Compiler Design Lab (2026-27)

Welcome to the course :

• Lab Session Plan:Click Here
• TinyCStr description
• We will be using SLY (Sly Lex Yacc) for designing compiler of TinyCStr
• David Beazley talk on PLY/SLY

Date	Topic	Resources	Evaluation	Feedback
18-07-2026	TinyCStr description; Sly Lexer/Parser demo	SLY (Sly Lex Yacc) TinyCStr description Sly Lex Yacc Calculator Demo	Clickhere	Clickhere
21-07-2026	Lexer of TinyCStr Level1	Partial Implementation with TODOs Level 1 Lexer		Clickhere
28-07-2026, 01-08-2026	Parser and AST of TinyCStr Level1	AST practice code (Should try before 25-07-2026) Partial Implementation with TODOs Level 1 Parser + AST		Clickhere
04-08-2026	Three-Address Code and MIPS assembly Level1	MIPS assembly reference Function call activation record with MIPS Three address code Gen Practice code MIPS Assembly Gen practice code		Clickhere
11-08-2026	Level 2 Lexer and Parser Type Casting, Relational/Ternary Op- erators	Partial Implementation with TODOs Level 2 Lexer + Parser		Clickhere
18-08-2026	Level2 Semantic Analyzer	Partial Implementation with TODOs Level 2 Semantic Analyzer		Clickhere
01-09-2026	Level2 Target Code generator

Compiler Design (2026-27)

Welcome to the course

• Compiler Engineer Career discussion in LLVM Social Bangalore
• Lexical Analysis
• Parsing
• Syntax Directed Translation
• Intermediate Code generation

Python Programming (2026-27)

Welcome to the course
Lecture Plan: Clickhere
Important point: "Python is both compiled and interpreted . When the command 'python example.py' is executed, the Python interpreter first compiles example.py into bytecode (.pyc), which is then executed by the Python Virtual Machine (PVM). Like Java, Python uses bytecode and a virtual machine. The difference is that the JVM uses Just-In-Time (JIT) compilation for faster execution, whereas the PVM executes the bytecode directly."
Resources:

• Python3 Tutorial
• Python for Everbody
• Basics of Python

Quantum Computing Lab

Syllabus : click here
Session plan : click here

Date	Topic	Handout
01-04-2026	Qiskit Basics, Classic Vs Quantum Bits	Click here
08-04-2026	Single-Qubit Gates & Bloch Sphere Visualisation	Click here
13-04-2026	Multi-Qubit Gates & Entanglement	Click here
17-04-2026	Bell State Preparation & Verification	Clickhere
17-06-2026	Deutsch-Jozsa Algorithm	Clickhere
15-07-2026	Grover’s Search Algorithm	Clickhere

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
Read	Role of Biology in Quantum Computing	Slides	Notes
15-04-26	Classical vs. Quantum Logical Operations	Slides	Notes
22-04-26	Classical Computing Limitations	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)

Computer Organization (2024-25-EEE)

Welcome to the course

Two text books we will be following
• Text book1 : Computer Organization by Carl Hamacher, Zvonks Vranesic, Safea Zaky 5th edition
• Text book2 : Computer System Architecture by M. Morris Mano
• (Unit-I) Basic Structure of Computers : Text book1 (Pages 2 to 23)
• (Unit-I) Data Representation Toipc : Text Book2 (Page 67 to 90)
• (Unit-II) Machine Instructions and Programs : Text book1 (Pages 37 to 86)
• (Unit-III) Input/Ouput Organization : Text book1 (Pages 203 to 272)
• (Unit-IV) Memory Systems : Text book1 (Pages 291 to 358)
• (Unit-V) Processing Unit : Text book1 (Pages 411 to 440)

Machine Learning( 2023-24)

• Introduction: Slides 11 to 21
• Simple Linear Regression Slides 2 to 13
• Concept Learning, FINDS Slides 1 to 9
• Candidate elimination Slides 10 to 24
• Decison tree learning Slides 1 to 29
• Slides 2 to 14
• remaining slides shared by mail

Other resources:

• Teachable Machines By Google
• Biological Neuron and Neural networks
• Neural netowrks and Deeplearning
• Play with Neural networks
• Quality of Data

Assignment : Last date for submission is 15/04/2024

Formal Languages and Automata Theory (2023-24)

Mathematical Models:

• Finite State Automata
• Push Down Automata
• Turing Machine

23-02-2024 MID-1

• QUIZ1_KEY

Assignment : Click

Date	Topic	Resource	SampleCode
29/12/2023	Data Structure for FSA transitions
05/01/2024	Data Structure for FSA
12/01/2024	Application of FSA	FormValidation	Validationcode
02/02/2024	Application of Regular Expression

Machine Learning Lab(2023-24)

Welcome to the course

Week0: Introduction to google colab
Colab Markdown: Introduction to Markdown
Google colab: FAQs
Mounting Google drive in colab: from google.colab import drive
drive.mount('/googledrive')
Data Sets Resources : Google public data sets , Kaggle Data sets, Data Hub.io, KDnuggets , UCI Machine Learning, Yoga Pose classification , For more

Date	Topic	Resource	Evaluation	Feedback
20/12/2023	Introuction to Numpy (Numerical Python Library)	BasicTutorial
30/12/2023	Introuction to Pandas Library	Userguide	HousingPriceDS
30/12/2023	Matplotlib Library	Plot types
31/12/2023	Exploratory Data Analysis Task	Task
03/01/2024	Exploratory Data Analysis Test	DataSet	Submit
07/01/2024	Decision Tree Task	Task DataSet	Submit
20/01/2024	Regression Tree Task	Task
24/01/2024	Decision Tree Test	Lenses MONK'sProblem Breast cancer Car Evaluation	Submit
24/01/2024	Regression Tree Test	Solar Flare
31/01/2024	Perceptron	fab,fabcd data sets	Submit
07/02/2024	Linear Regression using Neural Networks	CGPAtoPercentage	Submit
14/02/2024	Forward Pass of Neural Networks	ForwardPass DataSet	Submit
21/02/2024	Back propagation Algorithm	Back Propagation DataSet

Internal Exam : Data set generation Submit
Internal Exam : Model Submit

Introduction to Python Programming(2023-24)

Resources:

• Python3 Tutorial
• Python for Everbody
• Basics of Python
• Skill Test

Date	Topic	Practice	Contests
07/08/2023	Introduction to Python
09/08/2023
16/08/2023
21/08/2023
23/08/2023			Numbersandloops
13/09/2023
20/09/2023	Object oriented programming with Python
25/09/2023	Tutorial Problems

Compiler Design (2023-24)

• Compiler Engineer Career discussion in LLVM Social Bangalore
• Lexical Analysis
• Parsing
• Syntax Directed Translation
• Intermediate Code generation
• Code Optimization
• Available Expression Analysis and Live Variable Analysis( Slides 3 to 15 and Slides 39 to 48, number on top right)
• Run time environment
• Target Code generation
• AssignmentSubmissionLink

Compiler Design Lab (2023-24)

• TinyC description
• We will be using SLY (Sly Lex Yacc) for designing compiler of TinyC
• David Beazley talk on PLY/SLY
• Level2 Details
• First Phase record Submit RollNo.pdf file and Deadline is 30/09/2023 12.00 Noon
• Lisp Expression To C Expression Vice-Versa Code ( special class on 06/11/2023)
• IntermediateCodeSample code

Date	Resource	Evaluation	Feedback
02/08/2023	gccOptions
09/08/2023	sly Lexer practice Lexical analyzer for Level1 of TinyC Level1 Description
16/08/2023	sly Parser practice Calculator using Lexer & Parser
23/08/2023	sly Praser more examples Level1 Grammar
30/08/2023	Parser for Level1 of TinyC ASTclassdefinC++ DatastructuresinPython
13/09/2023	AST for Level1 of TinyC
20/09/2023	AST for Level1 of TinyC
27/09/2023	TargetCode for Level1 of TinyC CommandlineOptionsOfCompiler MIPSInstructionSet
04/10/2023	Lab Internal Examination
11/10/2023	IntermediateCode for Level2 of TinyC
18/10/2023	TargetCode for Level2 of TinyC
01/11/2023	IntermediateCode for Level3 of TinyC
08/11/2023	IntermediateCode for Level3 of TinyC
15/11/2023	Targetcode for Level3 of TinyC

Formal Languages and Automata Theory (2022-23)

Examinations

Date	Exam	Key
29/03/2023	Quiz-I	QKey
29/03/2023	MID-I	MKey

Assignment : Click

Machine Learning Lab (2022-23) (R20)

Welcome to the course

Week0: Introduction to google colab
Colab Markdown: Introduction to Markdown
Google colab: FAQs

Date	Topic	Resource	Evaluation	Feedback
19/12/2022	Data Acquisition and Data Exploration
26/12/2022	Simple Linear Regression
02/01/2023	K-nearest neighbour
09/01/2023	Decision Tree classifier
21/01/2023	Perceptron for boolean functions
23/01/2023	simple neuron for regression
30/01/2023	Back propagation
13/02/2023	Bayes classifier

Internal Examination Submission : Submit
External Examination Submission : Submit

Machine Learning 2022-23 (R20)

18/12/22 : Welcome to the course

Date	Topic	Material
20/12/2022	Introduction	Slides 11 to 21
23/12/2022	Simple Linear Regression	Slides 2 to 13
27/12/2022	Concept Learning, Find-S	Slides 1 to 9
30/12/2022	K-Nearest Neighbour
03/01/2023	Version Spaces and Candidate elimination	Slides 10 to 24
06/01/2023	Decision Tree Learning	Slides 1 to 9
10/01/2023	Decision Tree Learning(contd)	Slides 10 to 29
13/01/2023	Preceptron Learning	Slides 2 to 14
17/01/2023	Back Propagation	Derivation
20/01/2023	Back Propagation(Contd)
24/01/2023	Back Propagation(Contd)
27/01/2023	Bayes classifier
31/01/2023	Naive Bayes Classifier
03/02/2023	Bayesian Belief Networks
07/02/2023	Bayesian Belief Networks(Contd)
10/02/2023	Radial Basis Function Network(RBFN)
14/02/2023	Genetic Algorithm
17/02/2023	Genetic Algorithms(Contd)
21/02/2023	Reinforcement Learning
24/02/2023	Reinforcement Learning(Contd)
28/02/2023	Confidence Intervals
03/03/2023	Comparing Learning Algorithms
07/03/2023	EM Algorithm
10/03/2023	EM Algorithm(Contd)
14/03/2023	Computational Learning Theory
17/03/2023	Student Presentations
21/03/2023	Student Presentations
24/03/2023	Student Presentations

Assignment-1

Topic	List Of Students	SubmittedFile
Activation Functions	Manasa, Harika, Sainath, Lokesh	Slides ,Code
Web Scraping	Anusha, Spandana
Partial grading of Programming Assignments	Jayanth, Jayasri
Checkers game Data preparation	Jaswanth, Harshini, Aditya
Cricket Score predictor Data preparation	SaiTeja, Ishak, Dileep