Semester-Notes

• This repository includes academic notes, study materials, and resources from B.Tech (Hons) in CSE, specializing in Artificial Intelligence and Data Science.
  
  
• It features question papers, proprietary study guides, and resources to support learning in these fields.
  
  
• This repository serves as a valuable resource to access well-structured and reliable study materials.
  
  
• Study Materials are organized according to semesters and subjects.

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Table Of Contents 📔 🔖 📑

1 Semester

Data Science and Artificial Intelligence Subjects:

1. Engineering Mathematics I
   
   
2. Environmental Science
   
   
3. Foundations of Electronics Engineering
   
   
4. Fundamentals of Computational Biology
   
   
5. Language and Writing Skills
   
   
6. Learning Programming Concepts With C

• To see lab programs, visit: Learning Programming Concepts With C Lab
  

7. Professional Ethics and Life Skills

2 Semester

Data Science and Artificial Intelligence Subjects:

1. Data Structure Using C

• To see lab programs, visit: Data Structure Using C Lab
  

2. Digital Logic and Design
   
   
3. Engineering Mathematics II
   
   
4. Entrepreneurship
   
   
5. Object-Oriented Programming

• To see lab programs, visit: Object-Oriented Programming with C++ Lab
  

6. Python for Data Science

• To see lab programs, visit: Python for Data Science Lab

3 Semester

Data Science and Artificial Intelligence Subjects:

1. Analysis and Design of Algorithm

• To see lab programs, visit: Analysis and Design of Algorithm using Python Lab
  

2. Computer Organization and Architecture
   
   
3. Database Management System
   
   
4. Discrete Structure
   
   
5. Independent Project

• To see the project, visit: Library Management System
  

6. Probability and Statistics

4 Semester

Data Science and Artificial Intelligence Subjects:

1. Artificial Intelligence Principles and Applications
   
   
2. Computer Network
   
   
3. Data Visualization

• To see lab programs, visit: Data Visualization using Python Lab
  

4. Operating System
   
   
5. R for Data Science

• To see lab programs, visit: R for Data Science Lab
  

6. Theory of Computation

5 Semester

Data Science Subjects:

1. Computational Complexity
   
   
2. Cryptography and Network Security

• To see lab programs, visit: Cryptography and Network Security Lab
  

3. Intelligent Data Analysis

• To see lab programs, visit: Intelligent Data Analysis Lab
  

4. Natural Language Processing

• To see lab programs, visit: Natural Language Processing in Python Lab
  

5. Pattern Recognition and Machine Learning

• To see lab programs, visit: Pattern Recognition and Machine Learning Lab
  

6. Vocational Training

• To see the lab project, visit: Vocational Training Project
  

7. Minor Project

• To see the lab project, visit: Stock Market Prediction app.

Artificial Intelligence Subjects:

1. Artificial Neural Networks
   
   
2. Predictive Modelling and Analytics

6 Semester

• Presentation:
  • Update_Presentation.pptx: Presentation for the first two months.
  • Final_Presentation.pptx: Final presentation of the project.
• Internship Report:
  • Final_Report.pdf: Detailed report of the project work, methodologies, results, and conclusions.

7 Semester

Data Science Subjects:

1. Algorithmic Gaming Theory
   
   
2. Big Data Analytics

• To see lab programs, visit: Big Data Analytics Lab
  

3. Data Wrangling

• To see lab programs, visit: Data Wrangling Lab
  

4. Image Processing
   
   
5. Management Information System
   
   
6. Software Engineering

• To see lab programs, visit: Software Engineering Lab
  

7. Minor Project

• To see the lab project, visit: Stock Market Prediction App.

Artificial Intelligence Subjects:

1. Business Intelligence and Analytics
   
   
2. Intelligent System and Robotics

Syllabus

This section contains the syllabus for each semester:

• Click here to view the syllabus
• Detailed course outlines, including topics and subtopics.
• List of recommended textbooks and reference materials.
• Suggested reading materials to complement the coursework.
• Key topics and learning objectives for each subject.

Question Papers

This section contains the question papers for each semester:

• Click here to view the Question Papers
• Organized by semester for easy navigation.
• Includes Class Test 1, Class Test 2, and Annual Exams.
• Contains Re-Class Tests, if applicable.
• Each semester folder provides a comprehensive collection of exam papers.

Docs

This folder contains the code for this website:

• The index.html file serves as the main page.
• The website is user-friendly, featuring an intuitive interface that is easy to navigate.
• Responsive design ensures the website looks great and functions well on all devices and screen sizes.
• A dropdown menu allows dynamic color changes with options for Autumn, Summer, Rainy, and Winter. Upon selection, the website color changes instantly. Refreshing the page restores the default color scheme.

Data Science and Artificial Intelligence Subjects

During the 1st to 4th semesters, both branches followed a common curriculum, ensuring a foundational understanding of core subjects.

From the 5th to 7th semesters, the curriculum began to diversify:

• 5th and 7th semesters: Two subjects were tailored to individual tracks, reflecting specialized interests. I have detailed these differences above, along with separate question papers and syllabi for both branches (AI and DS).
• 6th semester: Focused entirely on an internship, where students selected their projects, institutions, and domains independently.

Directory Structure 🗃️

Semester-Notes/
├── 1 SEMESTER/               # 📁 Folder for the first semester
│
├── 2 SEMESTER/               # 📁 Folder for the second semester
│
├── 3 SEMESTER/               # 📁 Folder for the third semester
│
├── 4 SEMESTER/               # 📁 Folder for the fourth semester
│
├── 5 SEMESTER/               # 📁 Folder for the fifth semester
│   ├── AI Subjects/          # 📁 AI Subjects folder inside 5th semester
│
├── 6 SEMESTER/               # 📁 Folder for the sixth semester
│
├── 7 SEMESTER/               # 📁 Folder for the seventh semester
│   ├── AI Subjects/          # 📁 AI Subjects folder inside 7th semester
│
├── SYLLABUS/                 # 📚 Folder containing the syllabus for all semesters
│
└── QUESTION PAPERS/          # 📝 Folder containing the question papers for all semesters
│
├── docs/                     # 🗂️ Folder containing website code
│   ├── index.html            # 🏠 Main landing page of the website
│   ├── Astyle-Commands.html  # ⚙️ Page dedicated to Astyle formatter commands
│   ├── Git-Commands.html     # 🛠️ Page dedicated to Git commands
│   ├── Hadoop-Commands.html  # 📊 Page dedicated to Hadoop commands
│   │
│   ├── css/
│   │   ├── index.css         # 🎨 Stylesheet for index.html
│   │   └── commands.css      # 🎨 Stylesheet for Astyle-Commands.html and Git-Commands.html and Hadoop-Commands.html
│   │
│   ├── js/
│   │   ├── index.js          # 🖥️ Script to dynamically change the primary color of the website
│   │   └── commands.js       # 📜 Script to manage the visibility of the color and copying of commands in Astyle-Commands.html and Git-Commands.html and Hadoop-|                                    Commands.html
│
├── LICENSE                   # 📜 MIT License file
│
└── README.md                 # 📄 Documentation file for the repository
│
└── CONTRIBUTING.md           # 🤝 Guide for contributing to the repository

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Website Design

This website showcases a comprehensive repository of semester notes and study resources. It features a dynamic, color-changing dropdown menu using JavaScript. The content is organized into detailed sections, covering semester-wise subjects and commonly used commands for Astyle, Git and Hadoop. Visit the website at: Website Link.

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