Free
Intermediate
28h
Mastering Algorithms for Problem Solving in Java Save for later
Save for later
Gain insights into essential algorithms for effective problem-solving in Java. Delve into recursion, dynamic programming, and graph algorithms to enhance your coding and tackle complex problems confidently.
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Course Overview
As a developer, mastering the concepts of algorithms and being proficient in implementing them is essential to improving problem-solving skills. This course aims to equip you with an in-depth understanding of algorithms and how they can be utilized for problem solving in Java.
Starting with the basics, you'll gain a foundational understanding of what algorithms are, with topics ranging from simple multiplication algorithms to analyzing algorithms. Then, you’ll delve into more advanced topics like recursion...Show More
As a developer, mastering the concepts of algorithms and being proficient in implementing them is essential to improving problem...Show More
WHAT YOU'LL LEARN
A comprehensive understanding of algorithms and their applications in problem-solving
Proficiency in implementing recursion and backtracking in Java for complex tasks in Java
Understanding and applying the concepts of memoization and dynamic programming for efficient computation
Hands-on experience solving algorithmic challenges in Java
A comprehensive understanding of algorithms and their applications in problem-solving
Show more
Course Content
1.
Getting Started
1 Lessons
Get familiar with algorithms, essential concepts, and practical applications for problem-solving in Java.
2.
Introduction to Algorithm
6 Lessons
Look at the fundamentals of algorithms, their historical evolution, and efficiency analysis.
3.
Recursion
13 Lessons
Master the steps to effective recursion, including reduction, sorting, and element selection techniques.
4.
Backtracking
10 Lessons
Enhance your skills in solving complex problems with recursive backtracking algorithms.
5.
Dynamic Programming
11 Lessons
Take a closer look at dynamic programming principles to solve complex problems efficiently.
Fibonacci Numbers–Recursive ApproachFibonacci Numbers–Iterative ApproachText SegmentationLongest Increasing SubsequenceEdit DistanceSubset Sum–Dynamic ProgrammingOptimal Binary Search Trees–Dynamic ProgrammingDynamic Programming on TreesChallenge: Dynamic ProgrammingSolution: Dynamic ProgrammingQuiz: Dynamic Programming
6.
Greedy Algorithms
7 Lessons
Follow the process of using greedy algorithms for optimal file storage, class scheduling, and encoding.
8.
Basic Graph Algorithms
9 Lessons
Master the steps to understand, represent, search, and modify graphs, including practical Java applications.
9.
Depth-First Search
11 Lessons
Learn how to use depth-first search for graph traversal, cycle detection, and connectivity.
10.
Minimum Spanning Trees
8 Lessons
Grasp the fundamentals of minimum spanning trees, key algorithms, and their efficiency.
11.
Shortest Paths
10 Lessons
Go hands-on with finding shortest paths in graphs using various algorithms.
12.
All-Pairs Shortest Paths
9 Lessons
Grasp the fundamentals of algorithms to solve all-pairs shortest paths and handle negative cycles.
14.
Wrapping up
1 Lessons
Take a look at key algorithm concepts and their practical problem-solving applications.
Certificate of Completion
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