Meeting link

 https://meet.google.com/fsm-bosa-udq

23ITS1-PYTHON WITH DJANGO

UNIT-II: Introduction to Django Framework Understanding Django environment, Features of Django and Django architecture, MVC and MTV, Urls and Views, Mapping the views to URLs, Django Template, Template inheritance Django Models, Creating model for site, Converting the model into a table, Fields in Models, Integrating Bootstrap into Django, Creating tables, Creating grids, Creating carousels. 

Sample Experiments: 

1. Create a Sample “Hello World” Application using Django 
2. Create a Login and Registration Page using MVC architecture in Django Framework 
3. Create a sample page in Django by integrating Bootstrap. 
4. Create an application with Tables, grids in Django 
5. Create a Django App with Carousels feature.

23ITS1-PYTHON WITH DJANGO

23ITS1-Complete_Syllabus

UNIT-I : Python libraries for web development : Collections-Container datatypes, Tkinter-GUI applications, Requests-HTTP requests, Beautiful Soup4-web scraping, Scrapy, Zappa, Dash, CherryPy, Turbo Gears, Flask, Web2Py, Bottle, Falcon, Cubic Web, Quixote, Pyramid. 

Experiments :  

1. Write a Python GUI program to import Tkinter package and create a window. Set its title and add a label to the window.
2. Write a Python program that designs a simple login form with labels and Entry widgets, arranging them in a grid using the Grid geometry manager.
3. Write a program using BeautifulSoup4 library for web scraping for a given URL 
4. Develop a Sample Hello World page using Flask framework 
5. Develop a sample web page using CherryPy / Web2Py / Bottle Framework  
6. Extra Experiment :    Write a Python GUI Program the change background color of window using Tkinter package 
7. Student DB Project using Flask

23AD02-ARTIFICIAL INTELLIGENCE

 23AD02-AI : Syllabus
 TextBooks:    

1. "Artificial Intelligence :  A Modern Approach" S. Russel    
2. Kevin Night and Elaine Rich, Nair B., “Artificial Intelligence (SIE)”,Mc Graw Hill

    UNIT-1  and UNIT-2  Notes   
    UNIT-1 :    PPT              Four Definitions of AI       

1. Introduction: AI problems, foundation of AI and history of AI intelligent agents: Agents and Environments, the concept of rationality, the nature of environments, structure of agents, problem solving agents, problem formulation   ppt    PPT2
2. IGNOU Problem Formulation Notes

UNIT - II:

• Searching- Searching for solutions, uniformed search strategies – Breadth first search, depth first Search. Search with partial information (Heuristic search) Hill climbing, A* ,AO* Algorithms, Problem reduction, Game Playing-Adversial search, Games, mini-max algorithm, optimal decisions in multiplayer games, Problem in Game playing, Alpha-Beta pruning, Evaluation functions.
• BFS and DFS  
• Hill Climbing             

C Programming - 2026

Text Books 

==========

•    Let us C by yaswant kantekar              

23CSS1-PYTHON PROGRAMMING

UNIT-5 :Introduction to Data Science: Functional Programming, JSON and XML in Python, NumPy with Python, Pandas.

• NumPy Material

• Pandas Material

• Matplot lib Material

• Experiments --- Programs on Numpy, Pandas, Matplot lib

Role of UML in Software Industry

•  Role of UML in Software Industry

Certifications & FDP (2026)

•  Agentic AI - FDP at ANU, Guntur Certificate

23AM01-Machine Learning

 UNIT-3: 

• Models Based on Decision Trees PPT             Notes
• Decision Trees for Classification, Impurity Measures, Properties, Regression Based on Decision Trees, Bias–Variance Trade-off, Random Forests for Classification and Regression. The Bayes Classifier: Introduction to the Bayes Classifier, Bayes’ Rule and Inference, The Bayes Classifier and its Optimality, Multi-Class Classification, Class Conditional Independence and Naive Bayes Classifier (NBC)            

 UNIT-4:

• Linear Discriminants for Machine Learning:         Notes
• Introduction to Linear Discriminants, Linear Discriminants for Classification, Perceptron Classifier, Perceptron Learning Algorithm, Support Vector Machines, Linearly Non-Separable Case, Non-linear SVM, Kernel Trick, Logistic Regression, Linear Regression, Multi-Layer Perceptron's (MLPs), Backpropagation for Training an MLP. 

 UNIT-5: 

• Fuzzy C Means

23AM01----Machine Learning

Previous Question papers:

• 8th May 2025 - 23AM01_Machine Learning

 Text Books :

1. “Machine Learning Theory and Practice”, M N Murthy,  V S Ananthanarayana, Universities Press (India), 2024.
2. Tom M. Mitchell, “Machine Learning’, MGH, 2017.

UNIT-1

• Introduction to Machine Learning

UNIT-2

• Nearest Neighbor-Based Models

CERTIFICATIONS (2025)

Global Certifications:

1. NVIDIA CERTIFATE on "Fundamentals of DEEP LEARNING"
2. Oracle Cloud Infrastructure 2025 Certified AI Foundations Associate (27th October 2025)
3. Oracle Cloud Infrastructure 2025 Certified Generative AI Professional   (28th October 2025)

NPTEL CERTIFICATION

1. NPTEL IIOT_NOV 2025
2. NPTEL IIOT_FDP_NOV_2025
3. FDP  On "Deep Learning Architectures and Applications”, by VIT AP 13th – 18th November 2025.

 Reviewer Certificates 2025

• Springer Reviewer Certificate Journal 17th Nov 2025

R & D  Publication 2025-2026Integration of MobileNetV2 for Efficient Prediction of Coffee Leaf Disease in Precision Agriculture

• Integration of MobileNetV2 for Efficient Prediction of Coffee Leaf Disease in Precision Agriculture | Springer Nature Link   9th July 2025

AWARDS- SATULURI NAGANJANEYULU

Awards Received 

• Instructor 5 Years of Service (CISCO)  13th  August 2025
• Instructor Excellence Advanced Level Award  CISCO 29th March 2021

23AD02-ARTIFICIAL INTELLIGENCE

 Text Books:

• "Artificial Intelligence :  A Modern Approach" Stuart Russel    
• Kevin Night and Elaine Rich, Nair B., “Artificial Intelligence (SIE)”, Mc Graw Hill      

 

 

 

UNIT-2 

• Informed Search        Best First Search   and A* Algorithm 
• A*  Algorithm Example                       A* History
• Problem Reduction
• Game Playing                                       
• Mini Max Algorithm

UNIT-3

• Knowledge Representation Issues
• Knowledge Representation
• Knowledge Representation Explanation 
• Semantic Nets , Inheritance 
• Constraint propagation
• KR Rules

UNIT-4

• First Order Predicate Logic (FOL) 

Research Publication of IEEE Transactions

• Optimized Attention Induced Multi Head Convolutional Neural Network for Intrusion Detection Systems in Vehicular Ad Hoc Networks (IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS)  with impact factor 7.9  DOI: 10.1109/TITS.2025.3561545        Web of science journal information

Research Publications

 Academic Year : 2024-2025

• Rat swarm political optimizer based deep learning approach for lung lobesegmentation and lung cancer detection using CT images      (ELSEVIER-Impact factor : 4.9)

• An optimised CNN-stacked LSTM neural network model for predicting stock market time-series data     ( Inderscience -March 2025 - Impact Factor : 0.8 )    Published Online:March 17, 2025   pp 196-224  https://doi.org/10.1504/IJCEE.2025.145022

 Academic Year : 2023-2024

• Enhancing stock market forecasting using sequential training network empowered by tunicate swarm optimization

• Stock Market Investment Strategy UsingDeep-Q-Learning Network  
• “Stock Market Investment Strategy Using Deep-Q-Learning Network” Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligencand Lecture Notes in Bioinformatics) 2023, 14078 LNAI, pp. 484–495  (First Online: 24 June 2023)  https://doi.org/10.1007/978-3-031-36402-0_45

   

  
  
•  

FDP ATTENDED  : 2024-2025

• DATA SCIENCE USING PYTHON

20CS17-INFORMATION SECURITY

 20CS17-INFORMATION SECURITY

• Text Books
• Networks Security Essential by Willam Stallings
• 
  
• Unit-1 PPT
• Unit-2 PPT

 

 

23CS03-DATABASE MANAGEMENT SYSTEMS

• SYLLABUS
• ALL UNITS PPT
• How to find the highest Normal Form

 

Object Oriented Programming Through JAVA(23CS05)

20CS10-DMDW Previous Papers

 Previous Question Papers

• 20CS10_DWDM_QUESTION PAPER (13th Dec 2023)
• 20CS10_DWDM_QUESTION PAPER (26th June 2023)     Key June 2023(pdf)
• 20CS10_DWDM_QP(24th Jan 2023)
• 20CS10_DWDM_QP(7th July 2022)            

Mid Papers (Sample)

• OBJECTIVE QUESTIONS FOR UNIT-1 AND UNIT2
  
•  
• MID-1  DESCRIPTIVE  2022-2023                          
• MID-1  OBJECTIVE      2022-2023 
•  

20CS10-DATA WAREHOUSING AND DATA MINING

Text Books:

• Data Mining Concepts and Techniques
• Introduction to Data Mining : Pang-Ning Tan & Michael Steinbach, Vipin Kumar, Fifth Impression, Pearson, 2015.

UNIT-1

• DATA WAREHOUSING  (NOTES)
• DESCRIPTIVE QUESTIONS
• OBJECTIVE QUESTIONS
• ASSIGNMENT QUESTIONS

UNIT-2

• Motivational Challenges
• Types of Data
• Data Quality
• Data Preprocessing
• Similarity and Dissimilarities Measures

UNIT-3

• Decision Tree 

WIPRO CERFICATES

• Dr S Naganjaneyulu Cloud Computing (16th Oct 2023 to 20th Oct 2023)
  
• Dr S.Naganjaneyulu Big Data Certificate (30th Jan 2023 to 03th Feb 2023)