Data Structures & Algorithms IV: Pattern Matching, Dijkstra’s, MST, and Dynamic Programming Algorithms from edX

This Data Structures & Algorithms course completes the 4-course sequence of the program with graph algorithms, dynamic programming and pattern matching solutions. A short Java review is presented on topics relevant to new data structures covered in this course. The course does require prior knowledge of Java, object-oriented programming and linear and non-linear data structures. Time complexity is threaded throughout the course within all the data structures and algorithms.

You will delve into the Graph ADT and all of its auxiliary data structures that are used to represent graphs. Understanding these representations is key to developing algorithms that traverse the entire graph. Two traversal algorithms are studied: Depth-First Search and Breadth-First Search. Once a graph is traversed then it follows that you want to find the shortest path from a single vertex to all other vertices. Dijkstra’s algorithm allows you to have a deeper understanding of the Graph ADT. You will investigate the Minimum Spanning Tree (MST) problem. Two important, greedy algorithms create an MST: Prim’s and Kruskal’s.

Prim’s focuses on connected graphs and uses the concept of growing a cloud of vertices. Kruskal’s approaches the MST differently and creates clusters of vertices that then form a forest.

The other half of this course examines text processing algorithms. Pattern Matching algorithms are crucial in everyday technology. You begin with the simplest of the algorithms, Brute Force, which is the easiest to implement and understand. Boyer-Moore and Knuth-Morris-Pratt (KMP) improve efficiency by using preprocessing techniques to find the pattern. However, KMP does an exceptional job of not repeating comparisons once the pattern is shifted. The last pattern matching algorithm is Rabin-Karp which is an “out of the box” approach to the problem. Rabin-Karp uses hash codes and a “rolling hash” to find the pattern in the text. A different text processing problem is locating DNA subsequences which leads us directly to Dynamic Programming techniques. You will break down large problems into simple subproblems that may overlap, but can be solved. Longest Common Subsequence is such an algorithm that locates the subsequence through dynamic programming techniques.

What's inside

Learning objectives

Improve java programming skills by implementing graph and dynamic programming algorithms
Study algorithm techniques for finding patterns in text processing
Use preprocessing in the boyer-moore and kmp algorithms
Explore the problem with hash codes in the rabin-karp algorithm
Understand the graph adt and its representations within auxiliary structures
Traverse graphs using the depth-first and breadth-first search algorithms

Investigate dijkstra’s shortest path algorithm which operates on weighted graphs
Study the minimum spanning tree (mst) problem and its characteristics
Utilize greedy algorithms, like prim’s and kruskal’s, to find the mst
Decompose large problems using dynamic programming techniques
Apply dynamic programming techniques in the longest common subsequence algorithm

Improve java programming skills by implementing graph and dynamic programming algorithms
Study algorithm techniques for finding patterns in text processing
Use preprocessing in the boyer-moore and kmp algorithms
Explore the problem with hash codes in the rabin-karp algorithm
Understand the graph adt and its representations within auxiliary structures
Traverse graphs using the depth-first and breadth-first search algorithms
Investigate dijkstra’s shortest path algorithm which operates on weighted graphs
Study the minimum spanning tree (mst) problem and its characteristics
Utilize greedy algorithms, like prim’s and kruskal’s, to find the mst
Decompose large problems using dynamic programming techniques
Apply dynamic programming techniques in the longest common subsequence algorithm

Syllabus

Module 0: Introduction and Review

Review of important Java principles involved in object-oriented design

The Iterator & Iterable design patterns, and the Comparable & Comparator interfaces

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Develops valuable problem-solving skills using graph and pattern matching algorithms that are essential in various industries

Provides a deeper understanding of data structures and algorithms through hands-on Java programming

Taught by experienced instructors specializing in computer science and data structures

Requires prior knowledge of Java, object-oriented programming, and data structures, making it suitable for intermediate learners

Reviews summary

Advanced algorithms: graphs, dp, & pattern matching

According to learners, this course is a rigorous and comprehensive continuation of the Data Structures & Algorithms series, proving to be highly rewarding for those seeking to deepen their understanding of advanced topics. Students praise the instructor's clear explanations of complex algorithms like Dijkstra's, MST, and Dynamic Programming. The challenging yet effective coding assignments are frequently highlighted as a core strength, truly solidifying concepts and encouraging practical application. While many find the pace is fast and it demands a solid foundational knowledge, a minority of reviewers found some sections, particularly Dynamic Programming and KMP, required supplementary materials for full comprehension. The course consistently receives positive feedback for its depth and focus on time complexity analysis.

Course offers in-depth exploration of advanced algorithms.

"Excellent depth on graph algorithms and dynamic programming."

"Comprehensive and detailed. The section on graph algorithms, especially Dijkstra's, was very thorough."

"It covers a lot of ground quickly, from graph algorithms to dynamic programming."

"A good continuation of the series. The content is relevant and important for software engineering roles."

Hands-on coding tasks are difficult but effectively solidify learning.

"The coding assignments are challenging but incredibly rewarding and help solidify the concepts."

"The problem sets truly test your understanding."

"The implementation tasks are very helpful for practical understanding."

"The assignments are crucial; I learned the most by implementing the algorithms myself."

Instructor provides precise and understandable explanations for complex topics.

"The instructor explains complex algorithms like Dijkstra's and Dynamic Programming very clearly."

"Absolutely brilliant! This course clarified many advanced topics I struggled with before. The explanations are precise."

"One of the best courses on advanced algorithms. The instructor breaks down complex topics into digestible parts."

"The instructor's passion for the subject shines through. A must-take for anyone serious about algorithms."

Some learners needed external resources for full comprehension of certain topics.

"I had to look up supplementary materials for Dynamic Programming to fully grasp it."

"I found some of the explanations for Dynamic Programming unclear. I had to spend a lot of time on external resources."

"Some parts felt a bit rushed, especially KMP and Rabin-Karp."

"The KMP explanation could be improved."

Course moves quickly and necessitates a strong prior understanding of DSA.

"Too difficult for my level, even with previous DSA knowledge. The pace is very fast, and it assumes a lot."

"Definitely requires a solid foundation in Java and DSA already."

"It's a challenging course, but be prepared for a steep learning curve."

"I felt overwhelmed by the theoretical depth without enough practical walkthroughs."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Data Structures & Algorithms IV: Pattern Matching, Dijkstra’s, MST, and Dynamic Programming Algorithms with these activities:

Review Object-Oriented Design principles

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Sharpen your Java skills by brushing up on Object-Oriented Design principles relevant to this course.

Browse courses on Object-Oriented Programming

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Review the Object-Oriented Design principles
Review the Java syntax for representing these principles
Practice writing simple Java code that implements these principles

Create a Graph ADT and its auxiliary data structures

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Build a foundation to understand graph algorithms by creating a Graph ADT.

Browse courses on Graphs

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Start by designing the Graph ADT on paper
Implement the Graph ADT in Java
Test your implementation with various graph algorithms

Practice implementing graph traversal algorithms

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Reinforce your understanding of graph traversal algorithms by practicing implementations.

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Choose a programming language and implement the Depth-First Search (DFS) algorithm
Implement the Breadth-First Search (BFS) algorithm
Test your implementations on graphs of varying sizes and structures

Four other activities

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Explore Dijkstra's Shortest Path algorithm

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Delve deeper into working with weighted graphs by studying Dijkstra's algorithm.

Browse courses on Dijkstra's Algorithm

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Find resources and tutorials on Dijkstra's algorithm
Follow a tutorial to implement the algorithm in a programming language of your choice
Test your implementation on various graphs and analyze the results

Practice implementing Minimum Spanning Tree algorithms

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Enhance your understanding of finding MSTs by implementing different algorithms.

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Choose a programming language and implement Prim's algorithm
Implement Kruskal's algorithm
Compare the performance and characteristics of both algorithms

Review 'Introduction to Algorithms' by Cormen, Leiserson, Rivest, and Stein

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Supplement your understanding of algorithms by reviewing this classic textbook.

View Introduction to Algorithms, fourth edition on Amazon

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Read chapters relevant to graph algorithms, dynamic programming, and pattern matching
Solve practice problems to reinforce concepts

Develop a reference guide for Dynamic Programming techniques

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Solidify your understanding by creating a comprehensive guide to Dynamic Programming techniques.

Browse courses on Dynamic programming

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Gather and organize your knowledge of Dynamic Programming concepts
Create a document or presentation that outlines the key aspects of these techniques
Provide examples and illustrations to enhance clarity

Career center

Learners who complete Data Structures & Algorithms IV: Pattern Matching, Dijkstra’s, MST, and Dynamic Programming Algorithms will develop knowledge and skills that may be useful to these careers:

Data Scientist

A Data Scientist analyzes data to create models and solve problems. This course, Data Structures & Algorithms IV: Pattern Matching, Dijkstra’s, MST, and Dynamic Programming Algorithms, provides a solid foundation in data structures and algorithms that are essential for success in this role. The course covers topics such as graph algorithms, dynamic programming, and pattern matching, which are all heavily used in data science. Additionally, the course provides a strong foundation in Java programming, which is a popular language for data science.

See salaries and explore the career path for Data Scientist

Software Engineer

A Software Engineer designs, develops, and maintains software systems. This course provides a strong foundation in data structures and algorithms, which are essential for success in this role. The course covers topics such as graph algorithms, dynamic programming, and pattern matching, which are all heavily used in software engineering. Additionally, the course provides a strong foundation in Java programming, which is a popular language for software development.

See salaries and explore the career path for Software Engineer

Quantitative Analyst

A Quantitative Analyst uses mathematical and statistical models to analyze financial data. This course provides a strong foundation in data structures and algorithms, which are essential for success in this role. The course covers topics such as graph algorithms, dynamic programming, and pattern matching, which are all heavily used in quantitative finance. Additionally, the course provides a strong foundation in Java programming, which is a popular language for quantitative finance.

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Operations Research Analyst

An Operations Research Analyst uses mathematical and analytical techniques to solve problems in a variety of industries. This course provides a strong foundation in data structures and algorithms, which are essential for success in this role. The course covers topics such as graph algorithms, dynamic programming, and pattern matching, which are all heavily used in operations research. Additionally, the course provides a strong foundation in Java programming, which is a popular language for operations research.

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Computer Scientist

A Computer Scientist researches and develops new computing technologies. This course provides a strong foundation in data structures and algorithms, which are essential for success in this role. The course covers topics such as graph algorithms, dynamic programming, and pattern matching, which are all heavily used in computer science. Additionally, the course provides a strong foundation in Java programming, which is a popular language for computer science.

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Data Engineer

A Data Engineer designs and builds systems to store and process data. This course provides a strong foundation in data structures and algorithms, which are essential for success in this role. The course covers topics such as graph algorithms, dynamic programming, and pattern matching, which are all heavily used in data engineering. Additionally, the course provides a strong foundation in Java programming, which is a popular language for data engineering.

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Machine Learning Engineer

A Machine Learning Engineer designs and builds machine learning models. This course provides a strong foundation in data structures and algorithms, which are essential for success in this role. The course covers topics such as graph algorithms, dynamic programming, and pattern matching, which are all heavily used in machine learning. Additionally, the course provides a strong foundation in Java programming, which is a popular language for machine learning.

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Business Analyst

A Business Analyst analyzes business processes and systems to identify areas for improvement. This course provides a strong foundation in data structures and algorithms, which are essential for success in this role. The course covers topics such as graph algorithms, dynamic programming, and pattern matching, which are all heavily used in business analysis. Additionally, the course provides a strong foundation in Java programming, which is a popular language for business analysis.

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Financial Analyst

A Financial Analyst analyzes financial data to make investment recommendations. This course provides a strong foundation in data structures and algorithms, which are essential for success in this role. The course covers topics such as graph algorithms, dynamic programming, and pattern matching, which are all heavily used in financial analysis. Additionally, the course provides a strong foundation in Java programming, which is a popular language for financial analysis.

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Market Researcher

A Market Researcher conducts research to identify and understand customer needs. This course provides a strong foundation in data structures and algorithms, which are essential for success in this role. The course covers topics such as graph algorithms, dynamic programming, and pattern matching, which are all heavily used in market research. Additionally, the course provides a strong foundation in Java programming, which is a popular language for market research.

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Product Manager

A Product Manager develops and manages products. This course provides a strong foundation in data structures and algorithms, which are essential for success in this role. The course covers topics such as graph algorithms, dynamic programming, and pattern matching, which are all heavily used in product management. Additionally, the course provides a strong foundation in Java programming, which is a popular language for product management.

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Project Manager

A Project Manager plans and manages projects. This course provides a strong foundation in data structures and algorithms, which are essential for success in this role. The course covers topics such as graph algorithms, dynamic programming, and pattern matching, which are all heavily used in project management. Additionally, the course provides a strong foundation in Java programming, which is a popular language for project management.

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Technical Writer

A Technical Writer creates documentation for technical products. This course provides a strong foundation in data structures and algorithms, which are essential for success in this role. The course covers topics such as graph algorithms, dynamic programming, and pattern matching, which are all heavily used in technical writing. Additionally, the course provides a strong foundation in Java programming, which is a popular language for technical writing.

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IT Manager

An IT Manager plans and manages IT systems. This course provides a strong foundation in data structures and algorithms, which are essential for success in this role. The course covers topics such as graph algorithms, dynamic programming, and pattern matching, which are all heavily used in IT management. Additionally, the course provides a strong foundation in Java programming, which is a popular language for IT management.

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Computer Programmer

A Computer Programmer writes code to implement software systems. This course provides a strong foundation in data structures and algorithms, which are essential for success in this role. The course covers topics such as graph algorithms, dynamic programming, and pattern matching, which are all heavily used in computer programming. Additionally, the course provides a strong foundation in Java programming, which is a popular language for computer programming.

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