about NotebookLM,
Check the infographic below 👇

Have you tried using AI for learning?
Comment below 👇

Learn AI for free: https://lnkd.in/euYZeAdb 

♻️ Repost to help your network learn efficiently with AI

You're learning too slowly without realising it.

Here’s how to learn faster than ever with AI with Google NotebookLM.

About Google NotebookLM
AI-powered “virtual research and learning assistant” that uses your uploaded content and prompt as a basis for conversation.
Accepts diverse sources like PDFs, Google Docs, websites and Google Slides and can answer questions grounded in them.
Generates summaries, explanations and even audio overviews (podcast-style) to help you understand learning materials quickly.
Try here: notebooklm.google.com

Follow these steps:
Go to notebooklm.google.com
Check any featured notebook if you want
Click ‘Create New Notebook’ to create a new one
Add the doc or link from which you want to learn
NotebookLM starts working on creating easy-to-digest content from your learning material.
You’ll get the study material summary prepared by NotebookLM.
Based on it, NotebookLM can create:
Audio podcast
Explainer video
Mind map
Reports
Flashcards
Quiz

Anyone today can build an app.

With AI. In 5 minutes. From a single text prompt. Without any technical knowledge. 

Here’s the ultimate prompting guide to help you build apps with AI.

I use Replit.
It is a tool with which anyone can build mobile and web apps with AI from simple text prompts without writing a single line of code with Replit’s powerful AI agent.

How it works:
1. Go to replit.com 
2. Signup 
3. Describe the app or design idea in the build and design section
4. Select what you want to build
5. Add reference files or Figma designs or an existing project to build an app
6. Add your prompt
7. Get your prompt refined with AI if required
8. Submit your prompt
9. AI Agent starts building
10. You get the entire app built in minutes
11. Follow-up if you need any changes
12. Preview and test it
13. Invite your team to check and make any changes
14. Publish with Replit 

Do’s:
✅ Define a clear problem and user outcome before prompting.
✅ Start with a well-defined feature set and expand only after basic flow works.
✅ Provide concrete examples, data formats, and edge cases in your prompts.
✅ Test each generated feature manually in real user scenarios.

Don’ts:
✅ Do not expect the first generation to be production ready without review.
✅ Do not mix multiple unrelated features in a single long prompt.
✅ Do not skip security checks such as auth, validation, and rate limiting.
✅ Do not rely only on auto tests run by the tool without your own testing.
✅ Do not deploy to real users without monitoring, logging, and error alerts.

To get the complete guide to build apps with AI,
Check the infographic below 👇 

Try here: https://lnkd.in/e6Eua37q

What do you think about building apps with AI?
Comment below 👇 

♻️ Repost to help your network cook apps with AI

Every successful CEO has one secret weapon.

It’s not talent, money, or luck.
It’s the ability to make better decisions.

Here are 30 powerful ChatGPT prompts for efficient decision-making.

Strategic Business Decision Evaluation 
- I am deciding between [Option A], [Option B], and [Option C] for my business. Provide a structured decision matrix where you track each option against evaluation metrics such as long-term ROI, alignment, risks, and feasibility. Assign weights to each factor, rank for each score, and end with a scenario recommendation of the best choice along with possible trade-offs.
 
 Personal Life Choice Analysis 
- I need to decide between [Choice A], [Choice B], and [Choice C] for my personal situation. Consider life constraints like financial stability, budget, time, location, lifestyle impact, and weighted pros/cons to create a logical framework that concludes, supports, risks, and recommends the best direction based on what aligns with a clear justification.
 
 Career Path Decision Aid 
- I’m torn between pursuing [Career Path A] and [Career Path B]. Analyse both paths in terms of salary potential, required skills, long-term growth opportunities, and career stability. For each option note risks and rewards, highlight career paths made by others with similar roles, and decide which one is the best fit for my values [insert personal values].
 
Investment Opportunity Comparison 
- I am considering investing in [Investment A], [Investment B], or [Investment C]. Create a risk/return analysis, a timeline to liquidity, use of long-term potential gains, income stream potential, and which option is most aligned with my financial portfolio strategy. Provide a decision recommendation of which option is superior for my investor profile.
 
 Time Management Decision Support 
- I have [X hours] available per day and need to allocate them between [Activity A], [Activity B], and [Activity C]. Optimise the schedule with balances in effectiveness, rest, and long-term productivity. Recommend the best time allocation plan with practical proof and examples, and create a framework based on a sample day plan.

Note: AI can help you with fast decision-making, but take all important decisions only by adding your human thinking and intuition to it.

To get more ChatGPT prompts, 
Check the infographic below 👇 

Which one prompt did you like the most here?
Comment below 👇 

Learn AI for free: https://lnkd.in/euYZeAdb 

♻️ Share this post to help your network use AI for better decision-making

Every successful CEO has one secret weapon.

It’s not talent, money, or luck.
It’s the ability to make better decisions.

Here are 30 powerful ChatGPT prompts for efficient decision-making.

Strategic Business Decision Evaluation 
I am deciding between [Option A], [Option B], and [Option C] for my business. Provide a structured decision matrix where you track each option against evaluation metrics such as long-term ROI, alignment, risks, and feasibility. Assign weights to each factor, rank for each score, and end with a scenario recommendation of the best choice along with possible trade-offs.
 
 Personal Life Choice Analysis 
I need to decide between [Choice A], [Choice B], and [Choice C] for my personal situation. Consider life constraints like financial stability, budget, time, location, lifestyle impact, and weighted pros/cons to create a logical framework that concludes, supports, risks, and recommends the best direction based on what aligns with a clear justification.

You don't need to spend hundreds of hours on learning the old way. 

Perplexity can become your smartest tutor only if you know what to ask.

Here are 20 Perplexity prompts that will help you learn more in less time.

Here are the use cases for which you can use Perplexity for learning:
✅ Comprehensive Topic Overview
✅ Step-by-Step Learning Roadmap
✅ Concept Comparison Table
✅ Academic Paper Summary & Analysis
✅ Beginner-Friendly Theory Explanation
✅ Chronological Timeline of Key Events
✅ Case Study Breakdown
✅ List of Best Practices
✅ Technical Term Deep Dive
✅ Overview of Research Methodologies

And more use cases with prompts are covered in the infographic below 

Will you try using Perplexity for learning?
Comment below 👇 

Learn AI for free: https://lnkd.in/euYZeAdb 

🔁 Repost to help your network use AI for learning

You don't need to spend hundreds of hours on learning the old way. 

Perplexity can become your smartest tutor only if you know what to ask.

Here are 20 Perplexity prompts that will help you learn more in less time.

Here are the use cases for which you can use Perplexity for learning:
✅ Comprehensive Topic Overview
✅ Step-by-Step Learning Roadmap
✅ Concept Comparison Table
✅ Academic Paper Summary & Analysis
✅ Beginner-Friendly Theory Explanation
✅ Chronological Timeline of Key Events
✅ Case Study Breakdown
✅ List of Best Practices
✅ Technical Term Deep Dive
✅ Overview of Research Methodologies

It took them 9 years to hit $500,000,000 ARR.

Then just one year to 2x it.

This is what you get,
When infrastructure finally catches up with ambition.

Because scaling businesses globally shouldn’t feel like fighting gravity.

The fastest-growing companies, from Canva to Brex, aren’t waiting on legacy systems.
They’re growing with Airwallex

They’re moving money, 
Across 60+ currencies without friction.
Managing spend, 
And scaling financial operations for global businesses.

$1,000,000,000 ARR isn’t just a regular financial milestone.

It’s proof that borderless finance is becoming the default layer of global business.

And for founders building the next wave of AI, SaaS, or e-commerce,
This is the infrastructure quietly powering your growth behind the scenes.

The internet made business global.
Airwallex made finance global.

Why I like Airwallex 👇
→ Trusted by 150,000+ companies.
→ Built for scale, speed, and smarter cross-border ops.

Legacy banking had a good run.
But the next era of growth?
It’s built on infrastructure that moves as fast as you do.

Learn more here 👉 https://lnkd.in/e8KW2nv8

What do you think about using such a globally scalable financial infrastructure in businesses? 
Comment below 👇 

♻️ Share this to help your network use modern financial systems in their businesses 

#AirwallexPartner

Aspiring Data Analyst | Excel 📊 | Power BI 📈 | SQL 🛢️ | Python | AI & Tech Enthusiast 🧠 | Content Creator | Sharing AI Tools & Data Trends 🤖 | Turning Data into Insights Problem-Sol | Open for Brand Collaborations🤝

I am a Computer Engineering graduate from SHUATS, Prayagraj, with a strong passion for data analytics and problem-solving. I have hands-on experience in data cleaning, visualization, and statistical analysis using Python (Pandas, NumPy, Matplotlib, Seaborn), SQL, and Power BI/Excel for effective data manipulation and reporting.

Through academic projects and self-driven learning, I have developed a keen ability to transform raw data into actionable insights, helping businesses make informed decisions. I thrive on finding patterns in data, optimizing processes, and deriving meaningful conclusions to drive business growth.

As a continuous learner, I stay updated with industry trends, new analytics techniques, and evolving technologies. My goal is to kickstart my career in data analytics and contribute to an organization where I can apply my skills to solve real-world challenges.

📩 Let’s connect! Whether you’re looking for a data-driven problem solver, discussing analytics trends, or exploring opportunities, I’d love to chat!

Saurabh Dubey

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https://lnkd.in/g5X6HVSX

python 

Chatgpt Can Get You Hired Faster Than Any Recruiter

Copy these 7 prompts to land your dream job:

1) Resume Transformer Transform my resume [paste resume] for [target position] into an ATS-optimized document that highlights achievements and incorporates industry keywords.

2) Cover Letter Creator Write a personalized cover letter for [position] at [company] that connects my experience to their needs and demonstrates why I'm an ideal fit.

3) Interview Answer Builder Create a STAR response for "[interview question]" using my experience with [example], making it concise and impressive.

4) Job Description Decoder Analyze this job listing [paste listing] to identify key requirements, hidden expectations, and phrases to include in my application.

5) LinkedIn Optimizer

Improve my LinkedIn profile [paste sections] to attract recruiters for [desired role], with compelling achievements and keywords.

6) Salary Negotiator

Create a negotiation script for my offer from [company/role] [paste details] to maximize compensation while maintaining relationship.

7) Interview Question Generator

Prepare me for my [company/position] interview with likely questions based on this job description [paste description].

Say goodbye to job rejections! 🚀

Use ChatGPT to create an ATS-friendly resume and land your dream job faster. Here are 7 quick prompts to boost your chances.

Start optimizing today and stand out!

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Happy Learning 💕

Docs

Do you even realize you’ve been helping people find jobs —
every time you share job opportunities, career tips, or course-based content that helps them upskill, prepare for interviews, and get hired?

But here’s the thing…
Are you actually earning from it?

Because you could be making $1,000+/week —
without changing a single thing about what you already do.

Let’s see how 👇

You’re the creator people trust.
They DM you for openings.
They save your posts.
They wait for your next update.

You’ve built influence —
now it’s time to build income too.

 Artha Job Board helps you launch your very own job platform —
where your audience can find real opportunities,
and you earn from every click.

With 4M+ preloaded job ads, refreshed daily,
and everything running automatically in the background —
all you do is share… and earn.

Here’s why creators are switching to Artha 👇
⚡ No coding. No setup. No maintenance.
⚡ Multiple income streams — ads, partner programs, premium licenses & more.
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You don’t need to change your content.
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SQL is more than writing queries — it’s about understanding how data is structured, how it flows, and how to think in terms of sets rather than individual rows.

Here are some core areas every SQL learner should master:

Different types of joins (INNER, LEFT, RIGHT, FULL)

Aggregate functions like COUNT, SUM, AVG, MIN, MAX

Using GROUP BY with HAVING for aggregated filtering

Window functions such as RANK, DENSE_RANK, ROW_NUMBER

Subqueries and Common Table Expressions (CTEs)

Writing conditional logic with CASE

Knowing when to use EXISTS vs IN

Proper handling of NULL values

Basics of indexing and performance optimization

Essential SQL commands to revise:

SELECT

FROM

WHERE

GROUP BY

ORDER BY

JOIN

UNION

LIMIT / OFFSET

INSERT, UPDATE, DELETE

CREATE / ALTER TABLE

LIMIT / OFFSET
INSERT, UPDATE, DELETE
CREATE / ALTER TABLE

If you’re gearing up for SQL interviews, make sure you go through these high-value LeetCode questions:

1. Combine Two Tables

2. Second Highest Salary

3. Rank Scores

4. Nth Highest Salary

5. Employees Earning More Than Their Managers

6. Department Top Three Salaries

7. Customer Who Never Orders

8. Game Play Analysis (Complete Series)

9. Duplicate Emails

10. Consecutive Numbers

If this adds value, you can connect with and don’t forget to repost so more people in your network can benefit.
Saurabh Dubey

Take your time, understand the logic.
In SQL, clarity beats shortcuts every single time.

SQL High-Quality Notes!
Saurabh Dubey

SQL 

Statistics Roadmap – Beginner to Advanced.

Confused about where to start with Statistics? Don’t worry—here’s a clear path that takes you from beginner to pro 👇

 Beginner – Build Your Foundation

Understand Population vs Sample

Learn Types of Data → Qualitative (categories) & Quantitative (numbers)

Grasp Scales of Measurement → Nominal, Ordinal, Interval, Ratio

Start with Descriptive Statistics → Mean, Median, Mode, Variance, Standard Deviation, Histograms & Skewness

👉 Goal: Learn how to summarize and describe data.

 Intermediate – Start Analyzing Deeper

Sampling Techniques → Random, Stratified, Systematic, Cluster

Correlation & Covariance → Understand relationships between variables

Probability Basics → Events, Rules, Conditional Probability

Probability Distributions → Normal, Binomial, Poisson, Uniform, Exponential

Central Limit Theorem (CLT) → Why samples behave like normal distribution

👉 Goal: Learn how to analyze patterns & relationships.

 Advanced – Make Decisions & Predictions

Inferential Statistics → Hypothesis Testing (H₀ vs H₁), P-values, Confidence Intervals

Statistical Tests →

Z-Test (large n, σ known)

T-Test (small n, σ unknown)

Chi-Square (categorical data)

ANOVA (compare multiple groups)

Regression & Forecasting → Linear Regression, Logistic Regression

Advanced Distributions & Modeling → Log-normal, Multinomial, Bayesian concepts

👉 Goal: Use statistics to predict, decide, and build models for Data Science, AI & Analytics.

 Summary:

Beginner = Describe data

Intermediate = Find patterns

Advanced = Make predictions & decisions

Mastering this flow will make your journey in Data Science, Machine Learning, and Analytics much smoother. 

#Statistics #DataScience #MachineLearning #Analytics #Learning

Follow for more content ❤️ 
Saurabh Dubey

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Become an SQL Expert – From Zero to Hero with Just One Ultimate Resource!

If you’ve ever struggled to understand how SQL really works — from basic queries to advanced optimization — this guide is exactly what you need.

This comprehensive 100-question SQL Master Guide is your complete roadmap to mastering database concepts, cracking interviews, and applying SQL confidently in real-world data analysis or development projects.

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Every concept includes examples, logic, and how it’s used in actual companies.

3. Advanced SQL That Sets You Apart

These topics create the gap between beginners and working professionals:

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Handling large datasets efficiently

This is where your interview performance jumps to the next level.

4. Real-World Business Scenarios

Not just theory — you’ll solve practical problems such as:

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These are the exact problems you get in analytics, backend, and engineering interviews.

 5. Interview-Ready Question Format

All 100 questions are structured in a clean Q&A format:

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Practical query

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📘 Who Is This For?
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Anyone wanting to become truly strong in SQL

If you’re serious about building a future in data, this is your toolkit.

Download the Complete VIP PDF (attached in the post)

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Your SQL mastery begins today.

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Follow for more content ❤️ 
Saurabh Dubey

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Kickstart Your Blockchain Journey — Practical, Live & Industry-Ready Training

BlockseBlock is launching a hands-on Blockchain Training Program from the 16th — perfect for developers who want to build real Web3 projects, understand how decentralized systems work, and grow their career in one of the fastest-rising tech domains.

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During a high-stakes client negotiation, Amit noticed the client frequently asking him to repeat himself.

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Saurabh Dubey

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Most People Fail Python Interviews — Don’t Be One of Them!

Python isn’t just another programming language —
It’s the engine behind Data Science, Web Development, Machine Learning, Automation, and Cloud Engineering.

But here’s the truth no one tells you 👇
❌ Interviewers don’t care if you know syntax.
✅ They care if you can think, optimize, debug, and build like an engineer.

And that’s exactly why I’ve created a “Top 50 Python Interview Questions” Premium PDF — crafted from real interview experiences at MAANG-level companies and high-growth startups.

💼 This guide will help you:

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📘 What’s inside the PDF:

🔹 Core Python concepts (datatypes, loops, OOPs, functions)
🔹 Advanced topics — generators, decorators, iterators, context managers
🔹 Exception handling, memory optimization, GIL & concurrency
🔹 Modules, packages & file handling
🔹 Real-world coding challenges that test logic
🔹 SQL + Python integration (super important for Data roles!)
🔹 Practical interview Q&A with clear, concise explanations

🎯 Perfect for:

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Freshers entering tech

Professionals targeting Python, Data, or Automation roles

Anyone serious about cracking technical interviews

Bonus: Real interview insights, mistakes candidates make, and what actually impresses interviewers.

👇Comment “PYTHON50” below, and I’ll send you the complete PDF.

Let’s make sure your next Python interview ends with:
💬 “You’re hired!”

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Saurabh Dubey

#Python #PythonInterview #DataScience #MachineLearning
#CodingInterviews #TechJobs #Programming #TechCareers
#DataAnalytics #PythonDeveloper

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🚨hiring #sde #freshers#developer🚨

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The Battle

Adam Biddlecombe

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Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Adam Biddlecombe's LinkedIn Performance

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