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Berkeley Global
This course gives students an overview and hands-on experience with some of the more popular data structures and algorithms used in the industry today. We will focus on arrays, linked lists, stacks, queues, hash tables, trees, heaps, graphs, and their associated algorithms (e.g., searching, sorting, traversal, shortest path, compression, etc.). We will also cover measuring complexity, recursion, dynamic programming, and data representation. We will examine these concepts in the context of various real-world situations. This course is offered in Java, Python, or C++. Prior knowledge or experience in some programming language is required.
Learner Outcomes
- Analyze the complexity of algorithms using Big O notation.
- Implement basic data structures such as arrays and linked lists to build more complex data structures.
- Work with queues and stacks, which are used in computer architecture, web servers, printers, music playlists and more.
- Understand the difference between recursion and iteration to solve problems.
- Distinguish the strengths and weaknesses of popular sorting algorithms.
- Use hash tables, which are used in relations databases, to perform optimized lookup.
- Work with the tree data structure, which is the foundation of hierarchical data storage, such as file systems, organizational structures, and Internet data.
- Implement an autocomplete using the tries data structure.
- Understand how graphs and Djikstra's algorithm can be used for finding the shortest path as in a navigation system.
- Optimize existing programs with dynamic programming and memoization techniques.
- Implement Huffman compression for efficient data storage and transmission.
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Summer enrollment opens on March 20!