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

Adjacency matrix and adjacency list

Adjacency matrix and adjacency list implementation

Applications of graphs

Graph Algorithms Overview Quiz

Breadth-First Search (BFS)

Breadth-first search introduction

Breadth-first search implementation

Applications of breadth-first search

BFS Quiz

Course Challenge #1 - WebCrawler

Breadth-first search - WebCrawler (core of search engines)

Breadth-first search - WebCrawler implementation

Depth-First Search (DFS)

DFS implementation I - with stack

DFS implementation II - with recursion

Depth-first search and stack memory visualisation

Applications of depth-first search

Memory management of graph traversal algorithms

Graph Traversal Quiz

Course Challenge #2- Maze Escape

Maze problem introduction

Course challenge #1 - maze escape

Maze solving algorithm implementation

Topological Ordering

What is topological ordering?

Topological ordering implementation I

Topological ordering implementation II

Finding the shortest path with topological ordering

Topological ordering shortest path implementation I

Topological ordering shortest path implementation II

Dynamic programming with topological sort

Topological Ordering Quiz

Cycle Detection

Cycle detection introduction

Cycle detection implementation I

Cycle detection implementation II

Cycle Detection Quiz

Shortest Path Methods - Dijkstra's Algorithm

What is the shortest path problem?

Dijkstra algorithm visualization

Dijkstra algorithm implementation I

Dijkstra algorithm implementation II

Dijkstra algorithm implementation III

Dijktsra's algorithm with adjacency matrix representation

Shortest path algorithms applications

Dijkstra's Algorithm Quiz

Course Challenge #3 - Longest Path

The critical path method (CPM) and longest paths

Course challenge #3 - DAG shortest path

Longest path implementation

Shortest Path Methods - Bellman-Ford Algorithm

What is the Bellman-Ford algorithm?

Bellman-Ford algorithm visualisation

Bellman-Ford algorithm implementation I

Bellman-Ford algorithm implementation II

Greedy algorithm or dynamic programming approach?

Bellman-Ford Algorithm Quiz

Course Challenge #4 - Arbitrage on FOREX

Arbitrage situations on FOREX introduction

Arbitrage situations on FOREX implementation

Spanning Trees - Kruskal's Algorithm

What is the disjoint set data structure?

Disjoint sets visualization

Kruskal's algorithm introduction

Kruskal algorithm implementation I

Kruskal algorithm implementation II

Kruskal algorithm implementation III

Kruskal's Algorithm Quiz

Spanning Trees - Prim's Algorithm

What is the lazy Prim's algorithm?

Lazy Prim's algorithm implementation I

Lazy Prim's algorithm implementation II

What is the eager Prim's algorithm?

Eager Prim's algorithm implementation

Comparison of minimum spanning tree algorithms

Applications of spanning trees

Prim's Algorithm Quiz

Strongly Connected Components - Kosaraju's Algorithm

Strongly connected components introduction

Kosaraju algorithm introduction

Kosaraju algorithm implementation II

Kosaraju algorithm implementation III

Strongly Connected Components - Tarjan's Algorithm

Tarjan algorithm introduction

Tarjan algorithm visualization

Tarjan algorithm implementation

Applications of strongly connected components

Strongly Connected Components Quiz

Maximum Flow Problem

Maximum flow introduction - basics

Maximum flow introduction - properties

Maximum flow introduction - cuts

Maximum flow introduction - residual networks

Good to know

Know what's good

, what to watch for

, 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

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

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

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

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

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

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

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

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.

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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.

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