Quantum Computing Lab

Syllabus : click here
Session plan : click here

Date	Topic	Handout	Feedback

Formal Languages and Automata Theory (2025-26)

Assignment-1 : Click
Assignment-2 : Click

Introduction to Quantum Computing (2025-26 for MTech)

Syllabus : click here
Lecture plan : click here

Classical computers are built from semiconductor chips containing billions of transistors. For decades, the number of transistors on a chip has roughly doubled every two years, a trend known as Moore’s Law. However, as transistors approach atomic scales, continuing this trend is becoming increasingly difficult, motivating the exploration of new computing paradigms such as quantum computing.

Date	Topic	Slides	Lecture Notes
09-03-26	Introduction, Why Quantum Computing? Milestones in quantum theory (Planck, Einstein, Bohr)	Slides	Notes
30-03-26	Linear Algebra, Hilbert Spaces and Quantum Mechanics Foundations	Slides	Notes

Machine Learning Skill Course ( 2025-26)

Syllabus : click here
Lecture plan : click here
Project statements : click here
report format : Title page, undertaking page, certificate page followed by
Latexformat (Suggest to use overleaf) and pdfformat
OR
worddocformat

Date	Theory Topic	Practical topic	Resources	Submission
01/12/2025	Introduction to Machine Learning	Numpy and Pandas	Theory , Lab , Data Set	Submit
08/12/2025	Data Pre-Processing and Feature Engineering	Data Cleaning, Transformation, Feature Engineering with Numpy, Pandas	Theory , Lab	Submit
15/12/2025		Data Visualization with Matplotlib & Seaborn	Lab	Submit
22/12/2025		Recap
29/12/2025	K-NN and Naive Bayes	K-NN and Naive Bayes using scikit-learn	Theory, Lab
05/01/2026	Decision Tree Classifier	Decision Tree Classifier using scikit-learn	Theory, Lab
12/01/2026	Support Vector Machine(SVM) based classifier	Support Vector Machine(SVM) based classifier using scikit-learn	Theory, Lab
16/02/2026		Linear Regression using scikit-learn	Theory, Lab

General Resources:

• Python3 Tutorial
• Python for Everbody
• Basics of Python
• Kaggle
• NumPy Tutorial
• Pandas Tutorial

Machine Learning - Minor (2025-26)

Welcome to the course

• Lecture material : Click here
• Videos: Click here

Design and Analysis of Algorithms ( 2025-26)

Welcome to the course

• Lecture material : Click here
• Selected Toipcs Videos: Click here
• Quiz-1 paper with solutions : QPaper , Deatiled_solutions , Explanation Video
• MID-1 paper with solutions : QPaper , Detailed_solutions, Explanation Video
• hacker rank coding contest (Greedy and DP-1D): JNTUGV_III_CSE_Greedy_DP1D

• Assignment -2 : Solving 4 X 4 Sudoku using back tracking and draw a state space tree
• Select a puzzle based on last two digits your roll number (501 should select puzzle 01)
• Click here for list of puzzles

We will be following two text books
• Text book1 : Fundamentals of Computer Algorithms by Ellis Horowitz, Sartaj Sahni, Sanguthevar Rajasekaran
• Text book2 : Introduction to Algorithms by Thomas H. Cormen, charles e. leiserson, ronald l. rivest, clifford stein
• (Unit-I) Introduction : Text book1 (Pages 1 to 62)
• (Unit-II) Divide and conquer : Text book1 (Pages 136 to 196)
• (Unit-III) Greedy : Text book1 (Pages 210 to 269)
• (Unit-III) Dynamic Programming : Text book1 (Pages 272 to 317)
• (Unit-IV) BackTracking : Text book1 (Pages 359 to 392)
• (Unit-V) Branch and Bound : Text book1 (Pages 399 to 431)

Design and Analysis of Algorithms(2024-25)

Welcome to the course

We will be following three text books
• Text book1 : Fundamentals of Computer Algorithms by Ellis Horowitz, Sartaj Sahni, Sanguthevar Rajasekaran
• Text book2 : Introduction to the design and analysis of Algorithms, Anany Levitin
• Text book3 : Introduction to Algorithms by Thomas H. Cormen, charles e. leiserson, ronald l. rivest, clifford stein
• (Unit-I) Introduction : Text book1 (Pages 1 to 62)
• (Unit-II) Decrease and conquer : Text book2 ( Click here )
• (Unit-II) Divide and conquer : Text book1 (Pages 136 to 196)
• (Unit-II) Transofrm and conquer : Text book2 ( Click here)
• (Unit-III) Greedy : Text book1 (Pages 210 to 269)
• (Unit-IV) Dynamic Programming : Text book1 (Pages 272 to 317)
• (Unit-V) BackTracking : Text book1 (Pages 359 to 392)
• (Unit-V) Branch and Bound : Text book1 (Pages 399 to 431)