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Mastering Data Structures and Algorithms: A Practical Approach | CMPR.X419
Prepare yourself to answer the data structure and algorithm questions that often come up in Silicon Valley job interviews. In this course, students will get the extensive practice they need to master data structures and algorithms— the foundation of good software engineering. Students will use high-level languages like Python, C, C++, or Java to learn a practical approach to solving data structure and algorithm.
The course starts with a review of time and space complexity. Analysis of algorithms and basic math is involved. We review basic data structures such as arrays, strings, linked lists, stacks, queues, and priority queues, and progress to more complex tasks involving hashes, trees and graphs. Students learn through working on a relevant problem for each section that helps them understand such data structures. They review basic algorithms and problem-solving techniques: including recursion, dynamic programming, divide and conquer, sorting and searching, and some graph algorithms. Testing is emphasized as a critical part of solution building.
Students who successfully complete this course will be well-prepared to answer questions and solve problems related to data structures and algorithms in their next job interviews.
Students must program their solutions in Python, C, C++, or Java.
At the conclusion of the course, you should be able to:
- Demonstrate the ability to measure computational and space complexity: Big O notation
- Identify and utilize the most appropriate Data Structures to solve a given problem
- Design algorithms for problems involving Sorting and Searching
- Demonstrate ability to solve Recursive problems
- Identify when it is best to use Greedy algorithms, Divide and Conquer, Dynamic Programming, and Backtracking to solve a given problem
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