Champak Tech Sutras

16/05/2026

Saturday Questions for 16-05-2026 is live.

This practice set focuses on Python DSA with patterns, prefix sum, sliding window, strings, sets, counting, and subarray problems.

Start from very simple questions and move step by step toward interview-style problem solving.

Practice here:
https://www.learnwithchampak.live/2026/05/saturday-questions-16-05-2026.html

Topics covered:
Pattern printing
Prefix sum
Range sum
Sliding window
String problems
Set and frequency problems
Subarrays

A useful practice set for students preparing for coding tests and technical interviews.

09/05/2026

Saturday Questions 09-05-2026 is live.

This week’s focus is Beginner DSA in Python.

The idea is simple: learn Data Structures and Algorithms step by step, with questions that help beginners think clearly, trace logic, and build confidence in problem solving.

Useful for students who are starting DSA with Python and want regular practice without feeling overwhelmed.

Read and practice here:
https://www.learnwithchampak.live/2026/05/saturday-questions-09-05-2026.html

To consult, click the phone icon at the bottom right of the page.

Programmers Picnic by Champak Roy

Beginner DSA Python coding test for Saturday Questions with list, string, loop, search, sorting, frequency, two-sum, stack, and palindrome practice.

02/05/2026

Starting

Saturday Questions — Sorting Trace & Algorithm Detection | Programmer's Picnic ...

28/04/2026

🚀 Launching My Live AI & Machine Learning Course This Sunday!

After months of planning, building, and refining — I’m excited to open enrollment for my Live AI-ML Course at Learn With Champak.

This is not just another recorded course.

👉 It’s a live, hands-on learning experience where we build things together from ground zero to real-world applications.

🔥 What you’ll get:

- ✅ Beginner to Advanced (Zero → Expert)
- ✅ Live coding sessions on Zoom
- ✅ Doubt solving + discussion via WhatsApp
- ✅ Assignments, MCQs & mini projects
- ✅ Real-world AI/ML use cases

📅 Batch starts this Sunday

Limited seats to ensure proper interaction.

💡 Who is this for?

- Students starting AI/ML from scratch
- Developers wanting to move into AI
- Anyone serious about learning by doing

👉 Course Details:
https://aiml.learnwithchampak.live/coursemap/

👉 Join WhatsApp Group (updates + access):
https://chat.whatsapp.com/CLCBRoi5AuB816tQ86hpQb

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I’ve designed this course the way I wish I had learned AI — structured, practical, and interactive.

If you’ve been waiting for the right time to start AI/ML…
this is it.

A 16-week beginner-friendly AI-ML with Python course by Champak Roy with live Zoom classes, WhatsApp doubt support, datasets, assignments, projects, and a final capstone.

27/04/2026

Multiple Inputs Linear Regression

https://aiml.learnwithchampak.live/regression/multipleinputs/

25/04/2026

Saturday Questions ❓
Sorting Trace & Algorithm Detection
Understand how arrays change step by step
Saturday, 25-04-2026

https://www.learnwithchampak.live/2026/04/saturday-questions-25-04-2026.html

24/04/2026

Java Lesson — While Loops, Nested While Loops, and Summation of Series
A full lesson from level zero to advanced, with special focus on summation of series.

A complete beginner-to-advanced Java lesson on while loops, nested while loops, and summation of series with examples, assignments, and interactive MCQ quiz.

23/04/2026

Today’s Task: Getting Started with Google Colab
1: What is Google Colab?
Google Colab (short for Colaboratory) is an online IDE (Integrated Development Environment) provided by Google. It allows you to write and run Python code directly in your browser without installing anything on your computer.
2: Why use Colab?
* Free access to powerful CPUs, GPUs, and TPUs
* No setup required
* Works from any device with internet
* Easy sharing and collaboration
Go to this page, follow the instructions and post your programs screenshots

https://theprogrammingsutras.substack.com/p/starting-the-programming-journey
🙂

Writing the Hello World Program using Python on Colab

22/04/2026

A list of terms in and

1. What is AI?
2. What is Machine Learning?
3. Data
4. Dataset
5. Feature
6. Label / Target
7. Model
8. Training
9. Testing
10. Prediction
11. Regression
12. Classification
13. Supervised Learning
14. Unsupervised Learning
15. Overfitting
16. Underfitting
17. Accuracy
18. Loss
19. Deep Learning
20. Neural Network

Go to this page and read about them.
https://aiml.learnwithchampak.live/lessons/terms

22/04/2026