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.

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, backtracking, dynamic programming, and greedy algorithms. You'll also learn about basic graph algorithms, depth-first search, shortest paths, minimum spanning trees, and all-pairs shortest paths. 

By the end of this course, you'll have acquired a wide range of skills that will significantly enhance your ability to solve problems efficiently in Java. Through this course, not only will you improve your coding skills, but you will also gain confidence in tackling complex problems.

Mastering Algorithms for Problem Solving in Java

What is the time complexity of all of the variants of the lattice algorithm to compute the product of any $m$-digit number with any $n$-digit number?

What is the time complexity of all of the variants of the lattice algorithm to compute the product of any <math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>m</mi></mrow><annotation encoding="application/x-tex">m</annotation></semantics></math>m-digit number with any <math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>n</mi></mrow><annotation encoding="application/x-tex">n</annotation></semantics></math>n-digit number?

It's way too complex for students to understand.

It does not contain operations that computers can perform.

It's considered an algorithm in the traditional sense because it's a well-defined, step-by-step procedure for solving a specific problem. 

Why is Martin’s algorithm *not* considered an algorithm?

Why is Martin’s algorithm not considered an algorithm?

Using a combination of pseudocode and structured English.

Using colloquial English and mathematical notation.

What's the recommended way to present an algorithm?

What’s the recommended way to present an algorithm?

It represents the exact running time of an algorithm on a specific input.

It measures the average case complexity of an algorithm.

It quantifies the amount of memory used by an algorithm.

It provides an upper bound on the worst-case running time of an algorithm.

Which statement best describes the concept of asymptotic notation in algorithm analysis?

Which statement best describes the concept of asymptotic notation in algorithm analysis?

How the running time changes as the size of the input grows

What is important in measuring the running time of an algorithm?



What is important in measuring the running time of an algorithm?

Test your knowledge of the concepts covered in the introduction chapter. 

Quiz: Introduction to Algorithm

Test your knowledge of the concepts covered in the introduction chapter.

Getting Started

Introduction to Algorithm

Recursion

Backtracking

Dynamic Programming

Greedy Algorithms

Prove Your Skills: A Five-Chapter Assessment

Basic Graph Algorithms

Depth-First Search

Minimum Spanning Trees

Shortest Paths

All-Pairs Shortest Paths

Pushing Your Limits: A Comprehensive Assessment

Wrapping up

Quiz: Introduction to Algorithm