# 5 Best Graph Theory Courses [2021 SEPTEMBER] [UPDATED]

Subject experts have composed this list of Best Graph Theory Online Tutorials, Course, Training, and Certification on the internet for 2021. It has numerous paid and free materials to assist you in learning Graph Theory, and the matter are suitable for learners of every level. Do have a look at our take on Best Classroom Management Courses.

## 5 Best Graph Theory Courses [2021 SEPTEMBER] [UPDATED]

### 1. Introduction to Graph Theory by University of California San Diego (Coursera)

In this program, you will get a beginner level understanding of graph theory and how it can solve a range of problems. Learn to represent mathematical results and explore insights about ideas that back them up. After finishing the lectures, you will be prepared to get hands-on and apply the algorithms using Python.

Key USPs-

– Represent problems graphically and identify the relationship between objects.

– Distinguish between Hamiltonian and Eulerian cycles and their rule in genome assembly.

– Connect cities with minimal cost and look into the design of integrated circuits.

– Plenty of assignments and quizzes.

– Get a certificate by opting for verified track or audit the videos for free.

Duration: 20 hours

Rating: 4.5 out of 5

Review: Appreciate the structure and the explanations with examples. The practice tool before every lesson not makes it fun to learn but also sets the student in the context and can anticipate the concept. – SU.

### 2. Graph Theory Algorithms (Udemy)

If you aspire to build a computer science career, this program will help you build a strong foundation in this essential subject. Commence by getting acquainted with the standard terminologies and concepts. The classes also look at some popular algorithms like breadth and depth-first search, topological sort, Bellman-Ford, Floyd-Warshall algorithms, and much more. Check out our compilation of Best Reverse Engineering Courses.

Key USPs-

– Find out articulation points and bridges.

– Use Tarjan’s algorithm to detect strong components.

– Loo into dynamic programming approach for Travelling Salesman Problem.

– Every section is accompanied by a quiz to check your understanding level.

– Source code is available to see the discusses approaches in action.

– 46 Lectures + Full lifetime access.

Duration: 9 hours

Rating: 4.6 out of 5

### 3. Graph Theory (Udemy)

This tutorial will suit your needs if you are entirely new to the area and have no prior experience. The concepts are broken into smaller bits to make it easy to understand, and the complexity of the covered ideas elevate gradually. Some of the key areas touched upon are digraphs, trees, coloring, and planar and bipartite graphs.

Key USPs-

– Examples follow theory lessons to demonstrate the application.

– Go over edge and vertex deletion and addition.

– Learn about Kuratowski’s theorem and Euler’s formula.

– Attempt quizzes at the end of the videos.

– Reach out to the mentor and get answers to your doubts.

– 67 Lectures + Full lifetime access.

Duration: 10 hours

Rating: 4.6 out of 5

### 4. Graph Theory and Additive Combinatorics (MIT OpenCourseWare)

This class has been put together to analyze the classical and recent developments in additive combinatorics and graph theory and their connection. Apart from the essentials, you can also investigate some of the open problems and research work. Post completion, you can check out the course collection on the website to learn more about the subject. Don’t forget to check our list of Best Research Methods Courses.

Key USPs-

– Check out the instructor insights sections to get a better idea of the content.

– Complete the set of six assignments to practice along with the curriculum.

Duration: Variable

Rating: 4.4 out of 5

### 5. Advanced Algorithmics and Graph Theory with Python (edX)

Learning complex topics can often be an ordeal, making it difficult to connect all the discussed topics without proper demonstrations and examples. This program addresses this issue by putting together a curriculum that immediately offers the chance to practice the covered sections. Weave through challenges by coming up with unique solutions and boost your artificial intelligence simultaneously. By the end, you will be well acquainted with advanced algorithms and the data structures used to implement them.

Key USPs-

– Develop the intuition to choose among the different approaches to solve a problem.

– Turn your solution into effective Python code.

– Compare potential result in terms of scalability, complexity, and performance.

– Look into the territory of combinatorial game theory and winning strategies.