Semester-Notes

• This repository contains a vast collection of academic notes, study materials, and resources from various semesters of Datascience course.
  
  
• This repository serves as a valuable resource to access well-structured and reliable study materials.
  
  
• Study Materials are organized according to semesters and subjects.

---

Table Of Contents 📔 🔖 📑

1 Semester

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
  

7. Professional Ethics and Life Skills

2 Semester

1. Data Structure Using C

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

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++
  

6. Python for Data Science

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

3 Semester

1. Analysis and Design of Algorithm

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

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

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

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

4. Operating System
   
   
5. R for Data Science

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

6. Theory of Computation

5 Semester

1. Computational Complexity
   
   
2. Cryptography and Network Security

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

3. Intelligent Data Analysis

• To see lab programs, visit: Intelligent Data Analysis
  

4. Natural Language Processing

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

5. Pattern Recognition and Machine Learning

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

6. Vocational Training

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

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.

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 portfolio 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.

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
│
├── 6 SEMESTER/               # 📁 Folder for the sixth 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

---

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.

---

Thanks for Visiting 😄

• Drop a 🌟 if you find this repository useful.
  
  
• If you have any doubts or suggestions, feel free to reach me.
  
  📫 How to reach me:      
  
  
• Contribute and Discuss: Feel free to open issues 🐛, submit pull requests 🛠️, or start discussions 💬 to help improve this repository!