Mastering Algorithms and Data Structures in Go | CodeSignal Learn
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intermediate
intermediate
Mastering Algorithms and Data Structures in Go
Computer Programming
4 courses
56 practices
9 hours
This path is focused on helping you understand how to choose optimal algorithms and data structures for different problems, how to apply them, and how to understand their reasoning. Topics covered will include hash maps, recursion, and slices.
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4.32
158 learners
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Certificate of Achievement
Verified skills you'll gain
Badge for General Programming and Algorithms, Intermediate
INTERMEDIATE
General Programming and Algorithms
Badge for Computer Science Fundamentals, Developing
DEVELOPING
Computer Science Fundamentals
Tools you'll use
Go
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Course 1
Maps in Go
6 lessons
14 practices
Dive into Maps in Go with this specialized course where you will explore their implementation, practical applications, and problem-solving methodology in algorithms. Acquire hands-on experience and become proficient in addressing data analysis and management challenges.
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Course 2
Sorting and Searching Algorithms in Go
7 lessons
Course 3
Fundamental Data Structures - Stacks and Queues in Go
5 lessons
Course 4
Fundamental Data Structures - Linked Lists in Go
4 lessons
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Francisco Aguilar Meléndez
Data Scientist
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+11
20 practices
This comprehensive course is specially designed to impart a fundamental and advanced understanding of sorting and searching algorithms. The course will guide you through different types and functionalities of these algorithms, their complexity analysis, and practical application in resolving complex programming problems.
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11 practices
This advanced course delves deeper into the understanding and application of Stacks and Queues in Go. It elucidates the concept, implementation, and complexities of these data structures, with hands-on practice of solving interview-based algorithmic coding problems.
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11 practices
This foundational course provides a deep dive into the understanding and application of Linked Lists in Go. The course elucidates the inner workings, implementation, and complexities of Linked Lists, along with their versatility in solving interview-oriented algorithmic coding challenges.
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