https://github.com/syuvraj19/dsa-assignments
This repository contains Data Structures & Algorithm assignments from Seneca College's DSA456 course.
https://github.com/syuvraj19/dsa-assignments
dsa dsa-algorithm dsa-practice
Last synced: 5 months ago
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This repository contains Data Structures & Algorithm assignments from Seneca College's DSA456 course.
- Host: GitHub
- URL: https://github.com/syuvraj19/dsa-assignments
- Owner: syuvraj19
- Created: 2024-07-21T15:02:48.000Z (11 months ago)
- Default Branch: main
- Last Pushed: 2024-07-22T16:05:23.000Z (11 months ago)
- Last Synced: 2024-11-17T09:42:55.528Z (7 months ago)
- Topics: dsa, dsa-algorithm, dsa-practice
- Language: Python
- Homepage:
- Size: 1.79 MB
- Stars: 1
- Watchers: 1
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Data Structures and Algorithms (DSA456)
Welcome to the repository for **Data Structures and Algorithms (DSA456)** at Seneca College!
The GitHub repository DSA-Assignments contains assignments for the Data Structures and Algorithms (DSA456) course at Seneca College. The repository is organized into two main sections: lab_assignments (Lab Assignments 0-7) and final_assignments (Final Assignments 1-3). These assignments cover practical implementations and theoretical concepts, including algorithm analysis, growth rates, custom data structures, P vs NP problems, efficient data retrieval, and graph data structures. The repository includes documentation and is primarily written in Python.
## 📚 Course Overview
**Course Title:** Data Structures and Algorithms
**Course Description:**
Explore the core components of efficient programming with this in-depth look at classical data structures and algorithms. This course covers the implementation and theoretical basis of these building blocks, providing a strong foundation in computational theory and programming efficiency.
## 🎯 Learning Outcomes
Upon successful completion of this course, you will be able to:
- **Analyze Algorithms and Data Structures:** Design optimal programs by evaluating their resource usage.
- **Understand Growth Rates:** Forecast performance by explaining the relationship between resource use and growth rates.
- **Implement and Explain:** Use pseudo code and diagrams to illustrate the implementation of data structures and algorithms.
- **Create Custom Data Structures:** Extend language-specific libraries with your own custom implementations.
- **P vs NP Problem:** Explain this fundamental problem to understand computational limitations.
- **Efficient Data Retrieval:** Implement key-based container classes for fast and efficient data access.
- **Graph Data Structures:** Utilize graph structures to manage relationships between objects effectively.
## 🛠️ Projects and Assignments
### Lab Assignments
- **Lab Assignment 0-7:** Practical labs to apply and reinforce your understanding of course concepts.
### Final Assignments
- **Final Assignment 1-3:** Comprehensive projects to showcase your ability to implement and innovate using data structures and algorithms.
## 📁 Repository Structure
- `lab_assignments/`: Contains files for Lab Assignments 0-7.
- `final_assignments/`: Contains files for Final Assignments 1-3.
- `docs/`: Documentation and notes related to the course material.
## 📬 Contact
For any questions or feedback, please contact at [my mail](mailto:[email protected]).