This repository is a comprehensive collection of notes, prepared by Shreyas Kashyap, a BTech (Computer Science & Engineering) student with a Minor in Artificial Intelligence and Machine Learning at Lovely Professional University (LPU). It includes course materials, lab exercises, assignments, and project documentation, systematically organized for easy navigation and in-depth study.
This repository is meticulously organized semester-wise, with each course categorized to enhance your learning experience:
- Core Courses: Fundamental subjects essential to the field of Computer Science and Engineering, including specialized courses in AI/ML.
- Electives: Diverse topics such as Cloud Computing, Web Development, Cyber Security, and more.
- Soft Skills & Communication: Resources aimed at enhancing communication, teamwork, and analytical skills.
- Aptitude and Logical Reasoning: Materials crucial for competitive exams and placement preparations.
- Projects: Documentation and code for capstone projects and other practical assignments.
- Welcome Note
- About the Repository
- Table of Contents
- Course Overview
- Semester Breakdown
- SwiftSolve: An Interactive Question Solving Platform
- Core Courses
- Specialization Courses
- Capstone Projects
- Getting Started
- Progress Tracker
This repository encompasses notes and resources from various courses that constitute the BTech (CSE) program, including:
- Core Computer Science Courses: Fundamental courses covering programming, data structures, algorithms, computer architecture, operating systems, and networks.
- AI/ML Minor Courses: Advanced topics in Artificial Intelligence, Machine Learning, Deep Learning, Natural Language Processing, and Computer Vision.
- Electives: Subjects offering insights into Cloud Computing, Cyber Security, Data Science, Full Stack Development, and more.
- Soft Skills & Communication: Courses designed to improve verbal ability, analytical skills, and professional communication.
- Aptitude and Logical Reasoning: Essential materials for aptitude tests, logical reasoning, and quantitative analysis, aiding in competitive exams and placements.
- Projects: Detailed documentation and code repositories for capstone projects, internships, and other practical engagements.
|---|---|---|---| |Core Courses 🖥️|Minor in AI/ML 🤖|Electives 🔧|Projects 💼| ||||
# BTech (CSE) - AI/ML Minor
├── Semester 1
│ ├── CSE111 - Orientation to Computing-I
│ ├── CSE326 - Internet Programming Laboratory
│ ├── INT108 - Python Programming
│ ├── MEC135 - Basics of Mechanical Engineering
│ ├── MTH174 - Engineering Mathematics
│ ├── PES318 - Soft Skills-I
│ └── PHY110 - Engineering Physics
├── Semester 2
│ ├── CHE110 - Environmental Studies
│ ├── CSE101 - Computer Programming
│ ├── CSE121 - Orientation to Computing-II
│ ├── CSE320 - Software Engineering
│ ├── ECE249 - Basic Electrical and Electronics Engineering
│ ├── ECE279 - Basic Electrical and Electronics Laboratory
│ ├── INT306 - Database Management Systems
│ ├── MTH401 - Discrete Mathematics
│ └── PEL130 - Advanced Communication Skills-I
├── Semester 3
│ ├── CSE202 - Object Oriented Programming
│ ├── CSE205 - Data Structures and Algorithms
│ ├── CSE211 - Computer Organization and Design
│ ├── CSE306 - Computer Networks
│ ├── CSE307 - Internetworking Essentials
│ ├── CSE316 - Operating Systems
│ ├── CSE325 - Operating Systems Laboratory
│ ├── GEN231 - Community Development Project
│ └── PEL136 - Advanced Communication Skills-II
├── Semester 4
│ ├── CSE310 - Programming in Java
│ ├── CSE408 - Design and Analysis of Algorithms
│ ├── INT254 - Fundamentals of Machine Learning
│ ├── INT354 - Machine Learning-I
│ ├── INT404 - Artificial Intelligence
│ └── PEA307 - Advanced Analytical Skills-I
├── Semester 5
│ ├── ACC304 - Cost Accounting (Open Minor)
│ ├── CSE322 - Formal Languages and Automata Theory
│ ├── INT344 - Natural Language Processing
│ ├── INT423 - Machine Learning-II
│ ├── PEA308 - Advanced Analytical Skills-II
│ ├── PEV113 - Verbal Ability
│ └── CSE443 - Seminar on Summer Training
├── Semester 6
│ ├── CSE332 - Industry Ethics and Legal Issues
│ ├── CSE393 - Online Academic Course
│ ├── INT345 - Computer Vision
│ ├── INT221 - MVC Programming
│ ├── INT312 - Big Data Fundamentals
│ └── PEV114 - Advanced Verbal Ability
├── Semester 7
│ ├── (Option A: Industrial Internship)
│ │ └── CSE447 - Industry Co-op Project-I
│ └── (Option B: Coursework)
│ ├── CSE406 - Advanced Java Programming
│ ├── INT422 - Deep Learning
│ ├── CSE339 - Capstone Project-I
│ └── Open Minor Elective
└── Semester 8
├── (Option A: Industrial Internship)
│ └── CSE448 - Industry Co-op Project-II
└── (Option B: Coursework)
├── CSE403 - Network Security and Cryptography
├── CSE439 - Capstone Project-II
├── CSE435 - Comprehensive Seminar
└── Open Minor Elective
- CSE111 - Orientation to Computing-I: Introduction to computing concepts, basic programming constructs, and problem-solving techniques.
- CSE326 - Internet Programming Laboratory: Practical exposure to web technologies, HTML, CSS, and introductory JavaScript.
- INT108() - Python Programming: Fundamentals of Python programming, data types, control structures, functions, and modules.
- MEC135() - Basics of Mechanical Engineering: Overview of mechanical engineering principles, thermodynamics, and material science.
- MTH174() - Engineering Mathematics: Mathematical concepts including calculus, linear algebra, and differential equations.
- PES318() - Soft Skills-I: Development of communication skills, presentation techniques, and teamwork.
- PHY110() - Engineering Physics: Fundamental physics concepts relevant to engineering applications.
- CHE110() - Environmental Studies: Understanding environmental issues, sustainable development, and ecological balance.
- CSE101() - Computer Programming: In-depth study of programming concepts using languages like C/C++.
- CSE121() - Orientation to Computing-II: Advanced computing concepts, introduction to data structures.
- CSE320() - Software Engineering: Principles of software development, software life cycle models, and project management.
- ECE249() - Basic Electrical and Electronics Engineering: Fundamentals of electrical circuits, electronic devices, and applications.
- ECE279() - Basic Electrical and Electronics Laboratory: Hands-on experiments with electrical circuits and electronic components.
- INT306() - Database Management Systems: Concepts of databases, SQL, normalization, and transaction management.
- MTH401() - Discrete Mathematics: Logic, set theory, combinatorics, graph theory, and algorithms.
- PEL130() - Advanced Communication Skills-I: Enhancement of verbal communication, listening skills, and language proficiency.
- CSE202() - Object Oriented Programming: Concepts of OOP using languages like Java or C++, including classes, objects, inheritance, and polymorphism.
- CSE205() - Data Structures and Algorithms: Study of data structures like arrays, linked lists, trees, graphs, and algorithm design.
- CSE211() - Computer Organization and Design: Computer architecture, memory hierarchy, instruction sets, and CPU design.
- CSE306() - Computer Networks: OSI model, network protocols, routing, and network security basics.
- CSE307 - Internetworking Essentials: Networking technologies, TCP/IP stack, and practical networking skills.
- CSE316 - Operating Systems: Concepts of operating systems, process management, memory management, and file systems.
- CSE325 - Operating Systems Laboratory: Practical implementation of OS concepts, shell scripting, and system programming.
- GEN231 - Community Development Project: Participation in community service projects to develop social responsibility.
- PEL136 - Advanced Communication Skills-II: Further development of communication skills, focusing on professional contexts.
- CSE310 - Programming in Java: Advanced Java programming concepts, GUI development, and network programming.
- CSE408 - Design and Analysis of Algorithms: Algorithm complexity, advanced sorting, graph algorithms, and optimization techniques.
- INT254 - Fundamentals of Machine Learning: Introduction to machine learning concepts, supervised and unsupervised learning.
- INT354 - Machine Learning-I: In-depth study of machine learning algorithms, model evaluation, and implementation.
- INT404 - Artificial Intelligence: AI principles, problem-solving, knowledge representation, and reasoning.
- PEA307 - Advanced Analytical Skills-I: Development of analytical and quantitative skills, critical for problem-solving.
- ACC304 - Cost Accounting: Principles of cost accounting, budgeting, and financial management.
- CSE322 - Formal Languages and Automata Theory: Study of automata, formal languages, grammars, and computational theory.
- INT344 - Natural Language Processing: Techniques for processing natural language data, text analytics, and language models.
- INT423 - Machine Learning-II: Advanced machine learning topics, including deep learning and neural networks.
- PEA308 - Advanced Analytical Skills-II: Enhancement of analytical abilities with complex problem-solving techniques.
- PEV113 - Verbal Ability: Focused training on verbal reasoning, comprehension, and communication skills.
- CSE443 - Seminar on Summer Training: Presentation and discussion of experiences and learnings from summer internships.
- CSE332 - Industry Ethics and Legal Issues: Understanding professional ethics, legal considerations in technology.
- CSE393 - Online Academic Course: Elective course completed through an approved online platform.
- INT345 - Computer Vision: Study of image processing, feature extraction, and computer vision algorithms.
- INT221 - MVC Programming: Model-View-Controller architecture, web application development frameworks.
- INT312 - Big Data Fundamentals: Concepts of big data analytics, Hadoop, Spark, and data processing techniques.
- PEV114 - Advanced Verbal Ability: Advanced training in verbal communication, critical for interviews and professional settings.
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CSE447 - Industry Co-op Project-I: Full-term industrial internship providing practical industry experience.
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Coursework Option:
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CSE406 - Advanced Java Programming: In-depth Java topics, enterprise applications, and frameworks like Spring.
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INT422 - Deep Learning: Neural networks, convolutional networks, recurrent networks, and deep learning applications.
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CSE339 - Capstone Project-I: Beginning of the major project, involving planning and initial development.
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Open Minor Elective: Elective course from an open minor to broaden knowledge.
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CSE448 - Industry Co-op Project-II: Continuation of the industrial internship, culminating the industry experience.
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Coursework Option:
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CSE403 - Network Security and Cryptography: Study of security principles, cryptographic algorithms, and network security protocols.
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CSE439 - Capstone Project-II: Completion of the capstone project, finalizing development and presenting results.
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CSE435 - Comprehensive Seminar: Presentation and defense of the capstone project work.
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Open Minor Elective: Additional elective to complement the degree.
SwiftSolve is an interactive web-based platform designed to enhance your problem-solving skills through a structured approach to answering questions. Here's what it offers:
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Question Repository: Users can upload questions categorized by subject and difficulty level. This creates a vast pool of questions that anyone can use to practice.
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Randomized Question Order: Each test presents questions in a random order, ensuring a unique experience each time and minimizing memorization.
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Timed Tests: Each question comes with a time limit, promoting efficient problem-solving and time management skills. The entire test must also be completed within a specified duration.
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Difficulty Levels: Questions are sorted by difficulty, allowing users to choose tests that match their current skill level, making it easier to progress and improve.
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User-Friendly Interface: SwiftSolve provides an intuitive user interface to navigate the question repository, upload new questions, and take tests seamlessly.
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Improve Problem-Solving Skills: Regular practice with a variety of questions helps in enhancing critical thinking and analytical skills, which are crucial for success in technical fields.
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Prepare for Competitive Exams: By simulating real test conditions with timed questions, you can prepare effectively for competitive exams and assessments.
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Collaborative Learning: By allowing users to upload and share questions, SwiftSolve fosters a collaborative environment for students to learn from each other.
- Visit SwiftSolve to start practicing your problem-solving skills.
This section encompasses all the core courses and specializations, including the minor in Artificial Intelligence and Machine Learning, which are critical for the CSE program:
- Programming Fundamentals: CSE101, INT108, CSE202, CSE310
- Data Structures and Algorithms: CSE205, CSE408
- Computer Architecture: CSE211
- Operating Systems: CSE316, CSE325
- Database Systems: INT306
- Computer Networks: CSE306, CSE307
- Software Engineering: CSE320
- Artificial Intelligence and Machine Learning: INT254, INT354, INT404, INT423, INT344, INT345, INT422
- Theory of Computation: CSE322
- Electives in Emerging Areas: INT221, INT312, INT345, CSE403, INT221, INT422
The capstone projects are significant components of the curriculum, allowing students to apply their knowledge to real-world problems:
- Capstone Project-I (CSE339): Initial phase involving project proposal, literature review, and preliminary development.
- Capstone Project-II (CSE439): Final phase focusing on implementation, testing, documentation, and presentation.
To get started with this repository:
Clone the Repository:
git clone https://github.com/ShreyasKashyap357/LPU-BTech-CSE-Notes.git
Navigate the Notes: Browse the folder structure semester-wise.
Prerequisites: For using some of the materials (e.g., lab work in Python or Java), ensure you have a programming environment set up (like Jupyter notebooks, IDEs for Java, etc.).
- Navigate by Semester: Each semester folder contains subfolders for each course, including lecture notes, lab assignments, tutorials, and past exam papers.
- Course Materials: Within each course folder, materials are organized into lectures, labs, assignments, and additional resources.
- Projects and Assignments: Access project documentation and source code in the 'Projects' directory for hands-on learning.
- Search Functionality: Use the repository's search feature to find specific topics or keywords.
- Contributions: Check the 'Contributing' section to understand how to add your notes or improvements.
The LPU BTech (CSE) Notes Repository is a curated collection of notes, assignments, lab work, and project documentation aimed at helping BTech students in their studies, particularly in the Computer Science and Engineering program with a Minor in Artificial Intelligence and Machine Learning.
Any student or faculty member can contribute to the repository. If you have notes, resources, or projects you would like to share, please submit them using the contribution form.
You can access the notes by browsing the repository's folder structure, which is organized by semester and subject.
The repository includes notes for core courses, AI/ML minor courses, electives, and soft skills, as well as resources for aptitude and logical reasoning.
You can reach out through the provided contact information in the README file, or use the issue tracker on GitHub to ask your questions.
SwiftSolve is an interactive web platform that allows students to upload, practice, and solve questions in a timed environment. It offers a repository of questions sorted by difficulty and enables users to take tests based on their skill level.
To use SwiftSolve, simply visit the website, create an account, and start uploading questions or practicing existing ones. You can take timed tests to improve your problem-solving skills.
Yes! Users have the option to create custom question sets based on topics or difficulty levels for personalized practice.
Each question has a specified time limit, and users must complete all questions within the total duration set for the test. This simulates real exam conditions and helps improve time management skills.
Currently, SwiftSolve is web-based, but we are considering developing a mobile app in the future for better accessibility.
SwiftSolve provides a user dashboard that tracks your performance, including the number of questions solved, accuracy rates, and progress over time.
If you encounter any technical issues, please report them through the issue tracker on the SwiftSolve repository or contact support for assistance.
No, SwiftSolve is completely free for all users. We aim to provide accessible resources for all students.
Yes! We occasionally host coding challenges, and you can track your progress on the leaderboard. Check the repository for upcoming challenges.
We welcome user feedback and suggestions! You can submit your ideas through the issue tracker on the SwiftSolve GitHub repository.
Yes! We encourage users to join our community forums on Discord/Slack, where you can collaborate, ask questions, and participate in discussions.
The notes repository is regularly updated with new content as courses evolve. Make sure to check back frequently for the latest materials.
Absolutely! The notes are designed to help you prepare for exams and improve your understanding of the subjects.
If you have additional questions or suggestions for the FAQs, feel free to reach out through the contact information provided or create an issue in the repository.
Please report any errors or inaccuracies you find by opening an issue in the repository, so we can make the necessary corrections.
Contributions are highly encouraged! If you have additional notes or improvements, here’s how you can contribute:
- Fork the Repository: Create a personal copy of the repository. Click the fork button at the top of the repository page.
- Create a New Branch: Use a descriptive branch name (e.g., add-cse205-notes).
git checkout -b add-new-course-notes
- Make Your Changes: Add your notes, fix errors, or update the structure.
- Commit Your Changes:
git commit -m "Added notes for CSE205"
- Submit a Pull Request: Explain the changes and why they improve the repository and why the pull request must be merged.
- Review Process: Your contribution will be reviewed, and feedback may be provided.
To see who made changes to specific lines of code in this project, you can use the git blame command. This command will show you the last commit that modified each line of a file, along with the author's information.
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Open your terminal.
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Navigate to the repository directory.
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Run the following command:
git blame path/to/your/file.txt
- Summary ` In summary, "blame" in a README refers to the Git command that helps users track changes in files, providing valuable insights into the project's history. It can be a helpful tool for contributors to understand the context of changes and collaborate more effectively.
This repository is licensed under the GNU GPLv3.0 License. You are free to use, modify, and distribute the materials with proper attribution.
For any queries or suggestions, feel free to reach out: