CS CORNER Sunita Rai
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All study material AND coding related stuffs 🎁

You will find here ❤

Group Link: telegram.me/cscorner
Discussion Link: telegram.me/cscornersunitarai

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Link : https://www.instagram.com/cscornersunitarai
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Git Basics
Don’t let AI replace your job. Let it upgrade your career. 🚀

AI hiring is booming in 2025, and the real advantage now is hands-on skills with actual AI tools.

Coursera’s AI tracks are great for beginners and career changers, offering job ready skills from LLMs to RAG systems & agentic AI.

These programs teach real AI tools, help you build portfolio projects, and offer tracks for all skill levels.

Best Courses:👇

AI For Everyone
https://imp.i384100.net/POXGkR

Prompt Engineering for ChatGPT
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IBM RAG & Agentic AI
https://imp.i384100.net/XmbBZ3

Microsoft AI & ML Engineering
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Google AI Essentials
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These courses are built with industry experts so you learn what companies actually use.

If you’re aiming for an AI career before 2026, now is the time to start.
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Visualizing SQL Queries

Note: The actual execution sequence may differ from this mental model due to optimization strategies employed by the query optimizer.
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Hi Everyone! 👋
We are working on a really exciting project — a new learning app for students (10–18) where you learn real-life skills like Coding, AI, Finance, Public Speaking & Entrepreneurship through fun missions, not boring lectures 😄🔥

We’re trying to make learning practical, useful & super engaging — and your opinion will really help us shape it 💛

It’s a short 1-minute survey:
👉https://docs.google.com/forms/d/e/1FAIpQLSfU1L_yjUlOQCFGL92Ph36sPGxjs1Tf75povTO-ow-KEDsysg/viewform

Would really appreciate your response 🙏
Thank you so much! 🚀
🔅 Most important SQL commands
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📊 Data Science Roadmap at a Glance

Master the key pillars of Data Science step by step:

• Math & Stats: Build foundations in Linear Algebra, Probability, and Hypothesis Testing.

• Programming: Learn Python/R and SQL for data handling and analysis.

• Visualization: Use Tableau, Power BI, or Excel to tell stories with data.

• Feature Engineering: Focus on feature selection, encoding, and generation.

• Machine Learning: Start with basics, then explore advanced models like XGBoost.

• Deep Learning: Dive into Neural Networks, CNNs, and RNNs with TensorFlow or PyTorch.

• NLP: Work with text data using classification and word embeddings.

• Deployment: Deploy models using Flask, Django, or cloud platforms.

🎯 Tip: Learn consistently — Data Science is a journey, not a sprint.
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New blog on power BI
What is API Gateway?
Happy New Year Everyone ❤️
Thank you for all your support ❤️
Wishing you good luck for this year 😊
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