Advanced Algorithms (Graph Algorithms) in Java from Udemy

This course is about advanced algorithms (graph algorithms) focusing on graph traversal, shortest path problems, spanning trees and maximum flow problems and a lots of its applications from Google Web Crawler to taking advantage of stock market arbitrage situations.

Section 1 - Graphs Theory Basics:

what is a G(V,E) graph
adjacency matrix representation
adjacency list representation

Section 2 - Graph Traversal (Breadth-First Search)

what is breadth-first search?
how to use BFS for WebCrawling in search engines?

Section 3 - Graph Traversal (Depth-First Search)

what is depth-first search?
how to use recursion to implement DFS
applications of DFS such as topological ordering and cycle detection
find way out of a maze with DFS

Section 4 - Topological Ordering

what is topological ordering (topological sort)
directed acyclic graphs (DAGs)
DAG shortest path and longest path
critical path methods and project management

Section 5 - Cycle Detection

what are cycles in a graph?
forward edges and backward edges
cycle detection algorithms (Tarjan's algorithm with DFS)

Section 6 - Dijkstra's Shortest Path Algorithm

what is a shortest path in a G(V,E) graph
Dijkstra's shortest path algorithm

Section 7 - Bellman-Ford Shortest Path Algorithm

Bellman-Ford algorithm
how to handle negative cycles
finding arbitrage opportunities on the FOREX

Section 8: - Spanning Trees (Kruskal and Prim's Algorithms)

what are spanning trees?
union find data structures
Kruskal's algorithm
Prim's algorithm

Section 9 - Strongly Connected Components (SCCs)

what are strongly connected components
Kosaraju's algorithm
Tarjan's algorithm

Section 10 - Maximum Flow Problem

the famous maximum flow problem
how to reduce most of the hard problems to maximum flow problem
Ford-Fulkerson algorithm
bipartite matching problem

Section 9 - Travelling Salesman Problem and Hamiltonian Cycles:

travelling salesman problem (TSP)
how to deal with NP-hard problems
what are meta-heuristics

Section 10 - Eulerian Paths

eulerian paths and eulerian cycles
Hierholzer algorithm and the Chinese Postman Problem

Section 11 - Algorithms Analysis

how to measure the running time of algorithms
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
O(1), O(logN), O(N) and several other running time complexities

The course is going to take approximately 11 hours to completely but I highly suggest you typing these algorithms out several times in order to get a good grasp of it. You can download the source code of the whole course at the last lecture.

You should definitely take this course if you are interested in advanced topics concerning algorithms. There are a bunch of fields where these methods can be used: from software engineering to scientific research.

Thanks for joining the course, let's get started.

What's inside

Learning objectives

Learn about the applications of data structures
Learn about the fundamental basics of graphs and graph theory
Implement advanced algorithms (graph algorithms) efficiently
Learn graph traversing such as breadth-first search and depth-first search
Learn about topological ordering and cycle detection

Learn about shortest path algorithms (dijkstra's and bellman-ford algorithms)
Learn about spanning trees
Learn about strongly connected components
Learn about hamiltonian cycles and eulerian cycles
Learn about maximum flow (max flow min cut theorem)

Learn about the applications of data structures
Learn about the fundamental basics of graphs and graph theory
Implement advanced algorithms (graph algorithms) efficiently
Learn graph traversing such as breadth-first search and depth-first search
Learn about topological ordering and cycle detection
Learn about shortest path algorithms (dijkstra's and bellman-ford algorithms)
Learn about spanning trees
Learn about strongly connected components
Learn about hamiltonian cycles and eulerian cycles
Learn about maximum flow (max flow min cut theorem)

Syllabus

Introduction

Complexity theory basics

Graph Theory Overview

Graph theory overview

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Develops advanced algorithms and graph theory techniques sought by software engineers and scientific researchers

Teaches depth-first search and breadth-first search, algorithms fundamental to network traversal

Helps learners master efficient graph traversal for applications such as WebCrawling

Delves into more complex scenarios like topological ordering, cycle detection, and finding strongly connected components

Provides numerous examples and use cases to reinforce learning

May be less suitable for beginners in the field without foundational knowledge of algorithms and data structures

Reviews summary

In-depth graph algorithms with java

According to students, "Advanced Algorithms (Graph Algorithms) in Java" is a highly-regarded course offering a deep dive into graph algorithms. Learners praise the instructor's remarkably clear explanations, which break down complex topics with great intuition. Many appreciate the well-structured Java implementations and the coverage of practical, real-world applications, from web crawling to financial arbitrage. While it provides a solid theoretical foundation and valuable course challenges, some reviewers suggest a need for more extensive hands-on practice problems. Prospective students should be aware it assumes a strong background in basic data structures and Java. Notably, earlier audio quality concerns seem to have been addressed in newer content.

Past audio issues seem resolved in recent course content.

"The audio quality in some early lectures was inconsistent, and the accent can be a bit challenging..."

"I noticed that some of the older reviews mentioned audio issues, which seemed to have been resolved in the later parts of the course."

"I found the overall production quality to be consistently good in recent sections of the course."

Features well-structured, easy-to-follow Java implementations.

"The Java implementations are well-structured and easy to follow."

"The code examples are excellent and truly help in grasping the theoretical aspects."

"The Java code provided is clean."

"The examples using Java are very helpful."

Covers practical, real-world applications for strong relevance.

"I especially appreciated the practical applications discussed, like the web crawler and arbitrage."

"I loved the coverage of both theoretical concepts and their real-world applications."

"The examples are practical, and the Bellman-Ford algorithm application to FOREX arbitrage was particularly interesting."

"This course is useful for coding interviews or professional work as it covered essential graph algorithms."

Provides clear, intuitive explanations of complex algorithms.

"The instructor's explanations are incredibly clear, breaking down complex concepts like Tarjan's algorithm into digestible pieces."

"Fantastic deep dive into graph algorithms. The lectures are detailed and the instructor explains the intuition behind each algorithm..."

"This course exceeded my expectations. The explanations are precise, and the Java implementations are very clear."

"The instructor clearly knows his stuff. The structure makes it easy to follow along."

Primarily theoretical with code, lacks extensive practical problems.

"I wish there were more diverse problem sets or exercises beyond the challenges."

"I found the course lacked sufficient practice problems. It's mostly just listening and watching code."

"I needed to seek out external resources for exercises."

"It's more theoretical than practical application."

Requires strong programming basics; pacing can be challenging.

"It's definitely for someone with a good grasp of basic data structures and Java."

"While it's great, it's not for total beginners. A solid foundation in Java and basic data structures is essential."

"Some sections, particularly on maximum flow, felt a bit rushed."

"Some parts require me to pause and re-watch to fully grasp, especially the proofs."

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 Advanced Algorithms (Graph Algorithms) in Java with these activities:

Review Graph Theory Basics

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Refresh your knowledge of graph theory concepts, such as adjacency matrix and adjacency list, to strengthen your foundation for advanced graph algorithms.

Browse courses on Graphs

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Review definitions and representations of graphs.
Practice converting between adjacency matrix and adjacency list representations.

Graph Algorithms Reference Collection

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Compile a comprehensive collection of reference materials, tutorials, and code examples to support your understanding of graph algorithms.

Browse courses on Graph Algorithms

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Gather resources from various sources, such as textbooks, websites, and online forums.
Organize and categorize the materials based on different graph algorithms.
Include helpful notes and summaries to enhance comprehension.

Book Review: Introduction to Algorithms

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Review a classic textbook on algorithms to reinforce your understanding of graph algorithms and their applications.

View Introduction to Algorithms, fourth edition on Amazon

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Read selected chapters on graph algorithms, such as shortest path and minimum spanning trees.
Summarize key concepts and algorithms in your own words.
Identify areas where you need further clarification or practice.

Six other activities

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Show all nine activities

Breadth-First Search Exercises

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Practice implementing and applying breadth-first search to traverse graphs, enhancing your understanding of graph exploration.

Browse courses on Breadth-First Search

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Implement a breadth-first search algorithm.
Apply BFS to find the shortest path in an unweighted graph.

Topological Sorting Project

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Develop a program to perform topological sorting on a directed acyclic graph to enhance your understanding of ordering tasks in a dependency-based system.

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Design and implement a topological sorting algorithm.
Test your program on various input graphs with different dependencies.
Analyze the efficiency of your algorithm and suggest improvements.

Prim's Algorithm Tutorial

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Follow a guided tutorial to learn about Prim's algorithm and its application in finding minimum spanning trees.

Browse courses on Prim's Algorithm

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Watch a video tutorial or read an article on Prim's algorithm.
Implement Prim's algorithm in a programming language of your choice.

Mentor Junior Students in Graph Algorithms

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Provide guidance and support to junior students who are learning graph algorithms, helping them develop a deeper understanding and overcome challenges.

Browse courses on Graph Algorithms

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Identify opportunities to mentor junior students, such as through tutoring sessions or study groups.
Create lesson plans and activities to help students grasp graph algorithms.
Provide constructive feedback and encouragement to support students' progress.

Dijkstra's Algorithm Problems

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Practice solving problems related to Dijkstra's algorithm to reinforce your understanding of finding the shortest path in a graph.

Browse courses on Dijkstra's Algorithm

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Review the concept of Dijkstra's algorithm and its implementation.
Solve a set of practice problems on finding the shortest path in various graphs.
Analyze the time complexity of your solutions.

Maximum Flow Problem Practice

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Solve a series of practice problems involving the maximum flow problem and its applications to enhance your problem-solving skills.

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Review the maximum flow problem and Ford-Fulkerson algorithm.
Implement the Ford-Fulkerson algorithm in a programming language of your choice.
Solve practice problems involving maximum flow in various network scenarios.

Career center

Learners who complete Advanced Algorithms (Graph Algorithms) in Java will develop knowledge and skills that may be useful to these careers:

Data Scientist

Data Scientists use advanced algorithms to analyze data and extract insights that can help businesses make better decisions. This course can help you develop the skills you need to become a successful Data Scientist. You will learn how to implement advanced algorithms efficiently, including graph traversal algorithms, shortest path algorithms, and maximum flow algorithms. You will also learn about graph theory and its applications in various fields, such as software engineering and scientific research.

See salaries and explore the career path for Data Scientist

Software Engineer

Software Engineers design, develop, and maintain software systems. This course can help you develop the skills you need to become a successful Software Engineer. You will learn how to implement advanced algorithms efficiently, including graph traversal algorithms, shortest path algorithms, and maximum flow algorithms. You will also learn about graph theory and its applications in various fields, such as software engineering and scientific research.

See salaries and explore the career path for Software Engineer

Quantitative Analyst

Quantitative Analysts use advanced algorithms to analyze data and make predictions. This course can help you develop the skills you need to become a successful Quantitative Analyst. You will learn how to implement advanced algorithms efficiently, including graph traversal algorithms, shortest path algorithms, and maximum flow algorithms. You will also learn about graph theory and its applications in various fields, such as finance and economics.

See salaries and explore the career path for Quantitative Analyst

Operations Research Analyst

Operations Research Analysts use advanced algorithms to solve complex problems in business and industry. This course can help you develop the skills you need to become a successful Operations Research Analyst. You will learn how to implement advanced algorithms efficiently, including graph traversal algorithms, shortest path algorithms, and maximum flow algorithms. You will also learn about graph theory and its applications in various fields, such as logistics, scheduling, and supply chain management.

See salaries and explore the career path for Operations Research Analyst

Computer Scientist

Computer Scientists design, develop, and analyze computer systems. This course can help you develop the skills you need to become a successful Computer Scientist. You will learn how to implement advanced algorithms efficiently, including graph traversal algorithms, shortest path algorithms, and maximum flow algorithms. You will also learn about graph theory and its applications in various fields, such as computer science, artificial intelligence, and machine learning.

See salaries and explore the career path for Computer Scientist

Data Analyst

Data Analysts use data to solve problems and make informed decisions. This course can help you develop the skills you need to become a successful Data Analyst. You will learn how to implement advanced algorithms efficiently, including graph traversal algorithms, shortest path algorithms, and maximum flow algorithms. You will also learn about graph theory and its applications in various fields, such as business, healthcare, and social sciences.

See salaries and explore the career path for Data Analyst

Business Analyst

Business Analysts use data and analysis to help businesses make better decisions. This course can help you develop the skills you need to become a successful Business Analyst. You will learn how to implement advanced algorithms efficiently, including graph traversal algorithms, shortest path algorithms, and maximum flow algorithms. You will also learn about graph theory and its applications in various fields, such as business, finance, and marketing.

See salaries and explore the career path for Business Analyst

Financial Analyst

Financial Analysts use data to analyze financial markets and make investment recommendations. This course can help you develop the skills you need to become a successful Financial Analyst. You will learn how to implement advanced algorithms efficiently, including graph traversal algorithms, shortest path algorithms, and maximum flow algorithms. You will also learn about graph theory and its applications in various fields, such as finance, economics, and accounting.

See salaries and explore the career path for Financial Analyst

Market Researcher

Market Researchers use data to understand consumer behavior and market trends. This course can help you develop the skills you need to become a successful Market Researcher. You will learn how to implement advanced algorithms efficiently, including graph traversal algorithms, shortest path algorithms, and maximum flow algorithms. You will also learn about graph theory and its applications in various fields, such as marketing, advertising, and public relations.

See salaries and explore the career path for Market Researcher

Web Developer

Web Developers design and develop websites. This course can help you develop the skills you need to become a successful Web Developer. You will learn how to implement advanced algorithms efficiently, including graph traversal algorithms, shortest path algorithms, and maximum flow algorithms. You will also learn about graph theory and its applications in various fields, such as web development, user experience design, and search engine optimization.

See salaries and explore the career path for Web Developer

Software Tester

Software Testers test software to ensure that it meets requirements and is free of defects. This course can help you develop the skills you need to become a successful Software Tester. You will learn how to implement advanced algorithms efficiently, including graph traversal algorithms, shortest path algorithms, and maximum flow algorithms. You will also learn about graph theory and its applications in various fields, such as software testing, quality assurance, and software development.

See salaries and explore the career path for Software Tester

Project Manager

Project Managers plan, execute, and deliver projects. This course can help you develop the skills you need to become a successful Project Manager. You will learn how to implement advanced algorithms efficiently, including graph traversal algorithms, shortest path algorithms, and maximum flow algorithms. You will also learn about graph theory and its applications in various fields, such as project management, operations management, and supply chain management.

See salaries and explore the career path for Project Manager

Systems Analyst

Systems Analysts design and implement computer systems. This course can help you develop the skills you need to become a successful Systems Analyst. You will learn how to implement advanced algorithms efficiently, including graph traversal algorithms, shortest path algorithms, and maximum flow algorithms. You will also learn about graph theory and its applications in various fields, such as systems analysis, systems design, and systems engineering.

See salaries and explore the career path for Systems Analyst

Database Administrator

Database Administrators manage and maintain databases. This course can help you develop the skills you need to become a successful Database Administrator. You will learn how to implement advanced algorithms efficiently, including graph traversal algorithms, shortest path algorithms, and maximum flow algorithms. You will also learn about graph theory and its applications in various fields, such as database administration, data management, and data analysis.

See salaries and explore the career path for Database Administrator

Network Administrator

Network Administrators manage and maintain computer networks. This course can help you develop the skills you need to become a successful Network Administrator. You will learn how to implement advanced algorithms efficiently, including graph traversal algorithms, shortest path algorithms, and maximum flow algorithms. You will also learn about graph theory and its applications in various fields, such as network administration, network security, and network engineering.

See salaries and explore the career path for Network Administrator