"How many AI tools do you know?"

That's how I opened my live YouTube session last week – a simple question that got everyone thinking. The chat started buzzing. "ChatGPT," someone typed. "Maybe Gemini?" another person added.

What they didn't know yet? We were about to explore five game-changing tools that would completely transform how they approach data analysis, coding, and productivity.

By the end of that hour-long session, the energy was electric. Comments flooded in: "Why didn't I know about these earlier?" "This just saved me hours on my project!" "Can we do this again?"

Let me walk you through exactly what happened – and more importantly, which tools you need to start using today.

🎥 Watch the full session here

Setting the Right Expectations

Before diving into tools, I made something crystal clear to everyone watching: AI tools aren't here to steal your job. They're here to give you back your time.

Think about it. How many hours do you spend writing boilerplate code? Debugging syntax errors at 2 AM? Creating documentation nobody reads?

That's not where your value lies.

Your value is in understanding data, asking the right questions, building models that solve real problems, and communicating insights that drive decisions.

Everything else? Let AI handle it.

Tool #1: ChatGPT – Beyond the Basics

Yes, I started with the obvious one. But here's the thing – most people are using ChatGPT all wrong.

During the live session, I demonstrated something that made the chat explode. I showed them how to generate practice problems, not just get answers.

Here's what I did live:

I prompted ChatGPT: "Generate 20 practical Python tasks from OOP and Collections topics. Make sure to keep the level from beginner to intermediate."

Within 30 seconds, I had a comprehensive list of 20 practice problems, organized by topic, with increasing difficulty levels.

Someone in the chat wrote: "I spent my entire Sunday creating similar problems for practice!"

That's exactly the point.

The Right Way vs. The Wrong Way

I emphasized this repeatedly during the session: Don't ask ChatGPT for answers. Ask it for questions.

When your teacher gives you homework, don't just paste it into ChatGPT. That kills your logic-building ability. Your brain will shut down.

Instead, use ChatGPT to:

• Generate practice problems after you've learned a concept
• Get step-by-step logic (not direct code) when you're stuck
• Create documentation for code you've written
• Debug by understanding the approach, not copy-pasting solutions

I also showed them the power of context management. One crucial tip I shared: Always use separate chats for different topics.

ChatGPT is memory-based. If you're working on Python practice problems, don't suddenly ask it to write song lyrics in the same chat. Open a new chat. This way, ChatGPT understands your context and gives progressively better responses.

Tool #2: GitHub Copilot – Your AI Pair Programmer

This is where things got really interesting during the live session.

I opened VS Code on screen with GitHub Copilot enabled and started coding in real-time. No script. No preparation. Just genuine coding.

What blew everyone's mind: As I typed function names and comments, Copilot suggested entire blocks of code. Data validation functions, preprocessing steps – all intelligently autocompleted.

But here's the magic: It learns YOUR coding style.

When I wrote a custom function in a specific way, Copilot started suggesting similar patterns for other functions. It wasn't generic code – it was code that looked like I wrote it.

A student asked in the comments: "Is this cheating?"

My response resonated with many: "Is using a calculator cheating in engineering? No. It's using the right tool for the job. Your brain should focus on logic, not memorizing syntax."

How to Set It Up (I Showed This Live)

1. Go to GitHub Copilot's website
2. Sign in with your GitHub account
3. Install it as an extension in VS Code
4. It's completely free now (it used to be paid!)

During the demo, I showed how the Copilot icon appears in your editor. When it's disabled, you click to enable completions, and boom – AI assistance while you code.

I wrote a simple function definition with a docstring: "Addition of two numbers" – and Copilot autocompleted the entire function, including variable names, logic, and return statement. Just press Tab to accept.

Tool #3: Text2SQL AI – The SQL Game-Changer

This tool got the loudest reaction during the session.

For anyone who's struggled with SQL queries – and let's be honest, that's most of us – this is revolutionary.

Live Demo: I showed a complex database scenario. Multiple tables, foreign keys, the kind of structure that turns SQL queries into nested nightmares.

Then I used Text2SQL AI with natural language:

"List all products along with category from a single table called products. Note that I don't have any foreign key or other tables."

The AI generated perfect SQL instantly. When I tried a more complex query about category-wise analysis, it handled joins, aggregations, and filtering flawlessly.

Someone asked: "Won't this make us lazy? Shouldn't we learn SQL properly?"

My answer: Learn SQL fundamentals? Absolutely. Understand joins and aggregations? Non-negotiable. But spending 45 minutes debugging a query because you missed a comma? That's not learning. That's suffering.

Text2SQL AI lets you focus on what questions to ask your data, not how to write perfect syntax.

The Free Usage Tip

Yes, it's premium (20 credits free). But here's what I shared during the session: Use temporary email accounts to keep trying it for learning purposes. Your goal isn't to depend on it forever – it's to learn how complex queries are structured.

Tool #4: Powerdrill AI – The Hidden Gem

I called this the "hidden gem" during my session, and for good reason.

Live Demo: I uploaded an IPL 2024 CSV dataset on screen. The file had match data – teams, scores, toss decisions, winners, player of the match, etc.

I clicked one button: "Generate Data Report"

What happened next made jaws drop. Within minutes, Powerdrill AI:

• Analyzed the entire dataset automatically
• Created multiple visualizations (pie charts, bar charts, scatter plots)
• Generated insights I hadn't even thought to look for
• Produced a complete executive summary
• Explained the reasoning behind each analysis

The report included:

• Match winners overview with team performance metrics
• Top performers (Kolkata won 11 times, Rajasthan 9 times)
• Toss decision analysis with percentage breakdowns
• Correlation analyses between different variables
• Trend identification in team performances

And here's the kicker – every visualization came with detailed descriptions in proper analytical format, just like you'd write in a professional report.

What makes it special: It doesn't just analyze. It explains its reasoning. Why did it flag this correlation? What assumptions is it making?

One student commented: "This is like having a senior data analyst guiding you."
Exactly.

Export Everything

I showed how you can download the entire report as:

• Word document
• Markdown file
• PDF
• PowerPoint presentation
• Even integrate directly with Notion or Google Docs

Plus, you get the actual Python code it used for analysis. Want to learn? Read the code. Want to modify? Edit and re-run.

Tool #5: Quadratic AI – Where Spreadsheets Meet Intelligence

The final tool was a surprise for many during the session.

Here's the scenario I explained: You're an Excel expert but don't know Python. Or you're a Python wizard but struggle with spreadsheets. Quadratic AI bridges that gap.

Live Demo: I showed how you can:

1. Generate dummy data with AI: I literally typed "List 20 dummy product data along with category and price" and it created a perfect table
2. Write Python code in spreadsheet cells: Yes, actual Python code alongside Excel formulas
3. Use AI to generate visualizations: I asked it to "create pie chart category-wise" and it wrote the Python code AND displayed the chart

The beauty? You can work in whichever language you're comfortable with and get outputs in the format you need.

The Real Power

During the live session, I demonstrated:

• Starting with a blank sheet
• Using AI to populate data
• Writing natural language commands to analyze that data
• Getting Python code that processes everything
• Viewing results right there in the spreadsheet

Someone in the chat said: "This is perfect for moving from quick exploration to serious analysis!"

That's exactly right.

The Question Everyone Asked

About halfway through the session, this question came up repeatedly:

"Milan sir, if AI does all this, what's left for us to do?"

This deserves a complete answer.

Here's what AI CAN'T do:

• Understand business context and domain knowledge
• Ask the right questions that solve actual problems
• Interpret results in meaningful, actionable ways
• Make ethical decisions about data usage
• Communicate insights to non-technical stakeholders
• Think creatively about unconventional solutions

AI tools handle the mechanical work. YOU handle the thinking work.

The best data scientists won't be those who code fastest or write the most complex queries. They'll be the ones who ask better questions, see patterns others miss, and turn data into decisions that matter.

My Challenge to Every Student Watching

At the end of the session, I left everyone with this:

This week, pick ONE tool. Use it for ONE task. Just one.

Maybe it's using ChatGPT to generate practice problems. Maybe it's trying GitHub Copilot for your next script. Maybe it's converting one complex query with Text2SQL AI.

Start small. Build confidence. Then expand.

The goal isn't to become dependent on AI. It's to become more productive, more creative, and more focused on work that actually matters.

Key Takeaways From the Session

Throughout the live session, I emphasized these points:

1. Don't use AI to get answers – use it to learn methods
2. Context management is crucial (separate chats for separate topics)
3. Focus on logic, not syntax – let AI handle the syntax
4. Learn from AI-generated code – read it, understand it, then apply it
5. These tools are for learning, not replacing your brain

Why I Do These Sessions

As a Subject Matter Expert at Red & White Skill Education, I've trained hundreds of aspiring data scientists and AI/ML enthusiasts. Every session reinforces one truth:

The best professionals aren't working the hardest. They're working the smartest.

These AI tools aren't replacing data scientists – they're elevating them. The students who embrace these tools today will be the senior analysts and ML engineers tomorrow, not because they learned shortcuts, but because they learned to amplify their capabilities.

The live format on YouTube was intentional. I wanted real questions, real struggles, real "aha!" moments. And based on the engagement, the comments, and the feedback, we definitely achieved that.

Important Reminders

Before we ended the session, I made sure everyone understood:

• Attendance matters: For Red & White students, I reminded them to submit feedback with their GR ID and Branch Code
• Questions welcome: The comment section is always open for doubts and discussions
• Keep exploring: The tools I showed are just the beginning – there are countless more to discover

What's Next?

This was just the first of many such sessions. The landscape of AI productivity tools evolves every week. New capabilities, new integrations, new possibilities.

I'll continue hosting these live sessions on YouTube, exploring cutting-edge tools, and showing practical applications that make a real difference in workflows.

Because here's what I believe: Education shouldn't just teach you what to think – it should give you the tools to think faster, work smarter, and create better.

🎥 Missed the live session? Don't worry – watch the replay here

📋 Tools Covered:

1. ChatGPT – Enhance coding, debugging, and documentation
2. GitHub Copilot – AI-powered code completion (now free!)
3. Text2SQL AI – Natural language to SQL conversion
4. Powerdrill AI – Automated data analysis and reporting
5. Quadratic AI – Spreadsheets + Python + AI integration

Er. Milan Kathiriya is a Subject Matter Expert at Red & White Skill Education, specializing in AI/ML, Data Science, and productivity enhancement through intelligent tools. He conducts live training sessions, workshops, and expert talks for students and professionals looking to maximize their potential in the data-driven world

Subscribe to stay updated on upcoming sessions where we explore more AI tools and techniques that can transform your workflow. Have questions? Drop them in the comments – let's learn together!

Your Turn: Which tool are you going to try first? Comment below and let me know how it goes. The best learning happens when we share experiences!

Remember: Don't let AI make you lazy. Let it make you focused on what truly matters – thinking, analyzing, and creating impact.