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Berkeley Global
Get an overview and hands-on experience with some of the more popular data structures and algorithms used in industry today. The course focus includes arrays, linked lists, stacks, queues, hash tables, trees, heaps, graphs, and their associated algorithms (e.g., searching, sorting, traversal, shortest path, compression, etc.). You will also learn measuring complexity, recursion, dynamic programming, and data representation. You will examine these concepts in the context of various real-world situations. Course demonstrations are in Python, students can submit assignments in Python, Java, C/C++.
Prerequisites:
- Basic programming knowledge (Java, Python, C++)
- Knowledge of mathematical foundations (basic algebra, logic, probability)
Learner Outcomes
Upon completion of this course, students will be able to:
- 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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Sections
Spring 2025 enrollment opens on October 21!