https://github.com/nadidlinchestein/cs201-elementarydatastructures
https://github.com/nadidlinchestein/cs201-elementarydatastructures
Last synced: 7 months ago
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- Host: GitHub
- URL: https://github.com/nadidlinchestein/cs201-elementarydatastructures
- Owner: NadidLinchestein
- License: mit
- Created: 2025-01-23T10:56:02.000Z (9 months ago)
- Default Branch: main
- Last Pushed: 2025-01-23T12:00:05.000Z (9 months ago)
- Last Synced: 2025-01-23T12:18:39.373Z (9 months ago)
- Size: 5.86 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# CS201 - Elementary Data Structures
This course offers an in-depth exploration of **Data Structures** and their associated **Algorithms**, focusing on both theoretical constructs and real-world implementation in **C++**. Designed for aspiring software developers and computer scientists, the curriculum emphasizes the efficient storage, manipulation, and retrieval of data to solve computational problems.
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## Course Content Overview
### 1. Abstract Data Types (ADTs)
- Delve into the concept of **Abstract Data Types**, which define operations independently of their implementation.
- Differentiate between **ADTs** and **Data Structures**, highlighting their interplay in software engineering.
### 2. Arrays
- Master arrays as a linear, contiguous **Data Structure**.
- Implement multi-dimensional arrays and learn efficient memory management techniques in **C++**.
### 3. Stacks and Queues
- Understand **Last-In-First-Out (LIFO)** and **First-In-First-Out (FIFO)** principles.
- Implement stacks and queues using **static arrays**, **dynamic arrays**, and **circular arrays**.
- Analyze their operational complexities and trade-offs in system-level programming.
### 4. Pointers and References in C++
- Cultivate a deep understanding of **memory addressing** and **pointer arithmetic**.
- Master the utilization of **references** and **dereferencing** for robust and flexible programming.
- Explore the application of pointers in **dynamic memory management** and **interfacing with hardware**.
### 5. Dynamic Memory Allocation
- Explore runtime memory allocation using **malloc**, **calloc**, and **new** operators in C++.
- Address challenges such as **fragmentation**, **memory leaks**, and **dangling pointers**, and implement strategies for their mitigation.
- Understand the importance of **RAII (Resource Acquisition Is Initialization)** for efficient resource management.
### 6. Linked Data Structures
- Implement **Linked Lists**, **Linked Stacks**, and **Linked Queues** using **node-based architectures**.
- Explore **singly linked lists**, **doubly linked lists**, and **circular linked lists** for flexible memory usage.
- Harness non-contiguous memory allocation to dynamically manage datasets of varying sizes.
### 7. Algorithm Efficiency
- Evaluate algorithms using **asymptotic notations** such as **Big O**, **Big Theta (Θ)**, and **Big Omega (Ω)**.
- Conduct **time complexity** and **space complexity** analysis to optimize performance.
- Explore **amortized analysis** for understanding average-case behavior in dynamic systems.
### 8. Searching and Sorting Algorithms
- Implement fundamental algorithms such as:
- **Linear Search** and **Binary Search** for efficient data retrieval.
- **Bubble Sort**, **Quick Sort**, **Merge Sort**, and **Heap Sort** for data organization.
- Conduct **best-case**, **worst-case**, and **average-case** performance analysis for these algorithms.
### 9. Advanced Data Structures: Hash Tables, Graphs, and Trees
- Design **Hash Tables** with **open addressing** and **chaining** for collision resolution.
- Explore **Graphs**, including **directed**, **undirected**, and **weighted graphs**, and their representations using **adjacency matrices** and **adjacency lists**.
- Master **Trees** and specialized variants such as **Binary Trees**, **Binary Search Trees (BSTs)**, and **Balanced Trees** like **AVL** and **Red-Black Trees**.
- Learn advanced traversal algorithms like **Depth-First Search (DFS)** and **Breadth-First Search (BFS)**.
---
## Key Learning Outcomes
By completing this course, you will:
- Gain proficiency in implementing and manipulating complex **Data Structures** in **C++**.
- Develop an analytical approach to evaluating **algorithmic efficiency** using rigorous mathematical techniques.
- Master **memory management** and mitigate risks such as fragmentation and resource mismanagement.
- Build a strong foundation for advanced topics such as **graph theory**, **dynamic programming**, and **database indexing**.
---
## Assessment and Certification
- To earn the **CS201 Course Completion Certificate**, you must score **70% or higher** on the **Final Exam**.
- The certificate validates your proficiency in foundational **Data Structures and Algorithms**, a critical skillset for advanced computing roles.
---
This course is a rigorous journey into the realm of computational theory and practical engineering, equipping you with the technical acumen required for tackling real-world software development challenges.
---
## Authors
Passionate about creating impactful educational content for aspiring developers. [@NadidLinchestein](https://github.com/NadidLinchestein)
## License
This project is licensed under the [MIT License](https://choosealicense.com/licenses/mit/), granting you the freedom to use, modify, and distribute this content with proper attribution.