Algorithms Data Structures in Java #2 (+INTERVIEW QUESTIONS)
This course is perfect for anyone looking to learn about data structures and algorithms in Java. It covers topics such as prefix trees, ternary search trees, substring search algorithms, strings, sorting algorithms, data compression algorithms, and algorithms analysis. With approximately 12 hours of content, you will learn the basics of operations such as insertion, sorting, and autocomplete, as well as applications of tries in networking and the Boggle game. You will also learn about complexity classes, polynomial and non-deterministic polynomial algorithms, and running time complexities. Finally, the course includes interview questions to help you prepare for your next job. Join now and get started! ▼
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Course Feature
Cost:
Paid
Provider:
Udemy
Certificate:
Paid Certification
Language:
English
Start Date:
2023-01-24
Course Overview
❗The content presented here is sourced directly from Udemy platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.
Updated in [July 18th, 2023]
This course, Algorithms Data Structures in Java #2 (+INTERVIEW QUESTIONS), is designed to provide an overview of data structures and algorithms. It takes approximately 12 hours to complete and covers topics such as prefix trees (tries), ternary search trees, substring search algorithms, strings, sorting algorithms, data compression algorithms, and algorithms analysis.
The course begins with a discussion of prefix trees, which are used in modern search engines for autocomplete features and sorting. It then moves on to substring search algorithms, such as brute-force, Z algorithm, Rabin-Karp method, and Knuth-Morris-Pratt (KMP) substring search algorithm.
The course also covers strings in Java programming, sorting algorithms such as bubble sort, selection sort, insertion sort, shell sort, quicksort, and merge sort, as well as data compression algorithms such as run-length encoding, Huffman encoding, and LZW compression.
Finally, the course covers algorithms analysis, including running time analysis with big O (ordo), big Ω (omega) and big θ (theta) notations, complexity classes, polynomial (P) and non-deterministic polynomial (NP) algorithms, and O(1), O(logN), O(N) and several other running time complexities.
This course is designed to help students gain a better understanding of data structures and algorithms, and to prepare them for interviews. It is highly recommended that students type out the data structures several times on their own in order to get a good grasp of it.
Course Syllabus
Introduction
Trie Data Structures (Prefix Trees)
Interview Questions - IP Routing with Tries
Ternary Search Trees (TSTs)
Interview Questions - Boggle Game
Substring Search
Strings
Basic Sorting Algorithms
Interview Questions - Sorting
Data Compression
Next Steps
### APPENDIX - COMPLEXITY THEORY CRASH COURSE ###
Algorhyme FREE Algorithms Visualizer App
Course Materials (DOWNLOADS)
Pros & Cons
Brilliant content & instructor: Users appreciate the quality of the course content and the instructor's teaching style.
Comprehensive coverage: The course provides a strong foundation in algorithms and data structures, and concepts explained can be applied to any programming language.
Outdated lectures: Some lectures on String, Sorts, and Compression algorithms need to be updated, as they lack sufficient explanation regarding the written code.
Lack of quizzes: Users suggest that adding quizzes would be beneficial for better retention of the material.
Course Provider
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